Dissertations / Theses: 'Smart agriculture'

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Grossi, Francesca <1983&gt. "Climate smart agriculture : beyond the theoretical definition." Doctoral thesis, Università Ca' Foscari Venezia, 2017. http://hdl.handle.net/10579/11973.

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It has been long recognized that effective climate policies need to account for economic, environmental and social impacts, exemplifying the notion of “triple-wins”. In the context, of rapid population growth and urbanization rate, this rationale has acquired even more impetus through the notion of climate smart agriculture applied to urban and peri-urban agriculture (UPA), i.e. farming practices that take place within or on the fringe of a city. Notwithstanding, this increasing popularity of UPA as climate-smart strategy, substantial challenges still remain, especially in terms of impacts’ assessment. This research aims to contribute to fill existing knowledge gaps, through the development of triple-wins comparative analysis, enabling the practical investigation of UPA´s impacts, and thus a better understanding of whether and to which extent these farming practices can support the building of more resilient and sustainable cities in low and middle-income countries. Accordingly, it builds upon a multi-methods research design comprising of: qualitative content analysis, case study research, and a multiple criteria decision analysis method, the PROMETHEE II.

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Mattos, Adriane Wassmassdorf. "Smart farming." Master's thesis, Universidade de Lisboa, Faculdade de Arquitetura, 2016. http://hdl.handle.net/10400.5/14196.

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Giua, Carlo <1994&gt. "Smart Farming in Italian agriculture: essays on adoption and diffusion dynamics shaping the agricultural digital transition." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2022. http://amsdottorato.unibo.it/10379/1/C.%20Giua%2C%202022.%20Smart%20Farming%20in%20Italian%20agriculture%20-%20essays%20on%20adoption%20and%20diffusion%20dynamics%20shaping%20the%20agricultural%20digital%20transition.pdf.

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Smart Farming Technologies (SFT) is a term used to define the set of digital technologies able not only to control and manage the farm system, but also to connect it to the many disruptive digital applications posed at multiple links along the value chain. The adoption of SFT has been so far limited, with significant differences at country-levels and among different types of farms and farmers. The objective of this thesis is to analyze what factors contributes to shape the agricultural digital transition and to assess its potential impacts in the Italian agri-food system. Specifically, this overall research objective is approached under three different perspectives. Firstly, we carry out a review of the literature that focuses on the determinants of adoption of farm-level Management Information Systems (MIS), namely the most adopted smart farming solutions in Italy. Secondly, we run an empirical analysis on what factors are currently shaping the adoption of SFT in Italy. In doing so, we focus on the multi-process and multi-faceted aspects of the adoption, by overcoming the one-off binary approach often used to study adoption decisions. Finally, we adopt a forward-looking perspective to investigate what the socio-ethical implications of a diffused use of SFT might be. On the one hand, our results indicate that bigger, more structured farms with higher levels of commercial integration along the agri-food supply chain are those more likely to be early adopters. On the other hand, they highlight the need for the institutional and organizational environment around farms to more effectively support farmers in the digital transition. Moreover, the role of several other actors and actions are discussed and analyzed, by highlighting the key role of specific agri-food stakeholders and ad-hoc policies, with the aim to propose a clearer path towards an efficient, fair and inclusive digitalization of the agrifood sector.

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Pivoto, Dieisson. "Smart farming : concepts, applications, adoption and diffusion in southern Brazil." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/178439.

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O Smart Farming (SF) é um novo conjunto de tecnologias que podem ser usadas para melhorar a tomada de decisões e a automação em atividades agrícolas. Para isso, alguns agricultores começaram a utilizar a Internet das Coisas (IoT), que é uma tecnologia que permite que os objetos sejam detectados ou controlados remotamente em infraestruturas de rede existentes. Esse processo tende a criar oportunidades para uma integração mais direta do mundo físico com sistemas baseados em computador, gerando maior eficiência, precisão e benefícios econômicos para os usuários de SF. Além das novas áreas como IoT, Computação em Nuvem, Cognitive Computing e Big Data, dois campos contribuíram para o desenvolvimento de SF: Agricultura de Precisão (AP) e Tecnologia da Informação (TI).A presente tese analisou o processo de inovação no contexto da SF, desde a produção de conhecimento científico até a fase de difusão dessas tecnologias na agricultura, sendo que, o objeto de estudo contemplou as propriedades rurais de grãos. A discussão e análise realizadas no trabalho têm como base teórica o aporte da economia evolucionária e o paradigma tecnoeconômico usado para analisar revoluções tecnológicas. O trabalho consistiu de três etapas metodológicas distintas A primeira, de caráter exploratório, foi realizada por meio de entrevistas com especialistas de diferentes áreas, visando melhor compreender o tema estudado. Na segunda etapa, realizou-se um levantamento na literatura científica acerca do tema. De posse dessas informações, operacionalizou-se uma pesquisa empírica para analisar a adoção dessas tecnologias no ambiente real. Para isso, foram aplicados 119 questionários com produtores de grãos da região Sul do Brasil (Paraná, Santa Catarina e Rio Grande do Sul), sendo adotada amostragem estratificada, pois foram considerados produtores cujas propriedades produzissem 50% ou mais da receita bruta em grãos.Com base nos resultados, foi possível inferir que as tecnologias de SF encontram-se no processo de gestação e emergência. Observou-se um intenso desenvolvimento científico em tecnologias como IoT e ambientes inteligentes, bem como um forte efeito de "spillover" de outras indústrias para a agricultura. Entretanto, espera-se que nos próximos anos, o número de inovações disponíveis ao mercado na área de SF cresça. Os principais fatores de adoção de SF observados no trabalho foram: a) aumento de produtividade, b) melhor qualidade de processo, c) redução de custos, e d) maior conhecimento de áreas cultivadas. Da mesma forma, alguns fatores aumentaram a adoção de tecnologias em diferentes intensidades e maneiras. A educação teve o efeito significativo e positivo na adoção de tecnologias georeferenciadas de amostragem de solo A adoção do piloto de pulverização do piloto automático e softwares de gerenciamento teve influência positiva do tamanho da área. Os resultados da tese sinalizaram que um maior grau de escolaridade, tende a aumentar probabilidade de adoção dessas tecnologias. As principais barreiras que atrasam a entrada dos produtores de grãos na SF foram: a) o preço dos equipamentos, b) baixa qualificação do trabalho rural c) a precariedade do acesso à Internet nas regiões rurais brasileiras, e d) necessidade de inserir muitos dados e informações em software. Verificou-se assim que as máquinas empregadas nos sistemas produtivos de grãos estão passando pelo processo de digitalização, especialmente pelo aumento da disponibilidade de equipamentos com sensores e processos automatizados. No entanto, na percepção do produtor rural, grande número de técnicos e consultores ainda não está adaptado ao novo contexto da agricultura. Com isso, permanece o questionamento acerca da capacidade do produtor e dos consultores técnicos de acompanhar e aproveitar o potencial das tecnologias de SF na tomada de decisão na propriedade rural. Os resultados desse trabalho, inéditos no contexto brasileiro, avançam no sentido de compreender a difusão da SF no contexto brasileiro.
Smart Farming (SF) is a modern set technologies that can be used to improve decision making and automation throughout agricultural activities. To accomplish this, some farmers are using the Internet of Things (IoT), which is new technology that allows objects to be sensed or controlled remotely across existing network infrastructures. Further, it can create opportunities for more direct integration of the physical world into computer-based systems, which can result in improved efficiency, accuracy, and economic benefits for SF users. Besides the new areas such as IoT, Cloud Computing, Cognitive Computing and Big Data, two fields have contributed to the development of SF: Precision Agriculture (PA) and Information Technology (IT). The present study analyzed SF’s innovative processes, beginning with the production of scientific knowledge through to SF’s final diffusion of these technologies into agriculture. The discussion and analysis are based on the theoretical contributions of the evolutionary economy and the techno-economic paradigms and were used to analyze technological revolutions. The work consisted of three distinct methodological steps First, to better understand the subject being studied, interviews were conducted with researchers and market professionals, from different areas, such as agriculture, electronics engineering and mechanization. During the second stage, text mining was used to analyze scientific literature on SF. In the third step an empirical research was carried out to analyze the adoption of SF technologies in real environment. To operationalize this step, a questionnaire was sent to grain farmers from the southern region of Brazil, which included Paraná, Santa Catarina, and Rio Grande do Sul. Since these grain' farmers produced 50% or more of the gross revenue in grains were included in the database. After the surveys were completed, the empirical data was used to analyze the adoption of these technologies. Based on the results, it was possible to infer that SF technologies are in the process of gestation and emergence. There has been intense scientific development in technologies, such as IoT and smart environments. Additionally, there has been a strong spillover effect from industries to agriculture. Because of this, it is expected that the number of SF innovations available to the market will grow over the next several years The study indicated main factors that a farmer chose to adopt SF were: potential increase in productivity, better process quality, cost reduction, and a greater knowledge of cultivated areas. Additionally, adding in these factors, education had the positive effect on the adoption of georeferenced soil sampling. The adoption of an autopilot spray pilot and management software was positively influenced by the size of the area. The results of the study have indicated that a higher level of schooling tends to increase the probability of adopting these technologies. It was also found that high equipment costs, the low qualification of rural workers, the precariousness of Internet access in Brazilian rural regions, and the need to insert a lot of data and information in specific programs available to take advantage of SF technologies are the main barriers faced by grain producers, which contribute to their delay in implementing SF technologies. Additionally, it has been verified that the machines used in the grain production systems are becoming digitalized—the availability of equipment with sensors and automated processes are rapidly increasing. However, from the famers’ perception, many technicians and consultants, such as agronomists and agricultural engineers, have not yet adapted to the new context of agriculture, with growing implementation of SF technologies amongst farmers. Thus, the question remains whether farmers and technical consultants can take advantage of available SF technologies and, if so, whether they can use these technologies to help them make decisions and monitor their farming practices. The results of this research can be used to further understand how SF technologies are being used among Brazilian grain producers.

