To see the other types of publications on this topic, follow the link: Precision farming Agricultural engineering.
Journal articles on the topic 'Precision farming Agricultural engineering'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Precision farming Agricultural engineering.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Fahad, Muhammad, Tariq Javid, Hira Beenish, Adnan Ahmed Siddiqui, and Ghufran Ahmed. "Extending ONTAgri with Service-Oriented Architecture towards Precision Farming Application." Sustainability 13, no. 17 (August 31, 2021): 9801. http://dx.doi.org/10.3390/su13179801.
Full textAbstract:
The computer science perspective of ontology refers to ontology as a technology, however, with a different perspective in terms of interrogations and concentrations to construct engineering models of reality. Agriculture-centered architectures are among rich sources of knowledge that are developed, preserved, and released for farmers and agro professionals. Many researchers have developed different variants of existing ontology-based information systems. These systems are primarily picked agriculture-related ontological strategies based on activities such as crops, weeds, implantation, irrigation, and planting, to name a few. By considering the limitations on agricultural resources in the ONTAgri scenario, in this paper, an extension of ontology is proposed. The extended ONTAgri is a service-oriented architecture that connects precision farming with both local and global decision-making methods. These decision-making methods are connected with the Internet of Things systems in parallel for the input processing of system ontology. The proposed architecture fulfills the requirements of Agriculture 4.0. The significance of the proposed approach aiming to solve a multitude of agricultural problems being faced by the farmers is successfully demonstrated through SPARQL queries.
2
Perz, Rafal, and Kacper Wronowski. "UAV application for precision agriculture." Aircraft Engineering and Aerospace Technology 91, no. 2 (February 4, 2019): 257–63. http://dx.doi.org/10.1108/aeat-01-2018-0056.
Full textAbstract:
Purpose The purpose of this study is to show the potentials of a cost-effective unmanned aerial vehicles (UAV) system for agriculture industry. The current population growth rate is so vast that farming industry must be highly efficient and optimized. As a response for high quality food demands, the new branch of the agriculture industry has been formed – the precision agriculture. It supports farming process with sensors, automation and innovative technologies. The UAV advantages over regular aviation are withering. Not only they can fly at lower altitude and are more precise but also offer same high quality and are much cheaper. Design/methodology/approach The main objective of this project was to implement an exemplary cost-effective UAV system with electronic camera stabilizer for gaining useful data for agriculture. The system was based on small, unmanned flying wing able to perform fully autonomous missions, a commercially available camera and an own-design camera stabilizer. The research plan was to integrate the platform and run numerous experimental flights over farms, fields and woods collecting aerial pictures. All the missions have been planned to serve for local farming and forest industries and cooperated with local business authorities. Findings In preliminary flight tests, the variety of geodetic, forest and agriculture data have been acquired, placed for post processing and applied for the farming processes. The results of the research were high quality orthophoto maps, 3D maps, digital surface models and images mosaics with normalized difference vegetation index. The end users were astonished with the high-quality results and claimed the high importance for their business. Originality/value The case study results proved that this kind of a small UAV system is exceptional to manage and optimize processes at innovative farms. So far only professional, high-cost UAV platforms or traditional airships have been applied for agriculture industry. This paper shows that even simple, commercially available equipment could be used for professional applications.
3
Zecha, C. W., J. Link, and W. Claupein. "Mobile sensor platforms: categorisation and research applications in precision farming." Journal of Sensors and Sensor Systems 2, no. 1 (May 14, 2013): 51–72. http://dx.doi.org/10.5194/jsss-2-51-2013.
Full textAbstract:
Abstract. The usage of mobile sensor platforms arose in research a few decades ago. Since the beginning of satellite sensing, measurement principles and analysing methods have become widely implemented for aerial and ground vehicles. Mainly in Europe, the United States and Australia, sensor platforms in precision farming are used for surveying, monitoring and scouting tasks. This review gives an overview of available sensor platforms used in recent agricultural and related research projects. A general categorisation tree for platforms is outlined in this work. Working in manual, automatic or autonomous ways, these ground platforms and unmanned aircraft systems (UAS) with an agricultural scope are presented with their sensor equipment and the possible architectural models. Thanks to advances in highly powerful electronics, smaller devices mounted on platforms have become economically feasible for many applications. Designed to work automatically or autonomously, they will be able to interact in intelligent swarms. Sensor platforms can fulfil the need for developing, testing and optimising new applications in precision farming like weed control or pest management. Furthermore, commercial suppliers of platform hardware used in sensing tasks are listed.
4
Polishchuk, Yurij Vladimirovich, Vladimir Leonidovich Astafyev, Alexey Ivanovich Derepaskin, Nikolay Vladimirovich Kostyuchenkov, Nikolay Vladimirovich Laptev, and Artem Pavlovich Komarov. "Impacts of Automatic and Parallel Driving Systems on the Productivity of Machine-Tractor Units in the Northern Region of the Republic of Kazachstan." Acta Technologica Agriculturae 24, no. 3 (August 10, 2021): 143–49. http://dx.doi.org/10.2478/ata-2021-0024.
Full textAbstract:
Abstract Precision farming systems are being intensively introduced into the agricultural production of the Republic of Kazakhstan. According to developers and dealers, precision farming can reduce the cost of fertilizers, seeds, PPA, fuel and lubricants by 20% on average. At the same time, the efficiency possibilities resulting from the utilization of precision farming systems under certain conditions have not been fully studied. The aim of this work was to assess the influence of parallel and automatic driving systems on the technical, operational and economic indicators of units for sowing, chemical processing, harvesting, and autumn deep tillage using comparative tests in the northern region of the Republic of Kazakhstan. For these purposes, comparative tests were conducted for a seeder for sowing wheat; self-propelled sprayer for chemical weeding of wheat and flax; combine harvester for harvesting wheat; and unit for deep, subsurface tillage in Northern Kazakhstan. The comparative tests determined the impacts of GPS navigation systems, automatic and parallel control systems, and seeding control systems on agricultural, energy, operational, technological and economic performance of units.
5
Loret, Niccolò, Antonio Affinito, and Giuliano Bonanomi. "Introducing Evja - "Rugged" Intelligent Support System for precision farming." ACTA IMEKO 9, no. 2 (June 30, 2020): 83. http://dx.doi.org/10.21014/acta_imeko.v9i2.795.
Full textAbstract:
<p>Precision agriculture is a farming system based on the combination of detailed observations, measuring and rapid-response to optimize energetic input to maximize crops production. Precision agriculture use decision support system (DSS) for optimize farm management. In this context, <em>EVJA Observe Prevent Improve</em> (or just EVJA) is an Intelligent Support System for precision agriculture. A vast set of data (i.e. temperature, relative humidity, deficit of vapour pressure, leaf wetness, solar radiation, carbon dioxide concentration, soil moisture etc.) is continuously collected, submitted to a local control unit, and processed through algorithms specifically developed for different crops. On the other hands, farmers can access EVJA from their pc and mobile devices, and monitor complex agronomic data analysis presented in a user-friendly interface.</p>In this article, we will show how EVJA works, and how its output can be used to assess the health state of plants through a specific set of functions. Moreover, we will show the methodology to develop useful predictive models based on this information.<p>Specifically, we will describe a predictive algorithms capable to predict the infection risks of downy mildew for baby leaves plantations and for Fusarium ear blight of wheat.</p>
6
Schreiner, Simon, Dubravko Culibrk, Michele Bandecchi, Wolfgang Gross, and Wolfgang Middelmann. "Soil monitoring for precision farming using hyperspectral remote sensing and soil sensors." at - Automatisierungstechnik 69, no. 4 (April 1, 2021): 325–35. http://dx.doi.org/10.1515/auto-2020-0042.
