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Gill, Rana. "A Review on Various Techniques to Transform Traditional Farming to Precision Agriculture." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (2021): 131–35. http://dx.doi.org/10.17762/turcomat.v12i2.690.
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The agricultural sector is of great importance to fulfill food resources need of the country. Precision Agriculture (PA) with Internet of Things and Wireless Sensor Network is a transformation from traditional farming to smart farming. Wireless sensor networks and Internet of Things are considered as drivers to develop system which can change agriculture sector from manual to automatic. Advancement in the technology have pushed the growth of precision agriculture to very large extent despite of several challenges faced in this area. System for precision agriculture relies on hardware components mainly wireless sensors which act as a source for gathering of real time data. Depending upon the real time date retrieved by sensors automation in agriculture is done by adopting decision-based system. With Precision agriculture productivity is optimized by maintaining sustaniability as crop receives what is acutual requirement on the basis of new techniques and software platforms. This review article includes Inernet of Things (IoT), Wireless Sensors, Wireless communication and challenges faced in this area.
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Malik, Naila Nawaz, Wael Alosaimi, M. Irfan Uddin, Bader Alouffi, and Hashem Alyami. "Wireless Sensor Network Applications in Healthcare and Precision Agriculture." Journal of Healthcare Engineering 2020 (November 30, 2020): 1–9. http://dx.doi.org/10.1155/2020/8836613.
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A wireless sensor network is a large sensor hub with a confined power supply that performs limited calculations. Due to the degree of restricted correspondence and the large size of the sensor hub, packets sent through the sensor network are based primarily on multihop data transmission. Current wireless sensor networks are widely used in a range of applications, such as precision agriculture, healthcare, and smart cities. The network covers a wide domain and addresses multiple aspects in agriculture, such as soil moisture, temperature, and humidity. Therefore, issues of precision agriculture at the output of the network are analyzed using a star and mesh topology with TCP as the transmission protocol. The system is equipped with two sensors: Arduino DFRobot for soil moisture and DHT11 for relative temperature and humidity. The experiments are performed using the NS2 simulator, which provides an improved interface to analyze the results. The results showed that the proposed mechanism has good performance and output.
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Zheng, Bi Geng, and Heng Wang. "Application Research of Wireless Sensor Network in the Fine Production of Agriculture." Applied Mechanics and Materials 513-517 (February 2014): 3695–98. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3695.
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Wireless Sensor Network (WSN) technology has the potential to have impact on many aspects of Precision Agriculture (PA). However, current WSN applications in Precision Agriculture all adopt the traditional client/sever model, data are sent from the source to the destination, because of hugeous data, high concurrency and strong signal interference in Precision Agriculture and the extremely limited sensor network resources, such client/sever model hampers WSN applications in Precision Agriculture.[ This paper presents a mobile-based agent of wireless sensor network model MAPA, MAPA avoids the large agricultural intermediate data transmission through migrating the computing to the resource source, and consequently it prolongs the sensor network lifetime and promotes the WSN applications in Precision Agriculture.
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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.
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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.
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Prasad, Dr K. Raghavendra, Dorebabu C, Somashekara T, Parasurama H, and Mehaboob Basha. "Wireless Sensor Networks based Remote Monitoring System for Agriculture." International Journal for Research in Applied Science and Engineering Technology 11, no. 4 (2023): 4237–38. http://dx.doi.org/10.22214/ijraset.2023.51237.
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Abstract: The network covers a wide domain and addresses multiple aspects in agriculture, such as soil moisture, temperature, and humidity. Therefore, issues of precision agriculture at the output of the network are analyzed using wireless technology. The system is equipped with sensors for soil moisture and DHT11 for relative temperature and humidity. Current wireless sensor networks are widely used in a range of applications, such as precision agriculture, healthcare, and smart cities.
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A.Gowri Priya, A. Gowri Priya, and K. Kannan K.Kannan. "A Low Energy Consumption in Precision Agriculture Using Wireless Sensor Network." Indian Journal of Applied Research 4, no. 3 (2011): 134–35. http://dx.doi.org/10.15373/2249555x/mar2014/39.