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ALIEV, KHURSHID. "Internet of Things Applications and Artificial Neural Networks in Smart Agriculture." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2697287.

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Internet of Things (IoT) is receiving a great attention due to its potential strength and ability to be integrated into any complex systems and it is becoming a great tool to acquire data from particular environment to the cloud. Data that are acquired from Wireless Sensor Nodes(WSN) could be predicted using Artificial Neural Network(ANN) models. One of the use case fields of IoT is smart agriculture and there are still issues on developing low cost and power efficient WSN using advanced radio technologies for short and long-range applications and implementation of prediction tools. This is the reason why the target of this thesis is to develop a low cost and power efficient WSN and IoT based control system and analyze the best predictive model for such systems. With this purpose, we developed BLESensor node for short-range IoT applications and Internet of Plant(IoP) for long distance smart agriculture applications. A non-linear prediction model is developed in order to forecast acquired data from sensor nodes. BLESensor node Experimental test results reveal that newly developed BLESensor node has a good impact on the improved lifetime and applications could possibly make this emerging technological area more useful. The Android software has been tested on Samsung Galaxy SM-T311, running Android 4.4.2 and it works without any issues and it is supposed to work on all other Android devices equipped with BLE. The working temperature range of the BLESensor node is supposed to work goes from -20 °C to 70 °C due to battery temperature limits. The system has been tested in the climatic chamber (Challenge 250 from Angelantoni) present at the Neuronica Lab, which allowed the sensor to be software calibrated. Several measurements have been proven that each node offers an uncertainty of 1.2 °C for temperature. These values are acceptable for the type of application for which they are intended. The power consumption has been measured directly from scope analysis and simulating the code step by step and calculations resulted that the lifetime of the node lasts for a month. Considering a normal use of these sensors with a reasonable sampling time the lifetime could be increased. IoP node IoP node is a prototype device that works with WiFi protocol and collects temperature, humidity and soil moisture data of plants to the cloud. For IoP node, we have implemented a firmware, tested a prototype device and designed the PCB in OrCAD software and generated a Gerber file and developed an android application. Prediction model Comparisonofthreenon-linearmodelswithOakdatasetresultedinbetterperformance of NNARX model and we used NNARX model to predict 10 days step ahead maximum and minimum temperature and described the results of performances. The performance given by trained models in terms of Mean Square Error (MSE) for maximum temperature prediction provided an error of 0.8826 on unseen data for the month of September. Similarly, the performance of model predicting minimum temperature was tested and it resulted in an error value of 0.944. In conclusion, this work must be intended only as a proof-of-concept, although, the developed BLESensor system, IoP prototype device and predictive models showed expected optimum results, both in terms of functionalities and usability.

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Casten, Carlberg Carl Johan, and Elsa Jerhamre. "Artificial Intelligence in Agriculture : Opportunities and Challenges." Thesis, Uppsala universitet, Avdelningen för datorteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-443576.

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Artificial Intelligence (AI) is increasingly used in different parts of society for providing decision support in various activities. The agricultural sector is anticipated to benefit from an increased usage of AI and smart devices, a concept called smart farming technologies. Since the agricultural sector faces several simultaneous challenges, such as shrinking marginals, complicated pan-European regulations, and demands to mitigate the environmental footprint, there are great expectations that smart farming will benefit both individual farmers and industry stakeholders. However, most previous research focuses only on a small set of characteristics for implementing and optimising specific smart farming technologies, without considering all possible aspects and effects. This thesis investigates both technical and non-technical opportunities and hurdles when implementing AI in Swedish agricultural businesses. Three sectors in agriculture are scrutinized: arable farming, milk production and beef production. As a foundation for the thesis, a literature review revises former research on smart farming. Thereafter, an interview study with 27 respondents both explores the susceptibility and maturity of smart farming technologies and provides examples of technical requirements of three chosen applications of AI in agriculture. Findings of the study include a diverse set of aspects that both enable and obstruct the transition. Main identified opportunities are the importance smart farming has on the strategic agendas of several industry stakeholders, the general trend towards software technology as a service through shared machinery, the vast amount of existing data, and the large interest from farmers towards new technology. Contrasting, the thesis identifies main hurdles as technical and legislative challenges to data ownership, potential cybersecurity threats, the need for a well-articulated business case, and the sometimes lacking technical knowledge within the sector. The thesis concludes that the macro trend points towards a smart farming transition but that the speed of the transformation will depend on the resolutions for the identified obstacles.

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Arakelyan, Irina. "Climate-smart agriculture and rural livelihoods : the case of the dairy sector in Malawi." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28796.

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Over the last decade climate-smart agriculture (CSA) has been promoted as a new approach to deal with the impacts of climate change on agriculture while simultaneously trying to mitigate emissions and improve food security. This approach suggests that these multiple goals – adaptation, mitigation and food security - could be achieved simultaneously by adopting specific technologies. At its core, CSA describes agricultural interventions that can 1) sustainably increase agricultural productivity, and hence food security and farm incomes; 2) help adapt and build resilience of agricultural systems to climate change; and 3) reduce greenhouse gas emissions from agriculture (including crops, livestock and fisheries). The main focus of CSA is on smallholder producers, many of whom are already marginalized by existing food production systems, their livelihoods increasingly affected by changes in climate. Unsustainable agricultural practices are common amongst these groups. However, there is an increasing awareness of the need to sustain the natural resource base in order to maintain or increase productivity. Malawi is one of the poorest and least developed countries in the world, with chronic food insecurity affecting large parts of the population, and climate variability increasingly noticeable across the country. Agriculture is practiced predominantly on small holdings, with more than 80% of the population depending on land-based income. In this context, the introduction of climate-smart projects and technologies with the potential to deliver triple wins could improve farmers’ incomes and food security, increase their resilience to climate change impacts, as well as deliver global benefits via climate change mitigation. This dissertation looks at the adoption levels of various, potentially climate-smart agricultural practices by smallholder dairy farmers in Malawi, with the view of establishing the current level of engagement in these practices, and identifying the factors that influence adoption. Results show the importance of the socio-economic and institutional factors in explaining the probability of adopting different agricultural practices. In particular, the findings indicate the importance of well-informed and targeted extension support as one of the major enabling factors for the adoption of improved practices. The findings further show that farmers’ climate change perceptions play a key role in the adoption of climate-smart practices. Overall, the thesis concludes that a number of currently unsustainable dairy farm management practices could be improved upon to achieve double or triple-win benefits within a reasonably short timescale, many of them at low cost. In addition, limited adoption rates of several sustainable practices that are already in place could be improved with the provision of more training, knowledge sharing and extension advice and support on the benefits of these practices. However, the thesis argues that before implementing projects and policies that promise triple wins, a careful evaluation of benefits, including mitigation, adaptation, and food security, and risks must be carried out, as triple wins will not be achievable in many cases due to the local and external constraints including lack of skills and knowledge, and lack of funding. In this respect, whether climate-smart agriculture could become a globally sustainable approach to the climate change problem in agriculture, remains to be seen.

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BOTTA, ANDREA. "Agri.Q - Sustainable Rover for Precision Agriculture." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2963950.

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Jonarv, Hultgren Susanne, and Philip Tennevall. "Saving resources through smart farming : An IoT experiment study." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17968.

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Context: Smart farming, agritech, is growing in popularity and is starting to develop rapidly with some already existing technology that is implemented in agriculture for both industrial and private use. Objectives: The goal of this thesis is to investigate the beneﬁts and issues with implementing technology in agriculture, agritech. In this thesis the investigation and research is performed by conduction a literature study and an experiment. Realization: A prototype was created to monitor the soil moisture level and calculating the average soil moisture value, then water the plants when needed. This was then compared to a manually watered pot to investigate if agritech could reduce the water usage when maintaining plants. Results: The result of the experiment indicates that it is possible to improve the use of resources such as human labor, time spent on maintaining the plants and water usage. Conclusions: The conclusion of this thesis is with the help of agritech, human workers can spend more time on other tasks and maintain the technology implemented. Instead of observing the plants to see if they need watering and watering them manually. Water usage may also be minimized with the help of sensors that make sure the plants only get watered when needed by constantly checking the soil moisture level.

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Shaif, Ayad. "Predictive Maintenance in Smart Agriculture Using Machine Learning : A Novel Algorithm for Drift Fault Detection in Hydroponic Sensors." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42270.

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The success of Internet of Things solutions allowed the establishment of new applications such as smart hydroponic agriculture. One typical problem in such an application is the rapid degradation of the deployed sensors. Traditionally, this problem is resolved by frequent manual maintenance, which is considered to be ineffective and may harm the crops in the long run. The main purpose of this thesis was to propose a machine learning approach for automating the detection of sensor fault drifts. In addition, the solution’s operability was investigated in a cloud computing environment in terms of the response time. This thesis proposes a detection algorithm that utilizes RNN in predicting sensor drifts from time-series data streams. The detection algorithm was later named; Predictive Sliding Detection Window (PSDW) and consisted of both forecasting and classification models. Three different RNN algorithms, i.e., LSTM, CNN-LSTM, and GRU, were designed to predict sensor drifts using forecasting and classification techniques. The algorithms were compared against each other in terms of relevant accuracy metrics for forecasting and classification. The operability of the solution was investigated by developing a web server that hosted the PSDW algorithm on an AWS computing instance. The resulting forecasting and classification algorithms were able to make reasonably accurate predictions for this particular scenario. More specifically, the forecasting algorithms acquired relatively low RMSE values as ~0.6, while the classification algorithms obtained an average F1-score and accuracy of ~80% but with a high standard deviation. However, the response time was ~5700% slower during the simulation of the HTTP requests. The obtained results suggest the need for future investigations to improve the accuracy of the models and experiment with other computing paradigms for more reliable deployments.

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Issahaku, Gazali [Verfasser]. "Contribution of Climate-smart Agriculture to Farm Performance, Food and Nutrition Security and Poverty Reduction in Ghana / Gazali Issahaku." Kiel : Universitätsbibliothek Kiel, 2019. http://d-nb.info/1177797925/34.