Full textAbstract:
Abstract This work describes an approach to calculate pedological parameter maps using hyperspectral remote sensing and soil sensors. These maps serve as information basis for automated and precise agricultural treatments by tractors and field robots. Soil samples are recorded by a handheld hyperspectral sensor and analyzed in the laboratory for pedological parameters. The transfer of the correlation between these two data sets to aerial hyperspectral images leads to 2D-parameter maps of the soil surface. Additionally, rod-like soil sensors provide local 3D-information of pedological parameters under the soil surface. The goal is to combine the area-covering 2D-parameter maps with the local 3D-information to extrapolate large-scale 3D-parameter maps using AI approaches.
7
Beloev, Ivan, Diyana Kinaneva, Georgi Georgiev, Georgi Hristov, and Plamen Zahariev. "Artificial Intelligence-Driven Autonomous Robot for Precision Agriculture." Acta Technologica Agriculturae 24, no. 1 (January 29, 2021): 48–54. http://dx.doi.org/10.2478/ata-2021-0008.
Full textAbstract:
Abstract In the recent years, robotic systems became more advanced and more accessible. This has led to their slow, but stable integration and use in different processes and applications, including in the agricultural domain. Nowadays, agricultural robots are developed with the aim to replace the human labour in the otherwise exhausting, time-consuming or dangerous activities. Agricultural robotic systems provide many advantages, which can differ based on the type of the robot and its sensors, actuators and communication systems. This paper presents the design, the construction process, the main characteristics and the evaluation of a prototype of a small-scale agricultural robot that can be used for some of the simplest activities in agricultural enterprises. The robot is designed as an end-user autonomous mobile system, which is capable of self-localization and can map or inspect a specific farming area. The decision-making capabilities of the robot are based on artificial intelligence (AI) algorithms, which allow it to perform specific actions in accordance to the situation and the surrounding environment. The presented prototype is in its early development and evaluation stages and the paper concludes with discussions on the possible further improvements of the platform.
8
Hossain, Md Selim, Md Habibur Rahman, Md Sazzadur Rahman, A. S. M. Sanwar Hosen, Changho Seo, and Gi Hwan Cho. "Intellectual Property Theft Protection in IoT Based Precision Agriculture Using SDN." Electronics 10, no. 16 (August 18, 2021): 1987. http://dx.doi.org/10.3390/electronics10161987.
Full textAbstract:
In this work, we examine the privacy and safety issues of Internet of Things (IoT)-based Precision Agriculture (PA), which could lead to the problem that industry is currently experiencing as a result of Intellectual Property Theft (IPT). Increasing IoT-based information flow in PA will make a system less secure if a proper security mechanism is not ensured. Shortly, IoT will transform everyday lives with its applications. Intellectual Property (IP) is another important concept of an intelligent farming system. If the IP of a wise farming system leaks, it damages all intellectual ideas like cultivation patterns, plant variety rights, and IoT generated information of IoT-based PA. Thus, we proposed an IoT enabled SDN gateway regulatory system that ensures control of a foreign device without having access to sensitive farm information. Most of the farm uses its devices without the use of its integrated management and memory unit. An SDN-based structure to solve IP theft in precision farming has been proposed. In our proposed concept, a control system integrates with the cloud server, which is called the control hub. This hub will carry out the overall PA monitoring system. By hiring the farm devices in the agricultural system, these devices must be tailored according to our systems. Therefore, our proposed PA is a management system for all controllable inputs. The overall goal is to increase the probability of profit and reduce the likelihood of IPT. It does not only give more information but also improves information securely by enhancing the overall performance of PA. Our proposed PA architecture has been measured based on the throughput, round trip time, jitter, packet error rate, and the cumulative distribution function. Our achieved results reduced around (1.66–6.46)% compared to the previous research. In the future, blockchain will be integrated with this proposed architecture for further implementation.
9
Poblete-Echeverría, Carlos, and Sigfredo Fuentes. "Editorial: Special Issue “Emerging Sensor Technology in Agriculture”." Sensors 20, no. 14 (July 9, 2020): 3827. http://dx.doi.org/10.3390/s20143827.
Full textAbstract:
Research and innovation activities in the area of sensor technology can accelerate the adoption of new and emerging digital tools in the agricultural sector by the implementation of precision farming practices such as remote sensing, operations, and real-time monitoring [...]
10
Fang, Li Gang, Zhao Bin Liu, Hong Li Li, Cai Dong Gu, and Min Li Dai. "Application of Wireless Sensor Network for M2M in Precision Fruits." Advanced Materials Research 267 (June 2011): 482–87. http://dx.doi.org/10.4028/www.scientific.net/amr.267.482.
Full textAbstract:
The study introduced foreign and domestic situation of wireless sensor network technology in precision agriculture in detail. Applications of wireless sensor network are universal in foreign precision agriculture, however in its beginning stage in domestic agriculture. The function of domestic system based on wireless sensor network is usually positioning measurement and processing of agriculture elements, which does not meet final requirement of precision agriculture. The study designed a universal wireless sensor network for M2M combined intelligent communication technology and big agriculture machinery. The key technologies of wireless sensor network for M2M include development plan of ISA SP100.11a, spectrum technology based on DSSS, network technology based on net routing and low power radio frequency design, which can meet the real-time character, reliability, robustness and low energy consumption requirement of wireless communication in precision fruits. Moreover, the study presented several typical applications in precision fruits (including farming machine, water-saving irrigation machine and picking machine). With development of precision fruits in breadth and depth, integration application of wireless sensor network would have a widen prospect in the future.
11
Wang, Linlin, Yubin Lan, Yali Zhang, Huihui Zhang, Muhammad Naveed Tahir, Shichao Ou, Xiaotao Liu, and Pengchao Chen. "Applications and Prospects of Agricultural Unmanned Aerial Vehicle Obstacle Avoidance Technology in China." Sensors 19, no. 3 (February 3, 2019): 642. http://dx.doi.org/10.3390/s19030642.
Full textAbstract:
With the steady progress of China’s agricultural modernization, the demand for agricultural machinery for production is widely growing. Agricultural unmanned aerial vehicles (UAVs) are becoming a new force in the field of precision agricultural aviation in China. In those agricultural areas where ground-based machinery have difficulties in executing farming operations, agricultural UAVs have shown obvious advantages. With the development of precision agricultural aviation technology, one of the inevitable trends is to realize autonomous identification of obstacles and real-time obstacle avoidance (OA) for agricultural UAVs. However, the complex farmland environment and changing obstacles both increase the complexity of OA research. The objective of this paper is to introduce the development of agricultural UAV OA technology in China. It classifies the farmland obstacles in two ways and puts forward the OA zones and related avoidance tactics, which helps to improve the safety of aviation operations. This paper presents a comparative analysis of domestic applications of agricultural UAV OA technology, features, hotspot and future research directions. The agricultural UAV OA technology of China is still at an early development stage and many barriers still need to be overcome.
12
Latif, Ghazanfar, Jaafar Alghazo, R. Maheswar, V. Vijayakumar, and Mohsin Butt. "Deep learning based intelligence cognitive vision drone for automatic plant diseases identification and spraying." Journal of Intelligent & Fuzzy Systems 39, no. 6 (December 4, 2020): 8103–14. http://dx.doi.org/10.3233/jifs-189132.