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Abidin, Zainul, Raisul Falah, Raden Arief Setyawan, and Fitri Candra Wardana. "Wireless sensor network using nRF24L01+ for precision agriculture." Bulletin of Electrical Engineering and Informatics 14, no. 2 (2025): 1003–13. https://doi.org/10.11591/eei.v14i2.8481.
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Precision agriculture is a strategy for varying inputs and cultivation methods to suit varying soil conditions and agricultural crops. In order to optimize precision agriculture, wireless sensor network (WSN) is suitable to be integrated. In this research, network devices that communicate using nRF24L01+ based WSN was proposed. As a prototype, four sensor nodes were employed to measure the parameters of air temperature and humidity, soil moisture, and power supply voltage. While, a sink node serves to store measurement data locally. The data are sent to the sink node with a mesh network topology and saved in a comma-separated values (CSV) file and local database. Experimental results show that each sensor node can measure all parameters and successfully send data to the sink node every 1 minute without losing the data. The mesh topology can route data transfer automatically. Round trip time (RTT) of each sensor node depends on the distance from each node. Average power consumption of all sensor nodes in send mode is between 84 mW and 90 mW. Meanwhile, in sleep mode, the sensor nodes 1 and 2 consumed around 21-22 mW and the sensor nodes 3 and 4 consumed around 30 mW which are lower than the send mode.
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Zervopoulos, Alexandros, Athanasios Tsipis, Aikaterini Georgia Alvanou, et al. "Wireless Sensor Network Synchronization for Precision Agriculture Applications." Agriculture 10, no. 3 (2020): 89. http://dx.doi.org/10.3390/agriculture10030089.
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The advent of Internet of Things has propelled the agricultural domain through the integration of sensory devices, capable of monitoring and wirelessly propagating information to producers; thus, they employ Wireless Sensor Networks (WSNs). These WSNs allow real time monitoring, enabling intelligent decision-making to maximize yields and minimize cost. Designing and deploying a WSN is a challenging and multivariate task, dependent on the considered environment. For example, a need for network synchronization arises in such networks to correlate acquired measurements. This work focuses on the design and installation of a WSN that is capable of facilitating the sensing aspects of smart and precision agriculture applications. A system is designed and implemented to address specific design requirements that are brought about by the considered environment. A simple synchronization scheme is described to provide time-correlated measurements using the sink node’s clock as reference. The proposed system was installed on an olive grove to assess its effectiveness in providing a low-cost system, capable of acquiring synchronized measurements. The obtained results indicate the system’s overall effectiveness, revealing a small but expected difference in the acquired measurements’ time correlation, caused mostly by serial transmission delays, while yielding a plethora of relevant environmental conditions.
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Zhang, Bingtao, and Lingyan Meng. "Energy Efficiency Analysis of Wireless Sensor Networks in Precision Agriculture Economy." Scientific Programming 2021 (August 20, 2021): 1–7. http://dx.doi.org/10.1155/2021/8346708.
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Wireless sensor network (WSN) can play an important role during precision agriculture production to promote the growth of the agricultural economy. The application of WSN in agricultural production can achieve precision agriculture. WSN has the biggest challenge of energy efficiency. This paper proposes a model to efficiently utilize the energy of sensor nodes in precision agriculture production. The proposed model provides a comprehensive analysis of the precision agriculture. The model focuses on the characteristics of WSN and expands its application in precision agriculture. In addition, this paper also puts forward some technical prospects to provide a good reference for comprehensively and effectively improving the overall development level of precision agriculture. The paper analyzes the applicability and limitations of the existing sensor networks used for agricultural production technology. The ZigBee and Lora wireless protocols are utilized to have the best power consumption and communication in short distance and long distance. Our proposed model also suggests improvement measures for the shortcomings of existing WSN in the context of energy efficiency to provide an information platform for WSN to play a better role in agricultural production.
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S, Nifasath Piyar, and Dr S. Baulkani. "A Review of Wireless Sensor Networks in Agriculture." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (2022): 577–80. http://dx.doi.org/10.22214/ijraset.2022.47936.