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Tangerino, Giovana Tripoloni. "Método de amostragem de área agrícola com sensores embarcados: uma abordagem que leva em conta a variabilidade do campo." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/18/18145/tde-22072016-142046/.

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O trabalho apresentado destaca a importância do uso de práticas agrícolas que estimulem a manutenção da agricultura em níveis de alta produtividade, mas que, ao mesmo tempo, viabilizem uma minimização dos efeitos negativos da agricultura sobre o meio ambiente. O trabalho situa-se no contexto da aquisição de informação sobre a plantação considerando sua variabilidade para uso em Agricultura de Precisão. Foi proposto o desenvolvimento de um método inteligente de amostragem, que faz uso de sensores embarcados em veículos autônomos com capacidade de processamento em conjunto com técnicas geoestatísticas de amostragem. O processo de amostragem proposto leva em consideração a dependência espacial do campo, obtendo apenas a quantidade de informação necessária para reproduzir confiavelmente a variável em estudo para análises posteriores, amostrando mais densamente áreas de maior variabilidade e menos densamente áreas de menor variabilidade. O método desenvolvido estabelece a exploração em duas fases. Na fase de levantamento exploratório é utilizado um esquema de amostragem aninhado adaptado para as características do sistema de coleta de dados, nesta fase é realizada uma primeira avaliação sobre a escala espacial de variabilidade do campo. Na fase do levantamento principal são realizados ciclos de amostragens em grade, quantas vezes seja necessário até que critérios de decisão sejam atingidos. Nestes ciclos, ou etapas, são tomadas decisões com base na qualidade e na densidade de variabilidade das amostras. Tais decisões estabelecem se a área deve ser mais amostrada ou dividida em subáreas. A mínima precisão que se deseja alcançar é determinada pelo usuário e também limitada pelas capacidades estruturais da máquina que realizará aplicações a taxa variada. Em comparação com métodos tradicionais de obtenção de dados com sensores embarcados, as análises dos resultados mostram reduções que chegam a 98% na quantidade de pontos amostrados e redução de mais de 49% na distância final percorrida pelo veículo. Assim, a utilização do método proposto viabiliza a redução em custos computacionais de armazenagem e processamento, de gastos com combustíveis e de tempo de mão de obra. Os resultados evidenciam que é viável a amostragem baseada na densidade de variabilidade, racionalizando a quantidade, a qualidade e a disposição da informação obtida e armazenada. Em conclusão, o método de amostragem proposto apresenta potencial capacidade para sua utilização como uma ferramenta de apoio às novas práticas agrícolas, oferecendo uma alternativa mais eficiente e inteligente aos métodos tradicionais de coleta de dados.
The present work highlights the importance of using farming practices that encourage the maintenance of agriculture in high levels of productivity and, at the same time, enable reduction of the negative effects of agriculture on the environment. The work is in the context of acquisition of crop information considering its variability for use in Precision Agriculture. The development of a smart sampling method has been proposed, which uses of embedded sensors in autonomous vehicles with a processing capacity together with sampling geostatistics techniques. The sampling process takes into account the spatial dependence of the field, obtaining strictly the necessary amount of information to subsequent analyzes in a reliable way. It also aims to sample areas of higher variability more densily and areas of lower variability less densily. The developed method performs the exploration in two phases. In the exploratory phase, a nested sampling scheme adapted to the characteristics of the system is used. In this phase, the first assessment about the spatial scale of variability of the field is done. In the main survey phase, grid samplings are performed in stages, as many times as necessary until the decision criteria are reached. At the stages of the main survey, decisions are taken based on the quality and variability density of the samples, and this establishes whether the area should be better sampled or divided into subareas. The user determines the minimum precision to be reached. The structural capabilities of the machine, that will perform the variable rate applications, also restrict the system precision. The result analyses show that the number of samples reduced 98% and the final distance ran by the autonomous vehicle reduced 49%, compared to traditional methods that use embedded sensors to collect data. Thus, the use of the proposed method represents reduced computational costs of data storage and processing, fuel costs and manpower. The results show that the sampling based on variability density is feasible, rationalizing the quantity, quality and layout of the information obtained and stored. In summary, the proposed sampling method shows potential capacity to be used as a tool to support new agricultural practices, offering a more efficient and smart alternative to traditional methods of data collection.

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Nasser, Felix. "Climate-smart cocoa in Ghana: Examining discourses, trade-offs and implications for cocoa smallholders." Thesis, Stockholms universitet, Stockholm Resilience Centre, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-194713.

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Climate-smart agriculture (CSA) has emerged as a concept to address the multiple challenges and interdependencies of agriculture and climate change. Within CSA debates, equity and agroecology are especially contested. In Ghana, the concept of climate-smart cocoa (CSC) has emerged to simultaneously respond to high rates of deforestation, climate change pressures and low productivity of cocoa – Ghana’s principal agricultural export. Since CSC in Ghana is a nascent concept, it has received very little academic or critical appraisal. By applying a meta-discourse framework, this study aimed at gaining insights into local CSC discourses in Ghana and how these reflect global environmental meta-discourses. The adoption of certain discourses can reveal insights into subsequent policies and their implications for already marginalised cocoa smallholders. My findings are based on 37 qualitative interviews with cocoa smallholders, extension officers as well as governmental, non-governmental and private sector representatives of Ghana’s cocoa sector. Overall, my results suggest that an ecological modernisation discourse was the most pronounced meta-discourse reflected within CSC. A sustainable intensification discourse was the most common CSC practice to achieve a win-win between environment and development aspirations. Agroecological practices within CSC were mainly adopted to serve ecological modernisation discourses and are thus diametrically opposed to those promoted by more radical meta-discourses. Issues of contextual equity, especially regarding tree tenure, were ubiquitous, and discussed by a large majority of cocoa stakeholders. I caution that an overly simplistic win-win approach risks side-lining contextual equity issues and complexities regarding shade cover and agrochemical input. Community Resource Management Area Mechanisms (CREMAs) and other local governance mechanisms represent promising ways to balance trade-offs within the dominant CSC discourse by giving cocoa smallholders a stronger voice. However, given the dominance of large agricultural actors – such as foreign chocolate companies – within the current political economy of Ghana’s cocoa sector, this study cautions not to overestimate the potential of these local governance structures.

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Simpson, Christine Honan. "Conservation engineering outreach| Curriculum development and evaluation of Smart Fishing in the Bering Sea." Thesis, Alaska Pacific University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1571622.

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The purpose of this project to was to 1) develop, 2) instruct, 3) evaluate, and 4) revise a 5^th-12^th grade fisheries conservation engineering outreach program entitled Smart Fishing and the Bering Sea (SFBS).

Fishery resources are important to Alaska and Alaskans, but present complex conservation challenges including user conflicts and concerns about unsustainable fishing practices. Increasing Alaska residents' environmental literacy will enhance natural resource management decisions regarding fisheries. The intent of the SFBS program is to introduce students to ecological and economical factors that drive conservation engineering in the Bering Sea pollock fishery. I instructed the SFBS program to 93 students from four different public and private institutions in Anchorage, Alaska. My observations and participants' pre- and post-program concept maps were used to evaluate the effectiveness of the SFBS curriculum. Participants gained content knowledge from this fishery outreach program about the Bering Sea and commercial fishing. Program evaluation analysis and results were used to revise the curriculum and make suggestions to SFBS stakeholders.

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ARDENTI, FEDERICO. "CONTRIBUTION OF AGROECOLOGICAL MEASURES TOWARDS CLIMATE-SMART AND MULTIFUNCTIONAL FARMING SYSTEMS." Doctoral thesis, Università Cattolica del Sacro Cuore, 2023. http://hdl.handle.net/10280/135602.

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La continua crescita della popolazione mondiale, il progressivo degradamento dei suoli e il cambiamento climatico globale sono tra le più grandi sfide per l’umanità nel prossimo futuro. Pratiche non sostenibili di gestione del suolo e delle colture in agricoltura convenzionale hanno danneggiato lo stato di salute dell’agro-ecosistema e favorito il cambiamento climatico, attraverso la mineralizzazione della sostanza organica e il rilascio di forme reattive dell’azoto nelle acque e in atmosfera. L’adozione di nuove pratiche agricole sostenibili è stata indicata come una delle strade percorribili per l’adattamento dei sistemi agricoli ai cambiamenti climatici e per ridurre l’impatto negativo sull’ambiente. L’obiettivo principale di questa tesi è quello di valutare le performance delle pratiche sostenibili e clima-intelligenti (p.e., no-till, cover crop, e sub-irrigazione) in termini di potenziale produttivo delle colture, di incremento della qualità del suolo, e di riduzione dell’impatto climatico. Dai risultati emerge come le pratiche conservative (no-till e cover crop) siano in grado di generare rese colturali paragonabili ai sistemi convenzionali, mentre i sistemi irrigui efficienti (sub-irrigazione) siano particolarmente efficaci in condizioni climatiche siccitose. Inoltre, l’introduzione di queste pratiche agricole sostenibili ha consentito di preservare la qualità del suolo aumentandone il contenuto di azoto e carbonio e, allo stesso tempo, riducendo l’impatto climatico grazie al minor rilascio di nutrienti nell’ambiente.
Growing population, land degradation and climate change are significant threats to food security and human development. Conventional intensive farming is usually associated with soil quality depletion and environment pollution, through soil organic matter mineralization as carbon dioxide (CO2) and nitrogen release as reactive forms to atmosphere and water, thus promoting global climate change. The adoption of sustainable agroecosystems management is key for adapting to climate change while increasing soil quality and lowering agricultural impact on global warming. The main objective of this thesis is to evaluate the performances of climate-smart practices (i.e., no-till, cover crops, and subsurface drip irrigation) in terms of crop yield potential, soil quality increase and reduced impact on climate change. We concluded that conservation practices (no-till and cover crops) may ensure comparable crop yields to conventional system while high-efficient micro-irrigation systems (subsurface drip irrigation) are particularly effective under dry climate conditions. Moreover, such sustainable farming practices may (i) positively affect soil quality by enhancing carbon and nitrogen content into the soil, as well as (ii) reduce agricultural impact on climate change by lowering the release of nutrients to the environment.