Full textAbstract:
The agriculture industry is of great importance in many countries and plays a considerable role in the national budget. Also, there is an increased interest in plantation and its effect on the environment. With vast areas suitable for farming, countries are always encouraging farmers through various programs to increase national farming production. However, the vast areas and large farms make it difficult for farmers and workers to continually monitor these broad areas to protect the plants from diseases and various weather conditions. A new concept dubbed Precision Farming has recently surfaced in which the latest technologies play an integral role in the farming process. In this paper, we propose a SMART Drone system equipped with high precision cameras, high computing power with proposed image processing methodologies, and connectivity for precision farming. The SMART system will automatically monitor vast farming areas with precision, identify infected plants, decide on the chemical and exact amount to spray. Besides, the system is connected to the cloud server for sending the images so that the cloud system can generate reports, including prediction on crop yield. The system is equipped with a user-friendly Human Computer Interface (HCI) for communication with the farm base. This multidrone system can process vast areas of farmland daily. The Image processing technique proposed in this paper is a modified ResNet architecture. The system is compared with deep CNN architecture and other machine learning based systems. The ResNet architecture achieves the highest average accuracy of 99.78% on a dataset consisting of 70,295 leaf images for 26 different diseases of 14 plants. The results obtained were compared with the CNN results applied in this paper and other similar techniques in previous literature. The comparisons indicate that the proposed ResNet architecture performs better compared to other similar techniques.
13
Migliorini, Paola, Paolo Bàrberi, Stéphane Bellon, Tommaso Gaifami, Vassilis D. Gkisakis, Alain Peeters, and Alexander Wezel. "Controversial topics in agroecology: A European perspective." International Journal of Agriculture and Natural Resources 47, no. 3 (December 2020): 159–73. http://dx.doi.org/10.7764/ijanr.v47i3.2265.
Full textAbstract:
Seven potential controversial topics in agroecology are presented and discussed from a European perspective comparing the position of Agroecology Europe (AEEU) obtained from an iterative, participatory approach with members and compared with published literature, including views from other parts of the world. The seven controversial topics as follows: i) use of agrochemicals; ii) small-scale and peasant farming versus larger farms; iii) technological innovations in agriculture and precision farming; iv) biotechnology and genetic engineering in agriculture; v) local and short food circuits; vi) social justice; vii) gender perspective. The analysis shows that there are diverse points of view related to geographical area and sociopolitical contexts. However, there are several convergences in the ambition to redesign farming and food systems, as a lever acting on several topics, and in considering agroecology with a holistic, participatory, multiactor approach for the needed transition.
14
Mao, Wenju, Zhijie Liu, Heng Liu, Fuzeng Yang, and Meirong Wang. "Research Progress on Synergistic Technologies of Agricultural Multi-Robots." Applied Sciences 11, no. 4 (February 5, 2021): 1448. http://dx.doi.org/10.3390/app11041448.
Full textAbstract:
Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.
15
Lee, Sung-An, and Byung-Geun Lee. "Accurate 3D Surface Reconstruction for Smart Farming Application with an Inexpensive Shape from Focus System." Journal of Sensors 2020 (February 19, 2020): 1–7. http://dx.doi.org/10.1155/2020/1859512.
Full textAbstract:
In precision agriculture, 3D vision systems are becoming increasingly important. By applying different optical 3D vision techniques, the acquired 3D data can provide information regarding the most important phenotype features in every agricultural scenario. However, most of these 3D vision systems are expensive, except some of the triangulation techniques. In this study, we focus on estimating accurate shapes using shape from focus (SFF), which is a triangulation technique. Typically, the SFF system incurs significant errors from images, including noise. As a solution to this problem, a simple low-pass filter such as the Gaussian filter has generally been used in most studies. However, when a low filter is applied, the noise is depressed but the signals are also blurred, which results in inaccuracies regarding the depth map. In this study, the noise is depressed independently without losing the original signals, and the edge components, which play important roles in finding a focused surface, are enhanced using the independent component analysis (ICA). The edge signals are amplified with a simple basis vector correction in the IC vector space. The experiments are implemented with simulated objects and real objects. The experimental results demonstrate that the obtained accuracy is comparable to that of existing methods.
16
Haseeb, Khalid, Ikram Ud Din, Ahmad Almogren, and Naveed Islam. "An Energy Efficient and Secure IoT-Based WSN Framework: An Application to Smart Agriculture." Sensors 20, no. 7 (April 7, 2020): 2081. http://dx.doi.org/10.3390/s20072081.
Full textAbstract:
Wireless sensor networks (WSNs) have demonstrated research and developmental interests in numerous fields, like communication, agriculture, industry, smart health, monitoring, and surveillance. In the area of agriculture production, IoT-based WSN has been used to observe the yields condition and automate agriculture precision using various sensors. These sensors are deployed in the agricultural environment to improve production yields through intelligent farming decisions and obtain information regarding crops, plants, temperature measurement, humidity, and irrigation systems. However, sensors have limited resources concerning processing, energy, transmitting, and memory capabilities that can negatively impact agriculture production. Besides efficiency, the protection and security of these IoT-based agricultural sensors are also important from malicious adversaries. In this article, we proposed an IoT-based WSN framework as an application to smart agriculture comprising different design levels. Firstly, agricultural sensors capture relevant data and determine a set of cluster heads based on multi-criteria decision function. Additionally, the strength of the signals on the transmission links is measured while using signal to noise ratio (SNR) to achieve consistent and efficient data transmissions. Secondly, security is provided for data transmission from agricultural sensors towards base stations (BS) while using the recurrence of the linear congruential generator. The simulated results proved that the proposed framework significantly enhanced the communication performance as an average of 13.5% in the network throughput, 38.5% in the packets drop ratio, 13.5% in the network latency, 16% in the energy consumption, and 26% in the routing overheads for smart agriculture, as compared to other solutions.
17
Krul, Sander, Christos Pantos, Mihai Frangulea, and João Valente. "Visual SLAM for Indoor Livestock and Farming Using a Small Drone with a Monocular Camera: A Feasibility Study." Drones 5, no. 2 (May 19, 2021): 41. http://dx.doi.org/10.3390/drones5020041.
Full textAbstract:
Real-time data collection and decision making with drones will play an important role in precision livestock and farming. Drones are already being used in precision agriculture. Nevertheless, this is not the case for indoor livestock and farming environments due to several challenges and constraints. These indoor environments are limited in physical space and there is the localization problem, due to GPS unavailability. Therefore, this work aims to give a step toward the usage of drones for indoor farming and livestock management. To investigate on the drone positioning in these workspaces, two visual simultaneous localization and mapping (VSLAM)—LSD-SLAM and ORB-SLAM—algorithms were compared using a monocular camera onboard a small drone. Several experiments were carried out in a greenhouse and a dairy farm barn with the absolute trajectory and the relative pose error being analyzed. It was found that the approach that suits best these workspaces is ORB-SLAM. This algorithm was tested by performing waypoint navigation and generating maps from the clustered areas. It was shown that aerial VSLAM could be achieved within these workspaces and that plant and cattle monitoring could benefit from using affordable and off-the-shelf drone technology.
18
Ram, C. Ramasamy Sankar, S. Ravimaran, R. Santhana Krishnan, E. Golden Julie, Y. Harold Robinson, Raghvendra Kumar, Le Hoang Son, Pham Huy Thong, Nguyen Quang Thanh, and Mahmoud Ismail. "Internet of Green Things with autonomous wireless wheel robots against green houses and farms." International Journal of Distributed Sensor Networks 16, no. 6 (June 2020): 155014772092347. http://dx.doi.org/10.1177/1550147720923477.