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Abstract: Wireless sensor network (WSN) contains various sensor nodes with the capacity of sensing, computing, and wireless communications. WSN technology is used to control and monitor the environmental and soil parameter in agricultural field. WSN employ as a part of agriculture for few reasons like gives high interpretation, increase the production of the crop, lowpower consumption and gather distributed data. Efficient management of water assumes an important part in agriculture. Various agricultural parameters like soil moisture, atmospheric temperature and humidity etc. are monitored and controlled by Monitoring and Controlling Units. WSN have fascinated much attention in various research areas like health care monitoring, environment monitoring and structural health monitoring. Recently WSN is widely used to provide solution on precision agriculture to overcome various problems in the real-world (field).This paper reviews the monitoring of precision agriculture using wireless sensor network focuses on literature of the development of a wireless sensor network on agricultural environment to monitor environmental conditions and deduce the appropriate environmental and agriculture. Agriculture and farming is one of the industries which has recently started using WSN to increase the productivity and standardize the agricultural yield at affordable cost.
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Shafi, Uferah, Rafia Mumtaz, José García-Nieto, Syed Ali Hassan, Syed Ali Raza Zaidi, and Naveed Iqbal. "Precision Agriculture Techniques and Practices: From Considerations to Applications." Sensors 19, no. 17 (2019): 3796. http://dx.doi.org/10.3390/s19173796.
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Internet of Things (IoT)-based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers of automation in the agriculture domain. PA uses specific sensors and software to ensure that the crops receive exactly what they need to optimize productivity and sustainability. PA includes retrieving real data about the conditions of soil, crops and weather from the sensors deployed in the fields. High-resolution images of crops are obtained from satellite or air-borne platforms (manned or unmanned), which are further processed to extract information used to provide future decisions. In this paper, a review of near and remote sensor networks in the agriculture domain is presented along with several considerations and challenges. This survey includes wireless communication technologies, sensors, and wireless nodes used to assess the environmental behaviour, the platforms used to obtain spectral images of crops, the common vegetation indices used to analyse spectral images and applications of WSN in agriculture. As a proof of concept, we present a case study showing how WSN-based PA system can be implemented. We propose an IoT-based smart solution for crop health monitoring, which is comprised of two modules. The first module is a wireless sensor network-based system to monitor real-time crop health status. The second module uses a low altitude remote sensing platform to obtain multi-spectral imagery, which is further processed to classify healthy and unhealthy crops. We also highlight the results obtained using a case study and list the challenges and future directions based on our work.
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Dattatraya, Patil Yogita, Shradha Guttedar, and Pooja Kulkarni. "Decision based Precision Farming using Wireless Sensor Network." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–7. https://doi.org/10.55041/ijsrem.ncft067.
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Agriculture played important role in the growth of the Indian economy. Quality growth in agriculture can be achieved by the use of new technologies. One such ever-growing area is Precision Farming (PF) with the advancement in WSN technology. The routing technique Delay-Constrained Energy-Efficient Cluster-based Multi-Hop Routing in Wireless Sensor Networks (DECM) resulted in energy conservation and minimized delay in non critical data transmission. The Precision Farming without Cluster-Based wireless sensor network (PFwoCB) provide transmission of emergency data with maximum delay. Precision farming using APTEEN (PFAPTEEN) incur more delay in response time for one-time and persistent queries while Decision based Precision Farming in Wireless Sensor Network (DPF) support transmission of data without delay in critical events such as soil moisture or microclimate conditions exceeding beyond the set threshold. Keywords: Clustering, Delay, Precision Farming, WSN, Routing
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Pereira de Souza, Beatriz, Marcio Nunes de Miranda, and Luiz Maltar Castello Branco. "An Energy-efficient Wireless Sensor Network Applied to Greenhouse Cultivation." ACM SIGMETRICS Performance Evaluation Review 51, no. 3 (2024): 19–21. http://dx.doi.org/10.1145/3639830.3639839.
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Wireless sensors have already been used for a long time in military, health, and agricultural environments [6]. Despite the advances in precision agriculture, wireless sensor networks remain a distant reality for small farmers, mainly greenhouse farmers, in developing nations. Fungi and bacteria cause damage to the cultures and tend to spread quickly, limiting its production. Therefore, their early detection is essential for the food production market.