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Shahzad, Muhammad Faisal [Verfasser], Awudu [Akademischer Betreuer] Abdulai, and Martin [Gutachter] Schellhorn. "Climate-Smart Agriculture in Pakistan: Implications for Climate Risk Management, Food Security, and Poverty Reduction / Muhammad Faisal Shahzad ; Gutachter: Martin Schellhorn ; Betreuer: Awudu Abdulai." Kiel : Universitätsbibliothek Kiel, 2020. http://d-nb.info/1218534028/34.

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COSTANTINO, ANDREA. "Improving Climate Control and Energy Performance in Greenhouses and Livestock Houses: Modeling Advances and Experimental Results." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2942126.

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Lee, Angela. "Seeding Sustainability Over Extracting Capital: Advancing a Vision for Technology Justice in the Canadian Agri-Food Sector." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42003.

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The detrimental consequences associated with industrial models of food production are becoming more difficult to ignore. In response, one dominant approach to mitigating the myriad environmental, social, and ethical harms relating to food has sought to increase the efficiency of agricultural outputs through scientific and technological innovation. Although technology certainly has some role to play in any vision of a sustainable future, technocratic approaches to problem solving are insufficient—and arguably inappropriate—for addressing many of the kinds of complex challenges that we face today. There are recent indications that both agri-food law and policy and innovation policy are being taken more seriously in Canada, which creates an opportunity to reflect more deliberately on their ends and means. This dissertation explores the topic of how laws, policies, and other tools of governance can work to better align technological innovations in the agri-food sector with shared environmental goals and ethical aspirations. Taking a critical legal perspective closely informed by feminist insights and the work of existing, analogous justice movements, I examine several interlinkages between technology, law, the environment, and society to evaluate some of the failings of existing approaches to food systems transformation and to offer a contribution to the conversation about alternative pathways. Given the context-specific nature of food systems and food systems governance, my focus is primarily on Canada, but the universal importance of food in a globalized world renders some comparative and transnational discussion unavoidable. I use case studies and discourse analysis to demonstrate that, when considered through a justice-oriented lens, several of the new and emerging technologies being championed in the agri-food sector may not be as beneficial as their proponents claim. Instead, they may serve to retrench injustice and cement existing, exploitative power structures, making them more difficult to challenge and change later down the line. Thus, if technologies are to serve public instead of private interests in the ways they are incentivized, designed, regulated, and used, we will need to see broad systemic and structural reforms informed by thoughtful shifts in our values and priorities, rather than merely reactive adjustments to our policies and practices. Though this undertaking will be difficult, it is not impossible; this dissertation offers one way to facilitate the process of seeding change for environmental sustainability and technological justice.

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Mohammad, Ammad Uddin. "UAV Routing Protocol (URP) for crop health management." Thesis, Brest, 2017. http://www.theses.fr/2017BRES0147/document.

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Les réseaux de capteurs sans fil sont maintenant un moyen crédible de collecte de données sur les cultures. L'installation d'une structure de communication fixe pour relayer les données surveillées depuis la tête de grappe jusqu'à sa destination finale peut être soit impraticable en raison de la topologie du terrain, soit prohibitive en raison du coût initial élevé. Une solution plausible consiste à utiliser des véhicules aériens sans pilote (UAV) comme moyen alternatif de collecte de données et de contrôle de supervision limité de l'état des détecteurs. Dans cet article, nous considérons le cas des parcelles agricoles disjointes comprenant chacune des grappes de capteurs, organisées de manière prédéterminée en fonction des objectifs d'élevage. Cette recherche vise à trouver une solution optimale pour la recherche de UAV et la collecte de données à partir de tous les capteurs installés dans un champ de culture. En outre, le protocole de routage des capteurs tiendra compte d'un compromis entre la gestion de l'énergie et les frais généraux de diffusion des données. Le système proposé est évalué en utilisant un modèle simulé et il devrait trouver une classe parmi toutes les sous-considérations
Wireless sensor networks are now a credible means for crop data collection. The installation of a fixed communication structure to relay the monitored data from the cluster head to its final destination can either be impractical because of land topology or prohibitive due to high initial cost. A plausible solution is to use Unmanned Aerial Vehicles (UAV) as an alternative means for both data collection and limited supervisory control of sensors status. In this paper, we consider the case of disjoint farming parcels each including clusters of sensors, organized in a predetermined way according to farming objectives. This research focuses to drive an optimal solution for UAV search and data gathering from all sensors installed in a crop field. Furthermore, the sensor routing protocol will take into account a tradeoff between energy management and data dissemination overhead.The proposed system is evaluated by using a simulated model and it should find out a class among all under consideration

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Sjögren, Henry, and Elias Embaye. "Jordbruk som innovationsnätverk : Hur påverkar närhet och distans innovationen?" Thesis, Uppsala universitet, Kulturgeografiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448019.

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As society moves towards being more and more digitalised, so does agriculture as well. Hopefully these digital tools will help us reach environmental goals through optimizing the use of resources in the agricultural sector. However, there are a few barriers to overcome for the digital transition to run smoothly. This thesis investigates a small portion of the agricultural innovation network in Sweden. This is done through multiple interviews and literary research. We can clearly see how this innovation network during the last decades has moved towards becoming more knowledge centered and how the model triple helix now easily can be applied to the network. The network is then analysed using Ron Boschma’s five proximity factors and it becomes clear that concerning the agricultural innovation network, the cognitive and institutional proximity is of great importance for the innovational strength. It also becomes clear that the different proximity factors seldom act alone, but instead build upon each other to increase the negative respectively positive outcomes. Moreover it is shown that regarding the agricultural innovation network in Sweden, it can only benefit from improving the proximity factors, which is different from other types of industries.

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Kinhou, Viwagbo. "La souveraineté alimentaire dans une perspective de sécurité alimentaire durable : illusion ou réalité ? : le cas de la filière riz dans la commune de Malanville au Nord-Est du Bénin." Thesis, Rennes 2, 2019. http://www.theses.fr/2019REN20009/document.

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Le riz est devenu une denrée de grande consommation au Bénin et les études prospectives le présentent comme la céréale qui sera la plus consommée en Afrique de l’Ouest dans les prochaines décennies. Malgré le potentiel rizicole dont dispose le Bénin et les stratégies nationales de promotion du riz, l’offre domestique est faible par rapport aux ambitions affichées par ce pays de parvenir à la souveraineté alimentaire. Cette thèse vise à analyser les mesures de politiques de souveraineté alimentaire en matière de riz dans une perspective de sécurité alimentaire durable. Des enquêtes exploratoires et approfondies ont été réalisées auprès des riziculteurs. Des données quantitatives et qualitatives ont été collectées à l’aide de questionnaires et guides d’entretien. Les résultats de cette recherche montrent que le riz local dispose d’un avantage comparatif par rapport au riz importé. Cependant, des efforts doivent être faits pour réduire les coûts de production afin de rendre le riz malanvillois plus compétitif. Le niveau d’instruction, l’accès au crédit, l’expérience en riziculture et le statut social du producteur peuvent contribuer à améliorer le taux d’adoption des technologies et augmenter la productivité. Une politique rizicole combinant simultanément une politique de soutien du prix, de subvention d’engrais spécifiques au riz, de culture attelée et agricole climato-intelligente augmenterait la production et permettrait de parvenir à la souveraineté alimentaire
Rice has become a primary consumed product in Benin. Studies have revealed it will become the most consumed cereal in west Africa within the next decades. Despite the resources Benin possesses favouring rice culture and the government measures to promote it, the household supply remains unsatisfactory when compared to the objective set by the country to reach food sovereignty. The present essay analyses the government policies in order to reach a sustainable food sovereignty through rice culture. In depth, exploratory surveys have been conducted among the rice farmers. Qualitative and quantitative data was collected through structured questionnaires and guided interviews revealing the comparative advantage local rice has over imported one. Efforts have yet to be made in order for Malanville rice famers to reduce their production costs and become more competitive. Education level, access to loans, rice farmers experience as well as their social status are the key factors influencing the implementation of new technologies allowing an increase of productivity. Rice production and food sovereignty should be attained by implementing simultaneously income support policies, funded fertilizers, climate-smart culture and ploughing by oxen

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Ahmed, Faizan. "Global IoT Coverage Through Aerial And Satellite Network." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281245.