Full textAbstract:
Nowadays, smart farming involves the integration of advanced technologies that incorporate low-cost robots to meet the required knowledge and maintain the health of plants in farming. Technologies like precision agriculture are also used to optimize resources based on the field condition. Internet of Green Things is also one of the technologies to integrate and share the information between people and healthy farm things. Internet of Green Things gives the information like soil moisture, temperature, humidity, and nutrient level by means of respective sensors. Monitoring and information gathering in green houses with the help of robots is a tedious and expensive process. In this connection, information is shared among low-cost robots encouraging data availability of the current state of a plant with other robots. This will emphasize the monitoring of green houses in a well-organized way. In this article, a Flask-based framework through Raspberry Pi is proposed for interoperability among the low-cost ESP8266 robots. Data gathering is performed by smart robots that are accessible through Message Queuing Telemetry Transport subscribes by means of Representational State Transfer Application Programming Interface. A cloud-like database server is provided to stock up the data. The integration of robotics with Internet of Green Things gains more advantage in gathering about spatial information data that are connected with the irrigation. Visualization techniques and perspectives based on Internet of Green Things for precision agriculture in the field of farming are highlighted.
19
Dalezios, Nicolas R., Nicholas Dercas, Nicos V. Spyropoulos, and Emmanouil Psomiadis. "Remotely Sensed Methodologies for Crop Water Availability and Requirements in Precision Farming of Vulnerable Agriculture." Water Resources Management 33, no. 4 (January 4, 2019): 1499–519. http://dx.doi.org/10.1007/s11269-018-2161-8.
Full text
20
Ardiansah, Irfan, Nurpilihan Bafdal, Edy Suryadi, and Awang Bono. "Greenhouse Monitoring and Automation Using Arduino: a Review on Precision Farming and Internet of Things (IoT)." International Journal on Advanced Science, Engineering and Information Technology 10, no. 2 (April 20, 2020): 703. http://dx.doi.org/10.18517/ijaseit.10.2.10249.
Full text
21
Fathallah, Karim, Mohamed Abid, and Nejib Ben Hadj-Alouane. "Enhancing Energy Saving in Smart Farming through Aggregation and Partition Aware IoT Routing Protocol." Sensors 20, no. 10 (May 12, 2020): 2760. http://dx.doi.org/10.3390/s20102760.
Full textAbstract:
Internet of things (IoT) for precision agriculture or Smart Farming (SF) is an emerging area of application. It consists essentially of deploying wireless sensor networks (WSNs), composed of IP-enabled sensor nodes, in a partitioned farmland area. When the surface, diversity, and complexity of the farm increases, the number of sensing nodes increases, generating heavy exchange of data and messages, and thus leading to network congestion, radio interference, and high energy consumption. In this work, we propose a novel routing algorithm extending the well known IPv6 Routing Protocol for Low power and Lossy Networks (RPL), the standard routing protocol used for IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). It is referred to as the Partition Aware-RPL (PA-RPL) and improves the performance of the standard RPL. In contrast to RPL, the proposed technique builds a routing topology enabling efficient in-network data aggregation, hence dramatically reducing data traffic through the network. Performance analysis of a typical/realistic precision agriculture case, considering the potato pest prevention from the well-known late blight disease, shows that PA-RPL improves energy saving up to 40 % compared to standard RPL.
22
Salam, Abdu, Qaisar Javaid, and Masood Ahmad. "Bio-inspired cluster–based optimal target identification using multiple unmanned aerial vehicles in smart precision agriculture." International Journal of Distributed Sensor Networks 17, no. 7 (July 2021): 155014772110340. http://dx.doi.org/10.1177/15501477211034071.
Full textAbstract:
Farming is the major profession in several republics for centuries. However, due to the immigration of individuals from rural to urban, there is prevention in farming. The use of modern technology in the precision agriculture field increases productivity and also improves the exports of a country. The productivity may suffer due to different environmental factors, diseases and insects attacks on the crops, especially tomatoes. The target area (i.e. the affected crops area due to environmental factors) identification and delivery of timely information about diseases in the crops to the ground station are mandatory to make the precautionary measurements. In flying sensor networks, the localization and clustering of multiple unmanned aerial vehicles for target areas identification is a challenging task due to energy constraints, communication range, frequent change in topology, link expiration and high mobility. In this article, we proposed the localization and clustering of multiple unmanned aerial vehicles for the identification of affected target areas in the tomato crop field. The localization of unmanned aerial vehicles depends on the weights of environmental factors, that is, relative humidity, soil moisture, temperature, light intensity, NPK (nitrogen (n), phosphorus (p) and potassium (k)) and power of hydrogen (pH). A honey bee optimization approach is used for the localization and formation of multiple unmanned aerial vehicles’ cluster to accurately identify the target areas. The performance of our bio-inspired approach is compared in terms of communication overhead, packet delivery ratio, mean end-to-end delay and energy consumption with the existing swarm intelligence–based schemes and validated via a simulation. The simulation result shows that the bio-inspired approach performs better among the selected approaches.
23
Lozoya, Camilo, Antonio Favela-Contreras, Alberto Aguilar-Gonzalez, L. C. Félix-Herrán, and Luis Orona. "Energy-Efficient Wireless Communication Strategy for Precision Agriculture Irrigation Control." Sensors 21, no. 16 (August 18, 2021): 5541. http://dx.doi.org/10.3390/s21165541.
Full textAbstract:
In smart farming, precision agriculture irrigation is essential to reduce water consumption and produce higher crop yields. Closed-loop irrigation based on soil moisture measurements has demonstrated the capability to achieve a considerable amount of water savings while growing healthy crops. Automated irrigation systems are typically implemented over wireless sensor networks, where the sensing devices are battery-powered, and thus they have to manage energy constraints by implementing efficient communication schemas. Self-triggered control is an aperiodic sampling strategy capable of reducing the number of networked messages compared to traditional periodical sampling. In this paper, we propose an energy-efficient communication strategy for closed-loop control irrigation, implemented over a wireless sensor network, where event-driven soil moisture measurements are conducted by the sensing devices only when needed. Thereby, the self-triggered algorithm estimates the occurrence of the next sampling period based on the process dynamics. The proposed strategy was evaluated in a pecan crop field and compared with periodical sampling implementations. The experimental results show that the proposed adaptive sampling rate technique decreased the number of communication messages more than 85% and reduced power consumption up to 20%, while still accomplishing the system control objectives in terms of the irrigation efficiency and water consumption.
24
Řezník, Tomáš, Lukáš Herman, Martina Klocová, Filip Leitner, Tomáš Pavelka, Šimon Leitgeb, Kateřina Trojanová, et al. "Towards the Development and Verification of a 3D-Based Advanced Optimized Farm Machinery Trajectory Algorithm." Sensors 21, no. 9 (April 23, 2021): 2980. http://dx.doi.org/10.3390/s21092980.
Full textAbstract:
Efforts related to minimizing the environmental burden caused by agricultural activities and increasing economic efficiency are key contemporary drivers in the precision agriculture domain. Controlled Traffic Farming (CTF) techniques are being applied against soil compaction creation, using the on-line optimization of trajectory planning for soil-sensitive field operations. The research presented in this paper aims at a proof-of-concept solution with respect to optimizing farm machinery trajectories in order to minimize the environmental burden and increase economic efficiency. As such, it further advances existing CTF solutions by including (1) efficient plot divisions in 3D, (2) the optimization of entry and exit points of both plot and plot segments, (3) the employment of more machines in parallel and (4) obstacles in a farm machinery trajectory. The developed algorithm is expressed in terms of unified modeling language (UML) activity diagrams as well as pseudo-code. Results were visualized in 2D and 3D to demonstrate terrain impact. Verifications were conducted at a fully operational commercial farm (Rostěnice, the Czech Republic) against second-by-second sensor measurements of real farm machinery trajectories.