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Shiltagh, Nadia Adnan, and Hasnaa Ahmed Abas. "Spiking Neural Network in Precision Agriculture." Journal of Engineering 21, no. 7 (2015): 17–34. http://dx.doi.org/10.31026/j.eng.2015.07.02.
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In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce power consumption of sensor nodes Modified Chain-Cluster based Mixed (MCCM) routing algorithm is used. According to MCCM, the sensors will send their packets that are less than threshold moisture level to the sink. The SNN with Modified Spike-Prop (MSP) training algorithm is capable of identifying soil, irrigation periods and monitoring the soil moisture level, this means that SNN has the ability to be an identifier and monitor. By applying this system the particular agriculture area reaches to the desired moisture level.
 
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Li, Changcheng, Deyun Chen, Chengjun Xie, and You Tang. "Algorithm for wireless sensor networks in ginseng field in precision agriculture." PLOS ONE 17, no. 2 (2022): e0263401. http://dx.doi.org/10.1371/journal.pone.0263401.
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In the research on energy-efficient networking methods for precision agriculture, a hot topic is the energy issue of sensing nodes for individual wireless sensor networks. The sensing nodes of the wireless sensor network should be enabled to provide better services with limited energy to support wide-range and multi-scenario acquisition and transmission of three-dimensional crop information. Further, the life cycle of the sensing nodes should be maximized under limited energy. The transmission direction and node power consumption are considered, and the forward and high-energy nodes are selected as the preferred cluster heads or data-forwarding nodes. Taking the cropland cultivation of ginseng as the background, we put forward a particle swarm optimization-based networking algorithm for wireless sensor networks with excellent performance. This algorithm can be used for precision agriculture and achieve optimal equipment configuration in a network under limited energy, while ensuring reliable communication in the network. The node scale is configured as 50 to 300 nodes in the range of 500 × 500 m2, and simulated testing is conducted with the LEACH, BCDCP, and ECHERP routing protocols. Compared with the existing LEACH, BCDCP, and ECHERP routing protocols, the proposed networking method can achieve the network lifetime prolongation and mitigate the decreased degree and decreasing trend of the distance between the sensing nodes and center nodes of the sensor network, which results in a longer network life cycle and stronger environment suitability. It is an effective method that improves the sensing node lifetime for a wireless sensor network applied to cropland cultivation of ginseng.
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Musa, Purnawarman, Herik Sugeru, and Eri Prasetyo Wibowo. "Wireless Sensor Networks for Precision Agriculture: A Review of NPK Sensor Implementations." Sensors 24, no. 1 (2023): 51. http://dx.doi.org/10.3390/s24010051.
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The integration of Wireless Sensor Networks (WSNs) into agricultural areas has had a significant impact and has provided new, more complex, efficient, and structured solutions for enhancing crop production. This study reviews the role of Wireless Sensor Networks (WSNs) in monitoring the macronutrient content of plants. This review study focuses on identifying the types of sensors used to measure macronutrients, determining sensor placement within agricultural areas, implementing wireless technology for sensor communication, and selecting device transmission intervals and ratings. The study of NPK (nitrogen, phosphorus, potassium) monitoring using sensor technology in precision agriculture is of high significance in efforts to improve agricultural productivity and efficiency. Incorporating Wireless Sensor Networks (WSNs) into the ongoing progress of proposed sensor node placement design has been a significant facet of this study. Meanwhile, the assessment based on soil samples analyzed for macronutrient content, conducted directly in relation to the comparison between the NPK sensors deployed in this research and the laboratory control sensors, reveals an error rate of 8.47% and can be deemed as a relatively satisfactory outcome. In addition to fostering technological innovations and precision farming solutions, in future this research aims to increase agricultural yields, particularly by enabling the cultivation of certain crops in locations different from their original ones.
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G, Sahitya, Balaji N, and Naidu C.D. "Prototyping of Wireless Sensor Network for Precision Agriculture." International Journal on Cybernetics & Informatics 5, no. 4 (2016): 65–70. http://dx.doi.org/10.5121/ijci.2016.5408.