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Internet of Things (IoT) and Machine Type Communication (MTC) have got more momentum in the last few years but still, need to be penetrated with their full swing in our daily life. This can be possible with general framework that provides global network coverage. Non-terrestrial networks comprised of satellites and aerial platforms are expected to provide next-generation communication services in underserved and un-served areas by ensuring the quality of service that cannot be covered by existing terrestrial networks owing to economical and geographical limitations. The aim of this thesis is to formulate a set of massive and critical MTC use cases such as global environment monitoring, tracking of shipping containers and smart agriculture, and assess their comprehensive requirements like data size, sensor node density and uplink capacity and discuss possible network architectures and deployments focusing on satellite or aerial networks. A rigorous discussion on different network architectures to address the requirements have been presented, that involve (1) Low Earth Orbit (LEO) satellite based network, (2) High Altitude Platform (HAP) based network, and (3) HAP and UAV based network. The proposed network architectures have been simulated and analyzed using MATLAB tools for respective use cases in terms of required number of satellites or aerial platforms. The criteria for selection of network architectures for the use cases are based on the minimum number of satellites or aerial platforms. The results show that LEO constellation consisting of 260 satellites are feasible concerning deployment and management for global environment monitoring network. Similarly, 1440 LEO satellites provide global coverage for tracking of shipping containers. Smart agriculture use case requires high throughput, and hence HAP and UAV integrated network architecture is more realistic for a fully autonomous system as compared to other network architectures. Cooperative control and management of set of agricultural machines can be performed at the UAV. Simulation results show that single UAV can be capable of commanding and controlling the agricultural smart machines in one square kilometer crop field and can send the summary of events to the central station via a HAP.
Internet of Things (IoT) och maskintypkommunikation (MTC) har fått mer fart under de senaste åren men måste fortfarande penetreras med sin fulla sväng i vårt dagliga liv. Detta kan vara möjligt med allmän ramverk som ger global nätverkstäckning. Icke- markbundna nät bestående av satelliter och flygplattformar förväntas tillhandahålla nästa generations kommunikationstjänster i undervärdiga och obetjänade områden genom att säkerställa kvaliteten påtjänster som inte kan täckas av befintliga marknät pågrund av ekonomiska och geografiska begränsningar. Syftet med den här avhandlingen är att formulera en uppsättning massiva och kritiska MTC-användningsfall som global miljöövervakning, spårning av fraktcontainrar och smart jordbruk, och utvärdera deras omfattande krav som datastorlek, sensornoddensitet och upplänkkapacitet och diskutera möjliga nätverk arkitekturer och distributioner med fokus påsatellit- eller flygnät. En rigorös diskussion om olika nätverksarkitekturer för att möta kraven har presenterats, som involverar (1) Low Earth Orbit (LEO) satellitbaserat nätverk, (2) High Altitude Platform (HAP) baserat nätverk, och (3) HAP och UAV baserat nätverk. De föreslagna nätverksarkitekturerna har simulerats och analyserats med MATLAB-verktyg för respek- tive användningsfall i termer av det nödvändiga antalet satelliter eller flygplattformar. Kriterierna för val av nätverksarkitekturer för användningsfallen är baserade pådet minsta antalet satelliter eller flygplattformar. Resultaten visar att LEO-konstellationen bestående av 260 satelliter är möjlig när det gäller distribution och hantering för globalt miljöövervakningsnätverk. Påliknande sätt ger 1440 LEO-satelliter global täckning för spårning av fraktcontainrar. Småjordbruksanvändningsfall kräver hög kapacitet, och följaktligen är HAP och UAV integrerad nätverksarkitektur mer realistisk för ett helt autonomt system jämfört med andra nätverksarkitekturer. Kooperativ kontroll och hantering av jordbruksmaskiner kan utföras vid UAV. Simuleringsresultat visar att en enda UAV kan vara kapabel att kommandera och kontrollera jordbrukssmarta maskiner i ett kvadratkilometer grödningsfält och kan skicka sammanfattningen av händelser till centralstationen via HAP.

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TAMAGNONE, PAOLO. "Progress in planning mitigation and adaptation strategies driven by indigenous knowledge and numerical modelling to face hydrometeorological hazards in the Sahel." Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2912982.

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Wahl, Jacob D. "Development and Characterization of an IoT Network for Agricultural Imaging Applications." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2131.

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Smart agriculture is an increasingly popular field in which the technology of wireless sensor networks (WSN) has played a large role. Significant research has been done at Cal Poly and elsewhere to develop a computer vision (CV) and machine learning (ML) pipeline to monitor crops and accurately predict crop yield numbers. By autonomously providing farmers with this data, both time and money are saved. During the past development of a prediction pipeline, the primary focuses were CV and ML processing while a lack of attention was given to the collection of quality image data. This lack of focus in previous research presented itself as incomplete and inefficient processing models. This thesis work attempts to solve this image acquisition problem through the initial development and design of an Internet of Things (IoT) prototype network to collect consistent image data with no human interaction. The system is developed with the goals of being low-power, low-cost, autonomous, and scalable. The proposed IoT network nodes are based on the ESP32 SoC and communicate over-the-air with the gateway node via Bluetooth Low Energy (BLE). In addition to BLE, the gateway node periodically uplinks image data via Wi-Fi to a cloud server to ensure the accessibility of collected data. This research develops all functionality of the network, comprehensively characterizes the power consumption of IoT nodes, and provides battery life estimates for sensor nodes. The sensor node developed consumes a peak current of 150mA in its active state and sleeps at 162µA in its standby state. Node-to-node BLE data transmission throughput of 220kbps and node-tocloud Wi-Fi data transmission throughput of 709.5kbps is achieved. Sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day. This network can be utilized by any application that requires a wireless sensor network (WSN), high data rates, low power consumption, short range communication, and large amounts of data to be transmitted at low frequency intervals.

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Klingner, Matthias. "Konzeptwechsel als Chance – Schwarmtechnologien und Digitalisierung der Landwirtschaft." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234731.

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Fitzek, Frank H. P. "Echtzeitfähige Funkvernetzung für hochautomatisierte Arbeitsmaschinen und -prozesse in der Landwirtschaft." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234764.

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Trautz, Dieter, and Insa Kühling. "Automatisierungspotential und Technikanforderungen im ökologischen Landbau." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234781.

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Leeb, Theodor. "Technikentwicklungen für Nachhaltigkeit." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234798.

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Dueck, Gunter. "Landwirtschaft 4.0 - Disruptive Innovationen und Herausforderungen an menschzentrierte Technikentwicklung." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234807.

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Gruppioni, Carlotta. "Comparing semantics based and not semantics based Information Flow Processing in a case of drone-driven agricultural irrigation." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016.

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Device connessi come termostati intelligenti e sistemi d’illuminazione automatica stanno entrando nelle case, ma un’altra grande opportunità per l’Internet of Things si trova all’aperto, nel settore agricolo. L’obiettivo di questo lavoro di tesi è studiare il modo migliore di implementare l’infrastruttura di comunicazione Machine-to-Machine (M2M) per il progetto Agri-Eagle sviluppato alla VTT Technical Research Centre of Finland. In particolare, questo lavoro si focalizza sulla comunicazione M2M che segue il modello publish/subscribe, e l’obiettivo è analizzare come Smart-M3 e MQTT con JSON-LD sono in grado di soddisfare i requisiti del sistema Agri-Eagle. Per valutare la fattibilità di questi due soluzioni, sono state fatte implementazioni di riferimento dell'infrastruttura di comunicazione M2M con entrambe le tecnologie. Queste implementazioni di riferimento sono state poi valutate nelle seguenti aree: prestazioni e scalabilità, facilità di sviluppo e progettazione sforzi, l'interoperabilità, espressività ed estensibilità. Grazie all’implementazione in due fasi differenti, basate sui differenti requisiti del progetto, e l'analisi e test degli aspetti sopra citati, l'autore è stato in grado di capire che sia Smart-M3 e MQTT con JSON-LD soddisfano i requisiti del progetto.

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Zecha, Christoph. "XAVER - Roboterschwarm für das Feld." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234755.

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Brunsch, Reiner, and Cornelia Weltzien. "Gesunde Ernährung, Anforderungen und Potentiale der Rückverfolgbarkeit und Transparenz-Idee der dezentralen Wertschöpfungsketten." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-234777.

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Cavina, Andrea. "Recycling the city: a sustainable planning framework to reduce, reuse and recycle urban residual spaces." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8710/.

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Cities are key locations where Sustainability needs to be addressed at all levels, as land is a finite resource. However, not all urban spaces are exploited at best, and land developers often evaluate unused, misused, or poorly-designed urban portions as impracticable constraints. Further, public authorities lose the challenge to enable and turn these urban spaces into valuable opportunities where Sustainable Urban Development may flourish. Arguing that these spatial elements are at the centre of SUD, the paper elaborates a prototype in the form of a conceptual strategic planning framework, committed to an effective recycling of the city spaces using a flexible and multidisciplinary approach. Firstly, the research focuses upon a broad review of Sustainability literature, highlighting established principles and guidelines, building a sound theoretical base for the new concept. Hence, it investigates origins, identifies and congruently suggests a definition, characterisation and classification for urban “R-Spaces”. Secondly, formal, informal and temporary fitting functions are analysed and inserted into a portfolio meant to enhance adaptability and enlarge the choices for the on-site interventions. Thirdly, the study outlines ideal quality requirements for a sustainable planning process. Then, findings are condensed in the proposal, which is articulated in the individuation of tools, actors, plans, processes and strategies. Afterwards, the prototype is tested upon case studies: Solar Community (Casalecchio di Reno, Bologna) and Hyllie Sustainable City Project, the latter developed via an international workshop (ACSI-Camp, Malmö, Sweden). Besides, the qualitative results suggest, inter alia, the need to right-size spatial interventions, separate structural and operative actors, involve synergies’ multipliers and intermediaries (e.g. entrepreneurial HUBs, innovation agencies, cluster organisations…), maintain stakeholders’ diversity and create a circular process open for new participants. Finally, the paper speculates upon a transfer of the Swedish case study to Italy, and then indicates desirable future researches to favour the prototype implementation.

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van, Staden Wilma. "A review of Climate-Smart system innovations in two Agricultural Colleges in the North West Province of South Africa." Thesis, Rhodes University, 2018. http://hdl.handle.net/10962/63426.