25
Yazdinejad, Abbas, Behrouz Zolfaghari, Amin Azmoodeh, Ali Dehghantanha, Hadis Karimipour, Evan Fraser, Arthur G. Green, Conor Russell, and Emily Duncan. "A Review on Security of Smart Farming and Precision Agriculture: Security Aspects, Attacks, Threats and Countermeasures." Applied Sciences 11, no. 16 (August 16, 2021): 7518. http://dx.doi.org/10.3390/app11167518.
Full textAbstract:
In recent years, Smart Farming (SF) and Precision Agriculture (PA) have attracted attention from both the agriculture industry as well as the research community. Altogether, SF and PA aim to help farmers use inputs (such as fertilizers and pesticides) more efficiently through using Internet of Things (IoT) devices, but in doing so, they create new security threats that can defeat this purpose in the absence of adequate awareness and proper countermeasures. A survey on different security-related challenges is required to raise awareness and pave they way for further research in this area. In this paper, we first itemize the security aspects of SF and PA. Next, we review the types of cyber attacks that can violate each of these aspects. Accordingly, we present a taxonomy on cyber-threats to SF and PA on the basis of their relations to different stages of Cyber-Kill Chain (CKC). Among cyber-threats, we choose Advanced Persistent Threats (APTs) for further study. Finally, we studied related risk mitigation strategies and countermeasure, and developed a future road map for further study in this area. This paper’s main contribution is a categorization of security threats within the SF/PA areas and provide a taxonomy of security threats for SF environments so that we may detect the behavior of APT attacks and any other security threat in SF and PA environments.
26
Bucci, Giorgia, Deborah Bentivoglio, Matteo Belletti, and Adele Finco. "Measuring a farm's profitability after adopting precision agriculture technologies: A case study from Italy." ACTA IMEKO 9, no. 3 (September 30, 2020): 65. http://dx.doi.org/10.21014/acta_imeko.v9i3.799.
Full textAbstract:
<p class="Abstract">Precision agriculture (PA) offers the opportunity for farmers to improve both efficiency in managing resources and optimisation of process inputs, thus increasing their whole farm’s profitability. Despite these well-known benefits, the adoption of PA technologies (PATs) is still challenging due to socio-economic barriers and unique characteristics of the farms: cropping systems, technical developments, field sizes and farm scale. The economic aspect is undoubtedly one of the most important aspects to consider before adopting PATs. In most of the cases, farmers are reluctant to introduce precision farming systems since the costs and uncertainty about the profitability and advantages need to be addressed. This study aims to explore how PATs could affect the profitability of a representative Italian farm specialising in the production of cereals, making this a case study. In detail, an economic analysis was applied to determine the profitability of the farm, which showed that the adoption of PAT’s increased the yield of durum and soft wheat and significantly reduced the cost of mechanical operations and technical means. Therefore, the potential gains from the adoption of PATs challenges policymakers to design targeted interventions which could encourage their uptake. This paper is an extended version of the original contribution presented to the 2019 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) in Portici, Italy.</p>
27
Chebrolu, Nived, Philipp Lottes, Alexander Schaefer, Wera Winterhalter, Wolfram Burgard, and Cyrill Stachniss. "Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields." International Journal of Robotics Research 36, no. 10 (July 23, 2017): 1045–52. http://dx.doi.org/10.1177/0278364917720510.
Full textAbstract:
There is an increasing interest in agricultural robotics and precision farming. In such domains, relevant datasets are often hard to obtain, as dedicated fields need to be maintained and the timing of the data collection is critical. In this paper, we present a large-scale agricultural robot dataset for plant classification as well as localization and mapping that covers the relevant growth stages of plants for robotic intervention and weed control. We used a readily available agricultural field robot to record the dataset on a sugar beet farm near Bonn in Germany over a period of three months in the spring of 2016. On average, we recorded data three times per week, starting at the emergence of the plants and stopping at the state when the field was no longer accessible to the machinery without damaging the crops. The robot carried a four-channel multi-spectral camera and an RGB-D sensor to capture detailed information about the plantation. Multiple lidar and global positioning system sensors as well as wheel encoders provided measurements relevant to localization, navigation, and mapping. All sensors had been calibrated before the data acquisition campaign. In addition to the data recorded by the robot, we provide lidar data of the field recorded using a terrestrial laser scanner. We believe this dataset will help researchers to develop autonomous systems operating in agricultural field environments. The dataset can be downloaded from http://www.ipb.uni-bonn.de/data/sugarbeets2016/ .
28
Qureshi, Kashif Naseer, Muhammad Umair Bashir, Jaime Lloret, and Antonio Leon. "Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision." Journal of Sensors 2020 (January 31, 2020): 1–19. http://dx.doi.org/10.1155/2020/9040395.
Full textAbstract:
Wireless sensor networks (WSNs) are becoming one of the demanding platforms, where sensor nodes are sensing and monitoring the physical or environmental conditions and transmit the data to the base station via multihop routing. Agriculture sector also adopted these networks to promote innovations for environmental friendly farming methods, lower the management cost, and achieve scientific cultivation. Due to limited capabilities, the sensor nodes have suffered with energy issues and complex routing processes and lead to data transmission failure and delay in the sensor-based agriculture fields. Due to these limitations, the sensor nodes near the base station are always relaying on it and cause extra burden on base station or going into useless state. To address these issues, this study proposes a Gateway Clustering Energy-Efficient Centroid- (GCEEC-) based routing protocol where cluster head is selected from the centroid position and gateway nodes are selected from each cluster. Gateway node reduces the data load from cluster head nodes and forwards the data towards the base station. Simulation has performed to evaluate the proposed protocol with state-of-the-art protocols. The experimental results indicated the better performance of proposed protocol and provide more feasible WSN-based monitoring for temperature, humidity, and illumination in agriculture sector.
29
Plazas, Julian Eduardo, Sandro Bimonte, Gil De Sousa, and Juan Carlos Corrales. "Data-Centric UML Profile for Wireless Sensors." International Journal of Agricultural and Environmental Information Systems 10, no. 2 (April 2019): 21–48. http://dx.doi.org/10.4018/ijaeis.2019040102.
Full textAbstract:
Modelling WSN data behaviour is relevant since it would allow to evaluate the capacity of an application for supplying the user needs, moreover, it could enable a transparent integration with different data-centric information systems. Therefore, this article proposes a data-centric UML profile for the design of wireless sensor nodes from the user point-of-view capable of representing the gathered and delivered data of the node. This profile considers different characteristics and configurations of frequency, aggregation, persistence and quality at the level of the wireless sensor nodes. Furthermore, this article validates the UML profile through a computer-aided software engineering (CASE) tool implementation and one case study, centred on the data collected by a real WSN implementation for precision agriculture and smart farming.
30
Reitbauer, Eva, and Christoph Schmied. "Bridging GNSS Outages with IMU and Odometry: A Case Study for Agricultural Vehicles." Sensors 21, no. 13 (June 29, 2021): 4467. http://dx.doi.org/10.3390/s21134467.
Full textAbstract:
Nowadays, many precision farming applications rely on the use of GNSS-RTK. However, when it comes to autonomous agricultural vehicles, GNSS cannot be used as a stand-alone system for positioning. To ensure high availability and robustness of the positioning solution, GNSS-RTK must be fused with additional sensors. This paper presents a novel sensor fusion algorithm tailored to tracked agricultural vehicles. GNSS-RTK, an IMU and wheel speed sensors are fused in an error-state Kalman filter to estimate position and attitude of the vehicle. An odometry model for tracked vehicles is introduced which is used to propagate the filter state. By using both IMU and wheel speed sensors, specific motion characteristics of tracked vehicles such as slippage can be included in the dynamic model. The presented sensor fusion algorithm is tested at a composting site using a tracked compost turner. The sensor measurements are recorded using the Robot Operating System (ROS). To analyze the achievable accuracies for position and attitude of the vehicle, a precise reference trajectory is measured using two robotic total stations. The resulting trajectory of the error-state filter is then compared to the reference trajectory. To analyze how well the proposed error-state filter is suited to bridge GNSS outages, GNSS outages of 30 s are simulated in post-processing. During these outages, the vehicle’s state is propagated using the wheel speed sensors, IMU, and the dynamic model for tracked vehicles. The results show that after 30 s of GNSS outage, the estimated horizontal position of the vehicle still has a sub-decimetre accuracy.