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Blokhin, Yu I., and S. Yu Blokhina. "Wireless hybrid sensor network for agriculture monitoring." BIO Web of Conferences 141 (2024): 02025. https://doi.org/10.1051/bioconf/202414102025.
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This paper presents a hybrid wireless sensor network (WSN) for agricultural monitoring. The system was set up to facilitate monitoring of crop state, weather conditions and soil characteristics in real time in accordance with the application’s needs of three communication technologies: IEEE 802.15.4/ZigBee, WIFI and LTE 4G as a part of Internet of Things (IoT). Two types of sensor nodes were developed: a mobile sensor node with an optical camera and a sensor node with a soil moisture and temperature sensors. A base station operating as network coordinator was designed to control meteorological characteristics. The software of the sensor nodes has been written on the MicroPython language, the Pi Pico controller provides control and polling of peripheral devices in accordance with a given algorithm. At the base station, the data incoming from the sensor nodes have been processed with the calculation of soil parameters based on pre-set calibrations. After being processing, the data has been transmitted to the server. A Raspberry Pi 3B microcomputer and Java software are used to process data and manage the base station weather sensors. The interaction with the weather sensors has been completed in the frame of Pi4J project using the WiringPi libraries. On the server, the data has been distributed among the corresponding tables in the Agro database, each record has been assigned a unique identifier, date and time. PostgreSQL was chosen as the database management system. The choice of MicroPython determined by its simplicity and the availability of many ready-made web frameworks and libraries that facilitate the system development. For future applications, the system could be further modified and developed for precision agriculture.
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Than, Htike Aung, and Zin Latt Kyaw. "Performance Analysis on Energy Efficient and Scalable Routing Protocols of Wireless Sensor Network for Precision Agriculture." International Journal of Trend in Scientific Research and Development 3, no. 5 (2019): 2153–57. https://doi.org/10.5281/zenodo.3591163.
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This paper focuses on energy efficient routing protocols of wireless sensor network for the crop monitoring of precision agriculture. Precision agriculture can be defined as the advanced technology which is used the art and science to enhance crop production. In order to develop the precision agriculture, wireless sensor network technology becomes main issues in crop monitoring system. In this paper, two energy efficient and scalable routing protocols, Low Energy Adaptive Clustering Hierarchy LEACH and Distributed Energy Efficient Clustering DEEC protocols are analyzed in 100 square meters area with 100 sensor nodes. This paper mainly presents the dead nodes, alive nodes and amount of data received of routing protocols which will become main issues of crop monitoring system in precision agriculture. MATLAB software is utilized as core simulator for this research. Than Htike Aung | Kyaw Zin Latt "Performance Analysis on Energy Efficient and Scalable Routing Protocols of Wireless Sensor Network for Precision Agriculture" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27989.pdf
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Singh, Kamred Udham, Ankit Kumar, Linesh Raja, et al. "An Artificial Neural Network-Based Pest Identification and Control in Smart Agriculture Using Wireless Sensor Networks." Journal of Food Quality 2022 (May 17, 2022): 1–12. http://dx.doi.org/10.1155/2022/5801206.
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Despite living in a rural country, farmers in India face several challenges. Every year, they suffer significant losses due to agricultural insect infestation. These losses are primarily the result of inadequate field surveillance, crop diseases, and ineffective pesticide management. We need cutting-edge technology that is constantly evolving to maintain control over such major concerns responsible for output reductions year after year. Wireless sensor networks address all of these issues; in fact, wireless sensor network technology is quickly becoming the backbone of modern precision agriculture. We propose a strategy for pest monitoring using wireless sensor networks in this study by simply recognizing insect behaviour using various sensors. We proposed a rapid and accurate insect detection and categorization approach based on five important crops and associated insect pests. This method examines insect behaviour by collecting data from sensors placed in the field. The results show that the proposed work improves the accuracy of the existing work by 3.9 percent.
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Ajibola, Oyedeji. "A REVIEW OF WIRELESS SENSOR NETWORK POTENTIAL IN NIGERIA AS A TOOL FOR SUSTAINABLE DEVELOPMENT." Journal of Engineering Science XXVIII (1) (March 15, 2021): 67–74. https://doi.org/10.52326/jes.utm.2021.28(1).06.