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This study was centred on the Agricultural Innovation System in the North West Province, South Africa as a response to climate change. The study developed during a time when Climate-Smart Agriculture emerged in policy and was developed as a strategic agricultural innovation process in response to changes in climate that increased food insecurity. The Agricultural Colleges embedded in the agricultural system realised that they were teaching students without a clear provision for climate change and therefore needed to initiate climate responsive innovations to comply with the Climate-Smart strategy that had been proposed by the provincial authorities. This provided the context for the study to track and support the innovation process of transitioning towards Climate-Smart responsive curriculum and learning practices within the system. A theoretical framework for the study was developed using a Cultural Historical Activity Theory perspective. This allowed the researcher to approach the research process as two case studies of innovation within the Agricultural Innovation System of the North West Province. The study developed as an iterative process of innovation support and tracking. At the early stages of the research process, data were generated through document analysis and a survey completed by the research participants at the preliminary consultative workshop. The contextual data allowed the researcher to begin to develop a clear contextual profile for both case studies. The consultative workshops were held to orientate the research around the central problems and challenges related to curriculum alignment with provincial Climate-Smart Agricultural policies. The methodology thereafter was developed as an iterative process of successive intervention-innovation workshops where the participating staff in each college reviewed their curriculum with the support of a Climate-Smart Innovation Tool. This tool was developed as a mediating resource for participants to undertake intervention work towards curriculum innovation in their context. The historical analysis from the two consultative workshops and the data derived from the initial use of the Climate-Smart Innovation Tool was used to model the activity systems in the respective colleges and the provincial system. This analysis enabled the researcher to scope how the system was currently functioning and how it had changed over time. During the workshops, curriculum innovations were reviewed and a fuller picture of the challenges of system innovation emerged, especially from a curriculum innovation vantage point. This system analysis was used to analyse emergent tensions and contradictions within the system and to build a picture of the complexities of participating staff initiating innovations towards Climate-Smart responsiveness in the colleges and within the Agricultural Innovation System. During the review and tracking of the supported innovation process the Climate-Smart Innovation Tool was developed into online sub-tools where either Departments or individual lecturers could review and track their own Climate-Smart responsiveness. The tool was shown to be a useful tool for surfacing contradictions, and identifying absences, and thus for charting out the start of reflexive learning and change processes needed for introducing climate responsive knowledge into the system. The study reveals that catalysing of curriculum and learning system innovation aligned with wider innovations in the agricultural innovation system requires specific tools, time and the understanding of the importance of micro-level innovation. The innovations within the system revealed the significance of allowing for time and processes that facilitate ‘ascending’ from the abstract concept of Climate-Smart Agriculture into more concrete curriculum processes. The curriculum review tool developed for this study served as an important double stimulation tool, along with activity system mapping, and ongoing refinement and clarification of the object of Climate-Smart Agriculture and associated contradictions and action plans for climate smart responsiveness in the college context. The tools and processes that were developed during this study, assisting in the emergence of micro-level innovation of the curriculum and learning system. The barriers and processes hampering curriculum and learning innovation within the system were identified. The study concludes with the recommendations on how a Climate-Smart innovation process might best be supported with reflexive tools within a curriculum and learning system during a time of institutional flux.

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Thorn, Jessica Paula Rose. "Ecosystem services, biodiversity and human wellbeing along climatic gradients in smallholder agro-ecosystems in the Terai Plains of Nepal and northern Ghana." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:3319dafc-5b0c-436a-b653-a623fc3e8de4.

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Increasingly unpredictable, extreme and erratic rainfall with higher temperatures threatens to undermine the adaptive capacity of food systems and ecological resilience of smallholder landscapes. Despite growing concern, land managers still lack quantitative techniques to collect empirical data about the potential impact of climatic variability and change. This thesis aims to assess how ecosystem services and function and how this links with biodiversity and human wellbeing in smallholder agro-ecosystems in a changing climate. To this end, rather than relying on scenarios or probabilistic modelling, space was used as a proxy for time to compare states in disparate climatic conditions. Furthermore, an integrated methodological framework to assess ecosystem services at the field and landscape level was developed and operationalised, the results of which can be modelled with measures of wellbeing. Various multidisciplinary analytical tools were utilised, including ecological and socio-economic surveys, biological assessments, participatory open enquiry, and documenting ethnobotanical knowledge. The study was located within monsoon rice farms in the Terai Plains of Nepal, and dry season vegetable farms in Northern Ghana. Sites were selected that are climatically and culturally diverse to enable comparative analysis, with application to broad areas of adaptive planning. The linkages that bring about biophysical and human changes are complex and operate through social, political, economic and demographic drivers, making attribution extremely challenging. Nevertheless, it was demonstrated that within hotter and drier conditions in Ghana long-tongued pollinators and granivores, important for decomposition processes and pollination services, are more abundant in farms. Results further indicated that in cooler and drier conditions in Nepal, the taxonomic diversity of indigenous and close relative plant species growing in and around farms, important for the provisioning of ecosystem services, decreases. All other things equal, in both Nepal and Ghana findings indicate that overall human wellbeing may be adversely effected in hotter conditions, with a potentially significantly lower yields, fewer months of the year in which food is available, higher exposure to natural hazards and crop loss, unemployment, and psychological anxiety. Yet, surveys indicate smallholders continue to maintain a fair diversity of species in and around farms, which may allow them to secure basic necessities from provisioning ecosystem services. Moreover, farmers may employ adaptive strategies such as pooling labour and food sharing more frequently, and may have greater access to communication, technology, and infrastructure. Novel methodological and empirical contributions of this research offer predictive insights that could inform innovations in climate-smart agricultural practice and planning.

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Cortez, Zaga Christopher Americo, and Llamacponcca Victor Martin Casas. "Modelo para el intercambio de bienes en el sector agrícola empresarial peruano utilizando las tecnologías Smart Contracts y Blockchain." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2020. http://hdl.handle.net/10757/653295.

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El sector agrícola empresarial peruano debe tener una infraestructura que no limite la comercialización de bienes entre los agricultores por la dependencia de un intermediario. Sin embargo, esta no es la realidad porque actualmente para realizar la compra o venta de un producto, se necesita de un intermediario para validar ciertas actividades. Una alternativa para reducir esta dependencia es el uso de herramientas web a través del internet para que los agricultores puedan ofrecer sus productos al mercado y los compradores tengan una mayor variedad para su elección; sin embargo, esto genera una gran preocupación en la población ya que existe una desconfianza por la falta de seguridad que esto conlleva. Smart Contract y Blockchain, son tecnologías emergentes que están surgiendo para ofrecer nuevas oportunidades para el diseño de mercados descentralizados, estos permiten incrementar la seguridad de las transacciones, ahorros al no depender de un intermediario, aumentar la confianza de los agricultores y mejorar el crecimiento del país. Este proyecto propone una modelo que utiliza las tecnologías Smart Contract y Blockchain aplicadas en el sector agrícola empresarial peruano, que permite tanto al comprador como al vendedor comercializar productos agrícolas. Los resultados de las empresas encuestadas y tres expertos fueron satisfactorios, muchas de las empresas han tenido buena aceptación según la encuesta realizada, el 50% de las empresas considera como “Muy aceptable” el modelo según las características mencionadas en la encuesta y el otro 50% como "Aceptable"; así mismo, los expertos validan el modelo de acuerdo a los casos de uso de Blockchain y la metodología Solium para verificar que los Smart Contract se definieron correctamente.
The Peruvian agricultural sector must have an infrastructure that does not limit the commercialization of goods among farmers by the dependence of an intermediary. However, this is not the reality because currently to make a purchase or sale of a product, you need an intermediary to validate certain activities. An alternative to reduce this dependence is the use of web tools through the internet so that farmers can offer their products to the market and buyers have a greater variety for their choice; however, this generates a great concern in the population since there is a distrust for the lack of security that this entails. Smart Contracts and Blockchain, which are emerging technologies that offer new opportunities for decentralized market designs, these allow to increase the security of the transactions, savings by not depending on an intermediary, increase the confidence of the farmers and improve the country's growth. This project proposes a model that uses Smart Contract and Blockchain technologies applied in the Peruvian agricultural business sector, which allows both the buyer and the seller to commercialize agricultural products. The results of the surveyed companies and three experts were satisfactory, many of the companies have had good acceptance according to the survey carried out, 50% of the companies consider the model as "Very acceptable" according to the characteristics mentioned in the survey and the other 50 % as "Acceptable"; Likewise, the experts validate the model according to the Blockchain use cases and the Solium methodology to verify that the Smart Contracts were defined correctly.
Tesis

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WU, PENG-TA, and 鄔朋達. "Smart Contract of Organic Agriculture Subsidy." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/e7ucp8.

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碩士
東吳大學
資訊管理學系
107
Recently, the blockchain technology has been valued. With the support of resources across many industries, an increased number of innovations are made available, the emerging commercial modes in the financial technology in particular. The government, by employing the smart contracts, can change the way they deliver services and business processes to reduce the administrative cost. The government, in order to protect the interests of farmers, implements plural subsidy policies. The subsidy amount exceeds over half of the annual agricultural budget and the subsidy given to organic agriculture hikes year by year. Without being certified by organic agriculture certification companies, it is not allowed to make any organic claim. When farmers consider converting to organic, the costs may hinder their willingness, so the government grants subsidies to farmers in need of organic certification. The study employed the ethereum smart contract based on the blockchain technology to develop a prototype of the organic farming subsidy payment system. Compare the system with the current subsidy process, it shows that the system has the following advantages: 1. All applications must be submitted through the online application system, and farmers can apply for subsidies online at any time. 2. Integrate farmers' information flow into government's. E-procedures can reduce the working hours of review. 3. Using smart contracts to store data on the blockchain. With subsidies granted by cryptocurrency to ensure timely releases of funds.

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Montero, Erick Alejandro Moran, and 任秉晨. "IoT in agriculture - a proposal of smart agriculture in Ecuador." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/37cr35.

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碩士
國立政治大學
國際經營管理英語碩士學位學程(IMBA)
107
Agriculture in Ecuador is not efficient due to the limitations in terms of technology in its production processes. Research has shown that Ecuadorian farmers do not use any technology to work their land, generating waste of resources and slow development. This study aims to show the historical delay of certain countries, using Ecuador as an example, due to the lack of information. In this context, the application of IoT throughout the world has been studied, in order to evidence the positive results obtained. Based on a content analysis, this research takes a brief journey, from the four Industrial Revolutions to the current applications of the IoT (Internet of Things) technology in agriculture. In addition, the research analyzes the situation of agriculture in Ecuador with respect to the use of technology. Additionally, two simple and useful IoT systems have been studied and explained, with the purpose of illustrating their specific and real positive effects. Finally, a proposal for the implementation IoT Technology in agriculture is analyzed, through the associative and cooperative models, revealing a promising scenario of opportunities.

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Shih, Ching-Chiu, and 施勁秋. "Artificial Intelligence of Things for Smart Agriculture." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/sz9v2c.