31
Ansari, Mohammad Hasan Dad, Santosh Lavhale, Raviraj M. Kalunke, Prabhakar L. Srivastava, Vaibhav Pandit, Subodh Gade, Sanjay Yadav, et al. "Recent Advances in Plant Nanobionics and Nanobiosensors for Toxicology Applications." Current Nanoscience 16, no. 1 (January 22, 2020): 27–41. http://dx.doi.org/10.2174/1573413715666190409101305.
Full textAbstract:
Emerging applications in the field of nanotechnology are able to solve a gamut of problems surrounding the applications of agroecosystems and food technology. Nano Engineered Material (NEM) based nanosensors are important tools for monitoring plant signaling pathways and metabolism that are nondestructive, minimally invasive, and can provide real-time analysis of biotic and abiotic threats for better plant health. These sensors can measure chemical flux even at the singlemolecule level. Therefore, plant health could be monitored through nutrient management, disease assessment, plant hormones level, environmental pollution, etc. This review provides a comprehensive account of the current trends and practices for the proposed NEM related research and its (i) structural aspect, (ii) experimental design and performance as well as (iii) mechanisms of field application in agriculture and food system. This review also discusses the possibility of integration of data from NEM based nanosensors in current and emerging trends of precision agriculture, urban farming, and plant nanobionics to adopt a sustainable approach in agriculture.
32
Mazzetto, Fabrizio, Raimondo Gallo, and Pasqualina Sacco. "Reflections and Methodological Proposals to Treat the Concept of “Information Precision” in Smart Agriculture Practices." Sensors 20, no. 10 (May 17, 2020): 2847. http://dx.doi.org/10.3390/s20102847.
Full textAbstract:
Smart Agriculture (SA) is an evolution of Precision Farming (PF). It has technological basis very close to the paradigms of Industry 4.0 (Ind-4.0), so that it is also often referred to as Agriculture 4.0. After the proposal of a brief historical examination that provides a conceptual frame to the above terms, the common aspects of SA and Ind-4.0 are analyzed. These are primarily to be found in the cognitive approaches of Knowledge Management 4.0 (KM4.0, the actual theoretical basis of Ind-4.0), which underlines the need to use Integrated Information Systems (IIS) to manage all the activity areas of any production system. Based upon an infological approach, “raw data” becomes “information” only when useful to (or actually used in) a decision-making process. Thus, an IIS must be always designed according to such a view, and KM4.0 conditions the way of collecting and processing data on farms, together with the “information precision” by which the production system is managed. Such precision needs, on their turn, depend on the hierarchical level and the “Macrodomain of Prevailing Interest” (MPI) related to each decision, where the latter identifies a predominant viewpoint through which a system can be analyzed according to a prevailing purpose. Four main MPIs are here proposed: (1) physical and chemical, (2) biological and ecological, (3) productive and hierarchical, and (4) economic and social. In each MPI, the quality of the knowledge depends on the cognitive level and the maturity of the methodological approaches there achieved. The reliability of information tends to decrease from the first to the fourth MPI; lower the reliability, larger the tolerance margins that a measurement systems must ensure. Some practical examples are then discussed, taking into account some IIS-monitoring solutions of increasing complexity in relation to information integration needs and related data fusion approaches. The analysis concludes with the proposal of new operational indications for the verification and certification of the reliability of the information on the entire decision-making chain.
33
Cesco, Stefano, Youry Pii, Luigimaria Borruso, Guido Orzes, Paolo Lugli, Fabrizio Mazzetto, Giulio Genova, et al. "A Smart and Sustainable Future for Viticulture Is Rooted in Soil: How to Face Cu Toxicity." Applied Sciences 11, no. 3 (January 20, 2021): 907. http://dx.doi.org/10.3390/app11030907.
Full textAbstract:
In recent decades, agriculture has faced the fundamental challenge of needing to increase food production and quality in order to meet the requirements of a growing global population. Similarly, viticulture has also been undergoing change. Several countries are reducing their vineyard areas, and several others are increasing them. In addition, viticulture is moving towards higher altitudes and latitudes due to climate change. Furthermore, global warming is also exacerbating the incidence of fungal diseases in vineyards, forcing farmers to apply agrochemicals to preserve production yields and quality. The repeated application of copper (Cu)-based fungicides in conventional and organic farming has caused a stepwise accumulation of Cu in vineyard soils, posing environmental and toxicological threats. High Cu concentrations in soils can have multiple impacts on agricultural systems. In fact, it can (i) alter the chemical-physical properties of soils, thus compromising their fertility; (ii) induce toxicity phenomena in plants, producing detrimental effects on growth and productivity; and (iii) affect the microbial biodiversity of soils, thereby influencing some microbial-driven soil processes. However, several indirect (e.g., management of rhizosphere processes through intercropping and/or fertilization strategies) and direct (e.g., exploitation of vine resistant genotypes) strategies have been proposed to restrain Cu accumulation in soils. Furthermore, the application of precision and smart viticulture paradigms and their related technologies could allow a timely, localized and balanced distribution of agrochemicals to achieve the required goals. The present review highlights the necessity of applying multidisciplinary approaches to meet the requisites of sustainability demanded of modern viticulture.
34
Thapa, Rabin, and Nabin Bhusal. "Designing Rice for the 22nd Century: Towards a Rice with an Enhanced Productivity and Efficient Photosynthetic Pathway." Turkish Journal of Agriculture - Food Science and Technology 8, no. 12 (December 27, 2020): 2623–34. http://dx.doi.org/10.24925/turjaf.v8i12.2623-2634.3834.
Full textAbstract:
Rice (Oryza sativa L.) has been cultivated as an important cereal crop for more than 9,000 years and more than half of the world’s population depend on rice as it is their primary source of energy. Almost 30% of the current world cereal production is represented by the rice alone. It is estimated that the world’s population will reach 9.1 billion by 2050 i.e. 34 percent higher than today and for ensuring an ample amount of food and nutrition to such large population, global consumption of cereals will need to increase from 2.6 to 2.9 billion tonnes by 2027. On the other hand, the impacts of climate change in agriculture are expected to be negative, threatening the global food security. Besides, agriculture and global food security will be severely affected due to the COVID-19 pandemics as its after-effects are yet to be ascertained. The world needs an introduction of a new “Green revolution” in agriculture to increase crop production for food security and biofuel, because conventional breeding method have not brought much of gains not keeping its pace with the world population growth. Hence, the current study was done to review the various ongoing approaches and possible ways of designing a rice with enhanced productivity and photosynthetic capacity. One of the ways to increase yields, photosynthetic capacity accompanied by an increased Water Use Efficiency (WUE) and Nutrient Use Efficiency could be to introduce C4 traits into rice. Besides, genetic engineering using CRISPR-Cas9, molecular breeding, developing ideotype, heterosis breeding, developing apomictic rice, nitrogen fixing rice, use of nanotechnology as well as precision farming are the probable future approaches for designing a rice with high productivity. However, there are challenges and limitations in developing such rice and further research in this matter could help us get closer to developing the future rice.