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The emerging trend in the world of technology and Information Technology has posed so many opportunities and challenges. Wireless Sensor Network (WSN) is a relatively new and rapidly developing technology due to the advancement and development of the micro-electro-mechanical systems (MEMS) technology. The application areas of wireless sensor and wireless sensor network in the society as tools towards achieving sustainable development range from the health sector through the use of Wireless Body Area Networks (WBANs) to a safer, cleaner and healthier environment. This paper highlights and discusses the potentials of wireless sensor network technology in realizing sustainable development in our society, Nigeria as a case study. WSNs can be employed to improve access to quality health services, increased food production through precision agriculture to a better quality of human resources.
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Chen, Zhi Liang, Li Guo Tian, Meng Li, Yue Liu, and Jie Ping Zhang. "Design of CO2 Collection Node Based on ZigBee." Advanced Materials Research 461 (February 2012): 281–84. http://dx.doi.org/10.4028/www.scientific.net/amr.461.281.
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Precision agriculture relies upon the acquisition and processing of agricultural foundation information initially. One of important techniques of realizing it is the remote wireless low power consumption data collection. This paper employed the ZigBee wireless sensor network technology as well as AVR Atmega8L single-chip microcomputer and RF transceiver CC2530 as core parts, and eventually designed a wireless sensor network node for agriculture information collection. The node can accurately detect the concentration of CO2 in real time. Experiments show that the node works well, collects the data effectively and meets the design requirements
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Dr., Sangappa K. Rajeshwer. "Development and Design of a Wireless Sensor Network-Based Precision Agriculture System." Journal of Emerging Trends in Electrical Engineering 7, no. 1 (2025): 22–24. https://doi.org/10.5281/zenodo.14958382.
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<em>Precision agriculture is an advanced farming technique that optimizes agricultural productivity through the integration of technology. This paper presents the design and development of a precision agriculture system utilizing a wireless sensor network (WSN). The proposed system enables real-time monitoring of environmental conditions such as soil moisture, temperature, and humidity to enhance crop management. The architecture, components, and implementation strategy of the system are discussed, followed by a performance evaluation in a test environment. The results demonstrate the effectiveness of WSN-based precision agriculture in improving yield and resource efficiency.</em>
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Lloret, Jaime, Sandra Sendra, Laura Garcia, and Jose M. Jimenez. "A Wireless Sensor Network Deployment for Soil Moisture Monitoring in Precision Agriculture." Sensors 21, no. 21 (2021): 7243. http://dx.doi.org/10.3390/s21217243.
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The use of precision agriculture is becoming more and more necessary to provide food for the world’s growing population, as well as to reduce environmental impact and enhance the usage of limited natural resources. One of the main drawbacks that hinder the use of precision agriculture is the cost of technological immersion in the sector. For farmers, it is necessary to provide low-cost and robust systems as well as reliability. Toward this end, this paper presents a wireless sensor network of low-cost sensor nodes for soil moisture that can help farmers optimize the irrigation processes in precision agriculture. Each wireless node is composed of four soil moisture sensors that are able to measure the moisture at different depths. Each sensor is composed of two coils wound onto a plastic pipe. The sensor operation is based on mutual induction between coils that allow monitoring the percentage of water content in the soil. Several prototypes with different features have been tested. The prototype that has offered better results has a winding ratio of 1:2 with 15 and 30 spires working at 93 kHz. We also have developed a specific communication protocol to improve the performance of the whole system. Finally, the wireless network was tested, in a real, cultivated plot of citrus trees, in terms of coverage and received signal strength indicator (RSSI) to check losses due to vegetation.
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Brinis, Nour, and Leila Azouz Saidane. "Context Aware Wireless Sensor Network Suitable for Precision Agriculture." Wireless Sensor Network 08, no. 01 (2016): 1–12. http://dx.doi.org/10.4236/wsn.2016.81001.
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Karuppasamy, Dr K., T. N. Prabhu, and B. Mohankumar. "Precision of Soil Moisture in Agriculture Land Using Wireless Sensor Networks." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (2019): 506–12. http://dx.doi.org/10.5373/jardcs/v11sp10/20192837.