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碩士
國立臺灣科技大學
電機工程系
107
Artificial intelligence (AI) and the Internet of Things (IoT) technologies have been on the rise in recent years. These technologies are based on installed sensors and big data that these sensors collect. Data sensing and analysis have therefore become a popular research topic. The present study integrated AI and the IoT with the knowledge of agricultural experts to develop an expert agricultural cultivation system that realizes cultivation management and farm operations without human labor for the purpose of establishing an optimal irrigation schedule and automated cultivation system. In the present study, an Artificial Intelligence of Things architect that uses low-power-consumption outdoor IoT sensors in the sensing layer was constructed. A dynamic environment detection mechanism was proposed for sensor data transmission, in which data was transmitted on the basis of data characteristics to reduce the total number of transmission times and save energy. In the communication layer, low-power-consumption Long Range Wide Area Network (LoRaWAN) was used in combination with Message Queuing Telemetry Transport protocol to increase the transmission distance and reduce energy consumption. The edge layer consisted of an AI module and irrigation module. In the AI module, a data collection function was used to collect sensing data, and a growth status function was used to calculate the maturity level of crops by using color blocks. A plant water requirement function was used to predict the amount of water needed by the crops. Extreme gradient boosting (XGBoost) was adopted to build a prediction model. The algorithm of XGBoost effectively reduces variance and reduce bias, thereby ensuring that the prediction reflects the actual situations. The watering decision function schedules watering according to expert experience and performs watering prediction. The irrigation module receives messages from the AI module and delivers them to the watering controller, thereby completing a cultivation system without human labor. This study compared the prediction accuracy of the generalized additive model, support vector machine, random forest, and XGBoost and determined that XGBoost had optimal prediction accuracy and obtained the lowest mean square error (0.0085). The experimental results of the proposed architecture were revealed to show 50% and 30% less water consumption during irrigation than those obtained from using fixed and threshold watering times, respectively. The proposed method demonstrates more precise watering of crops. The dynamic environment detection transmission mechanism exhibited a 97.8% lower communication frequency compared with the fixed-schedule transmission mode and effectively reduced the overall energy consumption during transmission. In the analysis of human labor, the proposed system was discovered to reduce the cultivation time by 40.94% compared with manual cultivation, thus facilitating more effective farm management. The experimental results indicated that the proposed method can serve as a convenient cultivation model for farmers.

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Chen, Yu-Xian, and 陳昱憲. "Arduino-based IoT Framework for Smart Agriculture Application:A Case Study for Smart Coops." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/wy4gh6.

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HOU，SHENG-TAI and 侯聖泰. "Analysis of Smart Agriculture Irrigation Based on Fuzzy Control." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/9b946t.

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碩士
國立高雄科技大學
電子工程系
107
In 2050, the global population is estimated to reach 9.5 billion people. The estimated food demand will be the double of the current. It is imperative to use science and technology agriculture to increase food productivity. In Taiwan, agricultural revenue in 2015 was 500 billion NTD, but the food self-sufficiency rate was only 31.4%. Due to the gradual aging of the rural population, the shortage of manpower, coupled with the increasingly severe climate change, has led to considerable impact on agricultural production capacity. 　　According to the statistics of the Water Resources Department of the Ministry of Economic Affairs, agricultural irrigation water accounts for 73% of the total water consumption of the whole Taiwan. Most of the current irrigation systems only rely on experience to judge the dry moisture supply of the soil surface, which is easy to cause water waste. This study uses fuzzy theory to further explore the current agricultural irrigation system, providing different water needs according to the different root depths of its crops. Numeric results shown that the accuracy of the irrigation iferred by the proposed fuzzy system is about 90.8%. Followed by smart agriculture management, tracking soil moisture, precise irrigation, avoiding Keywords: Fuzzy algorithm, irrigation water, Smart agriculture,Fuzzy inference

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Lin, Chen-I., and 林貞誼. "A Study on Product Strategy of Smart Agriculture Solution." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/zjb76m.

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碩士
國立政治大學
經營管理碩士學程(EMBA)
107
The supply and demand situation of the agricultural industry and related issues directly affect the stability of human society and economic development. Relevant agricultural management units of various governments have launched various development plans related to the development of smart cities, as well as policies and programs to enhance agricultural development with smart technology, and hope to use ICT, Internet, and IOT-Internet of Things ), mobile networks, big data (Big Data), cloud technology (cloud computing / cloud platform), intelligent robot (AI) and blockchain (Block Chain), fifth-generation mobile communication technology and other smart technologies come Enhance the performance of supply and demand operations in the agricultural industry, and many well-known groups at home and abroad have also cooperated to develop various smart agricultural solutions. How can relevant smart agricultural solutions help the agricultural industry to break through the current challenges? How can the agricultural industry chain increase the overall value of the agricultural industry chain through smart agricultural solutions? How can the providers of smart agricultural solutions be? Growth in performance and revenue growth? This study is mainly to explore the current difficulties encountered by the agricultural industry as a starting point to define the problems that the agricultural industry needs to solve, as well as solutions that can be adopted. Through research to summarize the smart solutions for related agricultural applications, and the business value they bring, there are bottlenecks in related applications. And This study takes the case of agricultural smart solutions launched by internationally renowned groups in strategic alliances as an example to explore how to improve the efficiency and value of the agricultural industry chain, and to study how the relevant groups in this case can communicate through the inter-group strategic alliance. To provide a more complete and relevant smart agricultural solution to create a greater competitive advantage. This study also makes recommendations based on the research results as a reference for other related research.

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Cambra, Baseca Carlos. "PLAtaforma TEcnológica Multimedia para la Agricultura de Precisión (PLATEM Precision Agriculture)." Doctoral thesis, 2020. http://hdl.handle.net/10251/135820.

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[ES] Hay muchos trabajos relacionados con la automatización de procesos en agricultura. Con la revolución del Internet de las Cosas (del Inglés, Internet of things o IoT) están apareciendo en el mercado multitud de dispositivos capaces de interconectar sensores. Más enfocado a la agricultura intensiva, aparecen muchas comercializadoras de productos IoT que, aunque sus desarrolladores aseguran que son capaces de automatizar las tareas en los cultivos, vemos que no es así. Muchos productos tecnológicos desarrollados para ser usados en la agricultura de precisión, como son los programadores de riego tele-gestionados funcionan de forma independiente con otras tecnologías de la agricultura. En estos momentos y con el avance tecnológico actual, se debe integrar una programación de riego acorde a las necesidades reales del cultivo en tierra y con unas mediciones de necesidades de cultivo tomadas vía satélite o mediante dron desde el aire adaptando las variables de forma automática en una única plataforma de gestión. Si el patrón de producción de mi explotación funciona bien, la PLAtaforma TEcnológica Multimedia (PLATEM) permitirá compartir la estrategia seguida para que socios cooperativistas o personas que estén registrados en la red social, puedan verla y ver los contenidos publicados en ella sobre sistemas de control agrícolas. Esta tesis se centra en la investigación, diseño y desarrollo de nuevas tecnologías para integrar todos los sistemas presentes en un sistema automáticos, considerando, desde la monitorización de parámetros, hasta el procesado y toma de decisiones para una administración eficiente, siendo plata una herramienta óptima para la comunidad profesional de agricultores y con una usabilidad cercana al agricultor. Primeramente, se presentan trabajos previos relacionados con la captura de datos procedentes de cultivo y funcionamiento de riego a través del procesado de vídeo realizado con drones de vuelo autónomo. Seguidamente, se presentan los dispositivos presentes en la red inalámbrica de sensores orientada a captura de datos de los sensores terrestres y actuadores en sistemas de riego telegestionados de ultra bajo consumo energético. Por esto, nuestro trabajo se centra en redes de comunicaciones de banda estrecha, muy adecuadas para el uso en el medio rural. Nuestro sistema permite mantener un dispositivo comunicado y capaz de maniobrar las válvulas de hasta una extensión de 16 hectáreas con una pila comercial de 9 voltios toda una campaña de riego, sin necesidad de placas solares. Por último, toda la información e interoperabilidad de los apartados anteriores necesitan una gestión integral en un único sistema amigable con el usuario. En este punto presentamos un servidor con un motor de reglas de negocio y machine learning con autoaprendizaje capaz de generar decisiones para los controladores de riego, datos sensoriales de parcela o ambientales. Esta información es capaz de publicarse entre grupos sociales de usuarios e intercambiar métodos de trabajo y consignas. Todos los desarrollos y propuestas han sido precedidos de estudios de consumos energéticos en todos los dispositivos incluidos en el sistema. Además, se ha realizado un estudio en campo de las redes inalámbricas de sensores desplegadas en el medio rural bajo condiciones altamente problemáticas para comprobar el correcto funcionamiento del sistema entero.
[CAT] Existeixen gran quantitat de treballs relacionats amb l'automatització de processos en agricultura. Amb la revolució la Internet de les coses (de l'anglès Internet of Things o IoT) estan apareixent al mercat multitud de dispositius capaços d'interconnectar sensors. Més enfocat a l'agricultura intensiva, s'estan comercialitzant productes IoT que, tot i que els seus desenvolupadors asseguren que són capaços d'automatitzar les tasques en els cultius, veiem que no és així. Molts productes tecnològics desenvolupats per a utilitzar-los a l'agricultura de precisió, com són els programadors de reg tele gestionats, funcionen de forma independent amb altres tecnologies usades en l'agricultura. En aquests moments i amb l'avanç tecnològic actual, existeix la possibilitat d'aplicar unes rutines de reg adequades amb les necessitats reals del cultiu en terra, combinat amb la mesura de les necessitats de cultiu preses via satèl·lit o mitjançant vehicles aeris no tripulats o dron des de l'aire, adaptant les variables de forma automàtica en una única plataforma de gestió. Si el patró de producció de la meva explotació funciona bé, la PLAtaforma TEcnològica Multimedia (PLATEM) permetrà compartir l'estratègia seguida per tal que socis cooperativistes o persones que estiguin registrats en la xarxa social, puguen vore-la i veure els continguts publicats en ella sobre sistemes de control agrícoles. Aquesta tesi es centra en la investigació, disseny i desenvolupament de noves tecnologies per a integrar tots els sistemes presents en un sistema automàtics, considerant, des de la monitorització de paràmetres, fins al processat i pressa de decisions per a una administració eficient, sent PLATEM una ferramenta òptima per a la comunitat professional d'agricultors i amb una usabilitat propera a l'agricultor. Primerament, es presenten treballs previs relacionats amb la captura de dades procedents de cultiu i funcionament de reg a través del processat de vídeo realitzat amb drons de vol autònom. Seguidament, es presenten els dispositius presents en la xarxa sense fils de sensors orientada a captura de dades terrestres i els actuadors utilitzats per al reg tele-gestionats d'ultra baix consum energètic. Per això, el nostre treball se centra en xarxes de comunicacions de banda estreta, molt adequades per a l'ús en el medi rural. El nostre sistema permet mantenir un dispositiu comunicat i capaç de controlar les vàlvules en terrenys extensió de 16 hectàrees amb una pila comercial de 9 volts durant tota una campanya de reg, sense necessitat de plaques solars. Finalment, tota la informació i interoperabilitat dels dispositius que integren la xarxa necessiten una gestió integral en un únic sistema amigable amb l'usuari. En aquest punt presentem un servidor amb un motor de regles de negoci que aplica machine learning amb autoaprenentatge capaç de generar decisions per als controladors de reg, tenint en compte les dades dels sensors de parcel·la i ambientals. Aquesta informació és capaç de publicar-se entre grups socials d'usuaris i intercanviar mètodes de treball i consignes. Tots els desenvolupaments i propostes han estat combinats amb estudis de consums energètics. A més, s'ha realitzat un estudi en camp de les xarxes sense fils de sensors desplegades en el medi rural sota condicions altament problemàtiques per a comprovar el correcte funcionament del sistema sencer.
[EN] There are many works related to the automation of processes in agriculture. With the revolution of the Internet of Things (IoT), many devices capable of interconnecting sensors are appearing on the market. The focus is on intensive agriculture in a market where designers and marketers of IoT products present designs for the automation of crop production, claiming systematic achievements that ar not always compatible with agricultural reality. Many technological products, such as remote or WiFi management of irrigation programmers, focused on precision agriculture, are independent systems with no connection to other agricultural technologies. At this time and with the current technological advance, it must be integrated irrigation schedules in response to the real time needs of crop nutrition determining cultivation needs are transmitted via satellite or drone, in a platform will automatically integrate intelligent irrigation systems on the plot of land in relation to thermal analysis and crop vigor. If the production patterns of a farm are promising, PLAtaforma TEcnologica Multimedia (PLATEM) will allow disseminate a strategy followed to cooperative partners or people who are registered in the social network can see it and see the contents published in it on agricultural control systems. This thesis will attempt to solve the above-mentioned issues: the integration from start to finish of data capture and open data decisions for a community of professional farmers. Firtsly, we will review the literature on data harvesting of irrigation decisions for cultivation through computer-processed videos recorded by drones with autonomous flight mapping. Next, the devices present in a Wireless Sensor Network (WSN) are presented aimed at capturing terrestrial sensory data connected to tele-managed irrigation systems with ultra-low energy consumption. Hence, the focus of this work is firmly set on narrowband communication networks that are very suitable for use in rural areas. Our system maintains a communicated device capable of maneuvering valves within an area of 16 hectares with a commercial 9-volt battery throughout an irrigation campaign, with no need for solar panels. Finally, all the information and interoperability described in the previous sections will need integral management. At this point, we present a server with a business rules engine and machine learning with (self-learning) decision trees capable of generating decisions for irrigation controllers. The basic layer consists of the data processing of data mining models. The second layer consists of model training with historical data and the third layer applies to machine learning that generates the best results for guidance on recommendations. This information can be published and shared on social media between groups of users for the exchange of working methods and opinions regarding crops, cultivation strategies and demonstration plots. All of the proposed developments and proposals have been grounded in systematic energy consumption studies of all devices in the intelligent irrigation systems. In addition, a field study is conducted of the WSN deployed in rural areas under highly problematic conditions to determine the correct functioning of the entire system.
Cambra Baseca, C. (2019). PLAtaforma TEcnológica Multimedia para la Agricultura de Precisión (PLATEM Precision Agriculture) [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/135820
TESIS