35
Гаспарян, И. Н., А. Г. Левшин, И. Г. Голубев, С. В. Щиголев, and Ш. В. Гаспарян. "Technologies and machines for the production of potatoes." Kartofel` i ovoshi, no. 9 (September 7, 2021): 3–8. http://dx.doi.org/10.25630/pav.2021.65.12.001.
Full textAbstract:
В статье проанализирован мировой рынок с.-х. техники, ее особенности совершенствования за счет усложнения конструкций и активного внедрения технологий точного земледелия. Рассмотрены вопросы изменения российского парка сельхозмашин, который продолжительное время идет на спад по всем основным видам техники. Число тракторов в российском парке сократилось на 18,4%, комбайнов на 16,2%, в том числе картофелеуборочных машин. Сокращение имеющейся в отечественном парке сельхозтехники закономерно снижает обеспеченность сельхозмашинами в пересчете на 1000 га пахотной площади. Более детально рассмотрены применяемые механизированные технологии возделывания картофеля в РФ и необходимая для этого специальная техника, так как при выборе технологии необходимо учитывать всю систему машин от посадки до уборки. Дана характеристика основных распространенных в России механизированных технологий возделывания картофеля: традиционной, голландской, грядово-ленточной, гриммовской, гребневой. Представлена информация по технологическим процессам посадки и уборки, на которые приходится значительная часть эксплуатационных и трудовых затрат. Для реализации этих технологических процессов требуется использовать специальную технику, которая сильно разнится по производительности и особенностям применения в различных климатических условиях и объемах производства. В качестве примера использования комплекса такой техники охарактеризована система производства в крупнотоварном хозяйстве, ЗАО «Озеры» (Московская область). Потребность в технике для картофелеводства остается высокой и необходимо развивать отечественное машиностроение с учетом мировых достижений в этой области. The article analyzes the world market of agricultural machinery, its features of improvement due to the complication of designs and the active introduction of precision farming technologies. The issues of changing the Russian fleet of agricultural machinery are considered, which has been declining for a long time in all major types of equipment. The number of tractors in the Russian fleet decreased by 18.4%, combines by 16.2%, including potato harvesters. The reduction of agricultural machinery available in the domestic fleet naturally reduces the availability of agricultural machinery in terms of 1000 ha of arable land. The mechanized technologies of potato cultivation in the Russian Federation and the special equipment required for this are considered in more detail, since when choosing a technology, it is necessary to take into account the entire system of machines from planting to harvesting. The characteristics of the main mechanized technologies of potato cultivation common in Russia is given: traditional, Dutch, ridge-ribbon, Grimme, comb technologies. Information is provided on the technological processes of planting and harvesting, which account for a significant part of the operating and labor costs. To implement these technological processes, it is required to use special equipment, which varies greatly in performance and application characteristics in various climatic conditions and production volumes. As an example of the use of a complex of such equipment, the production system in a large-scale farm, CJSC Ozery (Moscow region), is described. The need for equipment for potato growing remains high and it is necessary to develop domestic mechanical engineering, taking into account the world achievements in this area.
36
Fanigliulo, Roberto, Francesca Antonucci, Simone Figorilli, Daniele Pochi, Federico Pallottino, Laura Fornaciari, Renato Grilli, and Corrado Costa. "Light Drone-Based Application to Assess Soil Tillage Quality Parameters." Sensors 20, no. 3 (January 28, 2020): 728. http://dx.doi.org/10.3390/s20030728.
Full textAbstract:
The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics, such as laser profile meters. The aim of the study was to compare traditional methods of soil roughness and cloddiness assessment (laser profile meter and manual sieving), with light drone RGB 3D imaging techniques for the evaluation of different tillage methods (ploughed, harrowed and grassed). Light drone application was able to replicate the results obtained by the traditional methods, introducing advantages in terms of time, repeatability and analysed surface while reducing the human error during the data collection on the one hand and allowing a labour-intensive field monitoring solution for digital farming on the other. Indeed, the profilometer positioning introduces errors and may lead to false reading due to limited data collection. Future work could be done in order to streamline the data processing operation and so to produce a practical application ready to use and stimulate the adoption of new evaluation indices of soil cloddiness, such as Entropy and the Angular Second Moment (ASM), which seem more suitable than the classic ones to achieved data referred to more extended surfaces.
37
Dombrowski, Olga, Harrie-Jan Hendricks Franssen, Cosimo Brogi, and Heye Reemt Bogena. "Performance of the ATMOS41 All-in-One Weather Station for Weather Monitoring." Sensors 21, no. 3 (January 22, 2021): 741. http://dx.doi.org/10.3390/s21030741.
Full textAbstract:
Affordable and accurate weather monitoring systems are essential in low-income and developing countries and, more recently, are needed in small-scale research such as precision agriculture and urban climate studies. A variety of low-cost solutions are available on the market, but the use of non-standard technologies raises concerns for data quality. Research-grade all-in-one weather stations could present a reliable, cost effective solution while being robust and easy to use. This study evaluates the performance of the commercially available ATMOS41 all-in-one weather station. Three stations were deployed next to a high-performance reference station over a three-month period. The ATMOS41 stations showed good performance compared to the reference, and close agreement among the three stations for most standard weather variables. However, measured atmospheric pressure showed uncertainties >0.6 hPa and solar radiation was underestimated by 3%, which could be corrected with a locally obtained linear regression function. Furthermore, precipitation measurements showed considerable variability, with observed differences of ±7.5% compared to the reference gauge, which suggests relatively high susceptibility to wind-induced errors. Overall, the station is well suited for private user applications such as farming, while the use in research should consider the limitations of the station, especially regarding precise precipitation measurements.
38
Hamrita, Takoi K., Jeffrey S. Durrence, and George Vellidis. "Precision farming practices." IEEE Industry Applications Magazine 15, no. 2 (March 2009): 34–42. http://dx.doi.org/10.1109/mias.2009.931816.
Full text
39
Mandal, Manas, Bappa Paramanik, Anamay Sarkar, and Debasis Mahata. "PRECISION FARMING IN FLORICULTURE." International Journal of Research -GRANTHAALAYAH 9, no. 1 (January 26, 2021): 75–77. http://dx.doi.org/10.29121/granthaalayah.v9.i1.2021.2871.
Full textAbstract:
Precision farming is a science base modern technology which provided management concept based on observation and response to intra-field variations. New technologies such as Global Positioning Systems (GPS), sensors, satellites or aerial images and Geographical Information Systems (GIS) are utilized to assess and analyse variations in agricultural and horticultural production. In this technology have two primary goals that are (i) optimum return (ii) preserving resource. Wireless Sensor Networks has crucial role to management of water resources, to assess the optimum point of harvesting, to estimate fertilizer requirements and to predict crop performance more accurately, disease and pest hazard also. Sensors use to precision farming technology in horticulture, which increasing productivity, decreasing production costs and minimizing the environmental impact of farming. Though precision farming has vital role in Agriculture and Horticulture sector but, no so popular due to high cost of technology and need high speed internet facility.
40
Finger, Robert, Scott M. Swinton, Nadja El Benni, and Achim Walter. "Precision Farming at the Nexus of Agricultural Production and the Environment." Annual Review of Resource Economics 11, no. 1 (October 5, 2019): 313–35. http://dx.doi.org/10.1146/annurev-resource-100518-093929.
Full textAbstract:
Precision farming enables agricultural management decisions to be tailored spatially and temporally. Site-specific sensing, sampling, and managing allow farmers to treat a field as a heterogeneous entity. Through targeted use of inputs, precision farming reduces waste, thereby cutting both private variable costs and the environmental costs such as those of agrichemical residuals. At present, large farms in developed countries are the main adopters of precision farming. But its potential environmental benefits can justify greater public and private sector incentives to encourage adoption, including in small-scale farming systems in developing countries. Technological developments and big data advances continue to make precision farming tools more connected, accurate, efficient, and widely applicable. Improvements in the technical infrastructure and the legal framework can expand access to precision farming and thereby its overall societal benefits.