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Moreno-Moreno, Carlos D., María Brox-Jiménez, Andrés A. Gersnoviez-Milla, Mariano Márquez-Moyano, Manuel A. Ortiz-López, and Francisco J. Quiles-Latorre. "Wireless Sensor Network for Sustainable Agriculture." Proceedings 2, no. 20 (2018): 1302. http://dx.doi.org/10.3390/proceedings2201302.
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Precision agriculture can be defined as the science of using technology to improve the agricultural production. It is advisable for farmers to use a decision support system; in fact, real–time monitoring of climatic conditions is the only way to know the water needed by a cultivation. On the other hand, since the 1990s, a strong decrease of the Mediterranean Quercus has been observed in the pastures of southwestern Spain and Portugal, causing a high mortality of holm and cork oak trees. Among the factors associated with this decrease, the radical decomposition caused by Phytophthora Cinnamomi is remarkable for its gravity, which makes it necessary to reforest the trees and to monitor the microclimatic factors that have an influence on this regeneration. Wireless Sensor Networks (WSN) are a technology in full evolution and development, as well as their appropriate use in cultivations that help to implement ecological techniques. With these considerations in this work five units/nodes with one or more sensors that allow different environmental readings have been developed. In this work, the acquisition of data obtained from different sensors has been achieved, allowing the monitoring of climatic elements such as soil moisture, air quality, temperature and humidity, rainfall intensity, precipitation level, wind speed and direction, luminous flux and atmospheric pressure. A web page has been designed where the user can consult the climatic conditions of the cultivation or reforestation. Different devices interconnected with a central unit have been developed where measurements of the cultivation are sent for its later analysis by the farmer. The microclimatic data acquisition developed in the WSN proposed in this paper allows a farmer to make decisions about the irrigation of the cultivation, use of fertilizers, the development and maturation phases of the cultivated products, obtaining the optimum stages of cultivation and harvesting.
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Smara, Mounya, and Al-Sakib Khan Pathan. "An Enhanced Mechanism for Fault Tolerance in Agricultural Wireless Sensor Networks." Network 4, no. 2 (2024): 150–74. http://dx.doi.org/10.3390/network4020008.
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Fault tolerance is a critical aspect for any wireless sensor network (WSN), which can be defined in plain terms as the quality of being dependable or performing consistently well. In other words, it may be described as the effectiveness of fault tolerance in the event of crucial component failures in the network. As a WSN is composed of sensors with constrained energy resources, network disconnections and faults may occur because of a power failure or exhaustion of the battery. When such a network is used for precision agriculture, which needs periodic and timely readings from the agricultural field, necessary measures are needed to handle the effects of such faults in the network. As climate change is affecting many parts of the globe, WSN-based precision agriculture could provide timely and early warnings to the farmers about unpredictable weather events and they could take the necessary measures to save their crops or to lessen the potential damage. Considering this as a critical application area, in this paper, we propose a fault-tolerant scheme for WSNs deployed for precision agriculture. Along with the description of our mechanism, we provide a theoretical operational model, simulation, analysis, and a formal verification using the UPPAAL model checker.
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Rodríguez-Robles, Javier, Álvaro Martin, Sergio Martin, José A. Ruipérez-Valiente, and Manuel Castro. "Autonomous Sensor Network for Rural Agriculture Environments, Low Cost, and Energy Self-Charge." Sustainability 12, no. 15 (2020): 5913. http://dx.doi.org/10.3390/su12155913.
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Over the last years, existing technologies have been applied to agricultural environments, resulting in new precision agriculture systems. Some of the multiple profits of developing new agricultural technologies and applications include the cost reduction around the building and deployment of them, together with more energy-efficient consumption. Therefore, agricultural precision systems focus on developing better, easier, cheaper, and overall more efficient ways of handling agricultural monitoring and actuation. To achieve this vision, we use a set of technologies such as Wireless Sensor Networks, Sensors devices, Internet of Things, or data analysis. More specifically, in this study, we proposed a combination of all these technologies to design and develop a prototype of a precision agriculture system for medium and small agriculture plantations that highlights two major advantages: efficient energy management with self-charging capabilities and a low-cost policy. For the development of the project, several prototype nodes were built and deployed within a sensor network connected to the cloud as a self-powered system. The final target of this system is, therefore, to gather environment data, analyze it, and actuate by activating the watering installation. An analysis of the exposed agriculture monitoring system, in addition to results, is exposed in the paper.