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44

Rocha, Humberto Emanuel Francisco. "Autonomous vehicle/robotic platform for smart and precision agriculture inside greenhouses." Master's thesis, 2022. https://hdl.handle.net/10216/140717.

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45

Chung, Yao-Nien, and 鍾燿年. "Development and Application of Smart Agriculture: The Case of Strawberry Industry." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/f25wh2.

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碩士
國立臺灣大學
生物科技管理碩士在職學位學程
107
In the face of extreme weather, aging agricultural manpower, food safety and other challenges, global agriculture has applied intelligent agricultural-related technologies such as ict, the Internet of Things (IoT) and big data (Big Data), and grasped more accurately key data through sensors. Those will make more effective and comprehensive maintenance of food security, food safety and ecological safety. Strawberry is one of the important small berries produced in temperate regions. As Taiwan is located in the subtropical zone, climate change is great, and the seedling raising period coincides with typhoon season, greenhouse seedling raising can reduce the risk of seedling loss caused by typhoon, while the rainy and humid climate during the cultivation period makes the fruit rotten easily, and the spread of diseases and insect pests is rapid, which makes the control difficult, thus affecting the quality and yield of strawberries. From the strawberry chain model developed by the research object in this study, Taiwan''s industrial trends such as electronic technology contract, agricultural technology research and development are very suitable for the development of smart agriculture. Therefore, if the cultivation of strawberries in greenhouses and smart agricultural systems, in addition to protecting crops, can also provide tourists with a good strawberry garden harvesting environment, improve the situation of open-air cultivation of strawberry garden that cannot provide tourists to pick fruits and the fruits are easily damaged in rainy days. It is more hopeful to produce summer strawberries to supplement the current strawberry industry, further so that the strawberry industry system is more perfect. In the future, there should be an opportunity for the whole factory to export strawberry planting model in this smart greenhouse to other areas and create greater output value.

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Chan, Tzu-Kuan, and 詹子寬. "LED Lighting Control for Smart Farms : A Simple Application of Precision Agriculture." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/2ba366.

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碩士
國立中央大學
通訊工程學系在職專班
107
With the popularity of network equipment, making good use of the Internet of Things (IoT) to connect all devices and data collection on Precision agriculture could be more efficiency, quality improvement and cost reduction. Light is an important factor in plant growth because it is necessary for photosynthesis This thesis designed and developed the "Cloud LED Plant Lighting Control Method" through plant farms scenario, and proposed a cloud computing algorithm. According to the plant growth time course, the required wavelength for photosynthesis was independently selected, brightness was automatically adjusted and the cloud could also integrate and complement the ambient light to reduce the power consumption of the lighting equipment. The design of "Cloud LED Lighting Power Conditioning System" in this study could be divided into three subsystem architectures: environmental monitoring terminal, power distribution terminal and cloud integration terminal. The technology includes the sensing device detection technology and the power distribution unit (PDU) control technology, cloud man-machine graphical operation interface compilation, ambient light complementary technology, digital dimming technology, etc. Therefore, combining with the Internet of Things technology for the intelligent farm cloud LED lighting control method could not only replace the traditional manpower management, but also monitor the power information and control the lighting through the cloud integration interface, and could perform the instant dimming according to the conditions of the ambient light source. In addition to the environment of sustained plant growth, it could reduce power waste as well. By the research results of this thesis, it was used as a lighting infrastructure system for the development of precision agriculture, which not only reduced the dependence of lighting equipment on energy, but also directly reduced the cost of electricity for farmers.

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Yang, SungJu, and 楊松儒. "Design and Research of Smart Agriculture Cloud Systems Base On Serverless Operation." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/pw3a77.

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碩士
國立中央大學
通訊工程學系在職專班
107
Recently, the realization of smart agriculture, whether it is data analyzing, or image uploading to the cloud after drone tracking, or even the implementation of agricultural related applications or automation, ultimately are all utilizing cloud services. But the high cost of cloud implementation is not affordable by most enterprises and farmers. Even if some existing cloud services are available, such as the sensor module suppliers, the service is still constrained by the cloud system feature limitations and lack of flexibility. This paper proposes a cloud architecture with serverless as the core development, which can effectively reduce the cost of enterprises and farmers deploying smart agriculture cloud systems to replace the existing traditional server architecture services. The lower cost of hardware and software implementation also reduces the difficulty of cloud implementation and the subsequent maintenance cost. In the meantime it also improves the flexibility and usability of the system significantly. After the deployment and the cost reduction of its use, the experimental result of the LoRa node agricultural sensor does help improving farmer’s crop productivity. This model is not limited to agricultural applications, but it can potentially be applied to other areas, such as: software applications, interactive robots, etc., to improve business performance and productivity.

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lombardo, stefania. "Studies on the adoption of digitalization and high technology for precision agriculture." Doctoral thesis, 2020. http://hdl.handle.net/2158/1212002.

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The study investigates which are the effective approaches for the introduction in the use of new technologies in sustainable precision agriculture and what the necessary networks are for effective technology adoption. Lo studio indaga quali siano gli approcci proficui per l’introduzione nell’uso delle nuove tecnologie in agricoltura di precisione sostenibile e quali siano le reti necessarie perché l’adozione della tecnologia sia effettiva

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Huang, Jen-En, and 黃振恩. "The Design and Implementation of Agriculture Blockchain Platform with IoT Based Smart Contracts." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/4838cu.

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Buhl, Martin Thomas. "Agriculture In change: evaluation of factors influencing the adoption of smart farming technologies in Portugal." Master's thesis, 2021. http://hdl.handle.net/10362/132387.

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Abstract:

Recent developments in technology, such as Smart Farming Technologies (“SFT”),have the potential of revolutionizing agriculture .However, the level of adoption falls short of expectations, implying the importance of understanding the drivers of and barriers to technology adoption. Based on interviews with sector experts and field survey data, this paper analyses factors that may condition the adoption of SFT in Portugal. The logistic regression shows the importance of cost of investment, trialability of the technology, the awareness of available training programs and external financing, as well as the age and education of farmers for the adoption of SFT.

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Dissertations / Theses on the topic 'Smart agriculture'

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