41
Shelake, Priyanka Chandrakant. "Testing and Monitoring Agricultural Soil using Precision Farming." International Journal for Research in Applied Science and Engineering Technology 7, no. 7 (July 31, 2019): 418–20. http://dx.doi.org/10.22214/ijraset.2019.7063.
Full text
42
Mandal, Subrata. "Precision Farming for Small Agricultural Farm: Indian Scenario." American Journal of Experimental Agriculture 3, no. 1 (January 10, 2013): 200–217. http://dx.doi.org/10.9734/ajea/2013/2326.
Full text
43
Busse, M., A. Doernberg, R. Siebert, A. Kuntosch, W. Schwerdtner, B. König, and W. Bokelmann. "Innovation mechanisms in German precision farming." Precision Agriculture 15, no. 4 (November 29, 2013): 403–26. http://dx.doi.org/10.1007/s11119-013-9337-2.
Full text
44
Weis, Martin, Christoph Gutjahr, Victor Rueda Ayala, Roland Gerhards, Carina Ritter, and Florian Schölderle. "Precision farming for weed management: techniques." Gesunde Pflanzen 60, no. 4 (November 8, 2008): 171–81. http://dx.doi.org/10.1007/s10343-008-0195-1.
Full text
45
K, Shruthi, G. M. Hiremath, and Amrutha T. Joshi. "FINANCIAL FEASIBILITY OF PRECISION FARMING IN PADDY- A CASE STUDY." Current Agriculture Research Journal 5, no. 3 (December 13, 2017): 318–24. http://dx.doi.org/10.12944/carj.5.3.09.
Full textAbstract:
Precision farming is an emerging, highly promising technology that helps in dealing with the present agricultural challenges by proper and effective management of soil and crop variability with the use of information technology. In order to initiate precision farming in India through state agricultural universities, the precision farming project in selected field crops was implemented in University of Agricultural Sciences, Raichur, Karnataka. The objective of the study was to assess the financial feasibility of project implementation at farm level in paddy. Primary data was collected with the aid of a well-structured, pre tested schedule. Findings showed that the project of precision farming in paddy which was implemented by the University was economically viable and financially feasible. The cost incurred in cultivation of paddy by adopting precision farming practices was ` 75,825.35/ha and gross returns were ` 1,22,656.30/ha. Results of financial feasibility measures showed that the Net Present Value at 12 per cent discount rate, at the end of ten years was found to be positive, Benefit-Cost ratio was more than one and Internal Rate of Returns of the precision farming in paddy was more than discount rate (12 %). It was also revealed that payback period was 6.84 months and profitability index due to adoption of precision farming was found to be 8.83. Hence it was concluded that investment on precision farming in paddy at farm level was feasible to operate at farm level with the technical assistance from University. Considering the adoption strategy of precision farming and its benefits, there is a need to bring awareness among farming community by the joint effort of public and private sectors through the extension agencies, non-governmental organizations and state agricultural universities
46
Norton, Tomas, and Daniel Berckmans. "Engineering advances in Precision Livestock Farming." Biosystems Engineering 173 (September 2018): 1–3. http://dx.doi.org/10.1016/j.biosystemseng.2018.09.008.
Full text
47
Skvortsov, E. A., and A. S. Gusev. "Territorial Features of Application of Precision Farming Technologies." Economy of agricultural and processing enterprises, no. 9 (2020): 59–66. http://dx.doi.org/10.31442/0235-2494-2020-0-9-59-66.
Full textAbstract:
The article discusses the issues of territorial patterns in the implementation of precision farming technologies, which are insufficiently studied and constitute a significant scientific problem. The purpose of the study is to identify the territorial patterns of the introduction of precision farming technologies in conjunction with the indicators of agricultural development in the regions. The number of applied precision farming technologies was clarified, 37 regions took part in the study, 24 of them provided information on the application of these technologies. The results of correlation of regional development indicators (12 indicators in three blocks) and the amount of equipment with precision farming elements are presented. The greatest positive correlation is observed between the introduction of precision farming technologies and the agricultural production index at comparable prices (0.51) and the level of subsidies (0.37). The greatest negative correlation is observed between the introduction of these technologies and the change in the registered unemployment rate (-0.3). Based on the results obtained, it can be assumed that in regions with high values of agricultural production growth and subsidies, precision farming technologies will be most intensively introduced.
48
Balogh, Péter, Attila Bai, Ibolya Czibere, Imre Kovách, László Fodor, Ágnes Bujdos, Dénes Sulyok, Zoltán Gabnai, and Zoltán Birkner. "Economic and Social Barriers of Precision Farming in Hungary." Agronomy 11, no. 6 (May 29, 2021): 1112. http://dx.doi.org/10.3390/agronomy11061112.
Full textAbstract:
Precision farming may play an important role in agricultural innovation. The study focuses on the attitude of Hungarian farmers toward precision farming. Based on the relevant technical literature, we performed a nationally representative questionnaire survey of 594 farmers and deep interviews with experts and farmers (30 persons). As regards the questionnaire, the authors found that the management of the average farm size in Hungary has the highest willingness to innovate and the second highest level of education among the developed clusters. The survey shows undertrained farmers with large farms to be the second most open group, which may result in the partial application of precision farming techniques. One of the most unexpected results of the Precision Farmers’ cluster is that the positive socio-economic utility of precision farming is rated as extremely low. In-depth interviews prove that the use of precision technologies does not increase local social cohesion. Strong organisational isolation of precision farmers prevents the spread of innovation knowledge and precision farming amongst the farming community, and the challenges of competitiveness alone do not force farmers to apply precision farming. Our results may be useful for the establishment of agricultural strategy.
49
Takácsné György, Katalin. "Economic aspects of an agricultural innovation – precision crop production." Applied Studies in Agribusiness and Commerce 6, no. 1-2 (June 30, 2012): 51–57. http://dx.doi.org/10.19041/apstract/2012/1-2/6.
Full textAbstract:
Innovation in agriculture ensures the wide-spread use of the latest, up-to-date technology. Such new technology is precision farming in crop production, which serves as a validation of the criteria of environmental and economic sustainability. The economic applicability of precision crop production depends on several factors.Among them the following aspects must be emphasized: the size of the farm, the characteristics of the production structure, the current input-output prices and their tendencies, the investment needed for transitioning to precision technology and its capital source, the level of professional knowledge and the managerial attitudes of the farm. I have examined the economic relations between potential savings in chemicals on EU level. It has been found that after switching to precision farming, the active ingredient use for fertilizers can be reduced by 340 thousand tons at the same expected yield level in an optimistic scenario in the EU-27, while the savings in pesticide use can be 30 thousand tons (calculating with the current dose-level). If approximately 30% of the crop producing and mixed farms over 16 ESU adopt this new technology, this will diminish environmental loads by up to 10-35%. The majority of farms characterized by greater output and size can be based on their own equipment but it might as well be presumed that smaller farms can turn to precision farming not based on their own investment. They can buy the technical service from providers, they can establish producer cooperation, for example in the frame of machinery rings. At a certain farm size and farming intensity precision crop production is a real, environmentally friendly farming strategy, with the help of which the farm can reach earnings that cover at least the economic conditions of simple reproduction.
50
Wolf, Steven A., and Frederick H. Buttel. "The Political Economy of Precision Farming." American Journal of Agricultural Economics 78, no. 5 (December 1996): 1269–74. http://dx.doi.org/10.2307/1243505.
Full text