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Singh, Ritesh, Michiel Aernouts, Mats De Meyer, Maarten Weyn, and Rafael Berkvens. "Leveraging LoRaWAN Technology for Precision Agriculture in Greenhouses." Sensors 20, no. 7 (2020): 1827. http://dx.doi.org/10.3390/s20071827.
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The technology development in wireless sensor network (WSN) offers a sustainable solution towards precision agriculture (PA) in greenhouses. It helps to effectively use the agricultural resources and management tools and monitors different parameters to attain better quality yield and production. WSN makes use of Low-Power Wide-Area Networks (LPWANs), a wireless technology to transmit data over long distances with minimal power consumption. LoRaWAN is one of the most successful LPWAN technologies despite its low data rate and because of its low deployment and management costs. Greenhouses are susceptible to different types of interference and diversification, demanding an improved WSN design scheme. In this paper, we contemplate the viable challenges for PA in greenhouses and propose the successive steps essential for effectual WSN deployment and facilitation. We performed a real-time, end-to-end deployment of a LoRaWAN-based sensor network in a greenhouse of the ’Proefcentrum Hoogstraten’ research center in Belgium. We have designed a dashboard for better visualization and analysis of the data, analyzed the power consumption for the LoRaWAN communication, and tried three different enclosure types (commercial, simple box and airflow box, respectively). We validated the implications of real-word challenges on the end-to-end deployment and air circulation for the correct sensor readings. We found that temperature and humidity have a larger impact on the sensor readings inside the greenhouse than we initially thought, which we successfully solved through the airflow box design.
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Song, Ge Lian, Mao Hua Wang, Xiao Ying, Rui Yang, and Bin Yun Zhang. "The Application of Wireless Sensor Network in Agriculture Information Collection." Applied Mechanics and Materials 263-266 (December 2012): 872–77. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.872.
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It is an important foundation to precision agriculture to collect the influence information of the crop quickly and effectively. The traditional laboratory manual collect and analysis method has been difficult to meet the timeliness requirements of agriculture information collection, through the wireless sensor network to carry on the agriculture information collection is a good way to solve the problem. In this paper, we propose a farmland data acquisition system based on the Wireless Sensor Network technology. The system establishes the whole crop monitoring system through exerting GPRS network and combining integrated circuits, sensors and GPRS communication modules on data transmission. And by using the internet, GPRS and field monitoring communication, the data center can produce a complete record, the curve showing and query of field data, meanwhile it can detect equipment remotely.
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Li, Xiaomin, Lixue Zhu, Xuan Chu, and Han Fu. "Edge Computing-Enabled Wireless Sensor Networks for Multiple Data Collection Tasks in Smart Agriculture." Journal of Sensors 2020 (February 25, 2020): 1–9. http://dx.doi.org/10.1155/2020/4398061.
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At present, precision agriculture and smart agriculture are the hot topics, which are based on the efficient data collection by using wireless sensor networks (WSNs). However, agricultural WSNs are still facing many challenges such as multitasks, data quality, and latency. In this paper, we propose an efficient solution for multiple data collection tasks exploiting edge computing-enabled wireless sensor networks in smart agriculture. First, a novel data collection framework is presented by merging WSN and edge computing. Second, the data collection process is modeled, including a plurality of sensors and tasks. Next, according to each specific task and correlation between task and sensors, on the edge computing server, a double selecting strategy is established to determine the best node and sensor network that fulfills quality of data and data collection time constraints of tasks. Furthermore, a data collection algorithm is designed, based on set values for quality of data. Finally, a simulation environment is constructed where the proposed strategy is applied, and results are analyzed and compared to the traditional methods. According to the comparison results, the proposal outperforms the traditional methods in metrics.
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Bharathi Priya, C., and S. Sivakumar. "A survey on localization techniques in wireless sensor networks." International Journal of Engineering & Technology 7, no. 1.3 (2017): 125. http://dx.doi.org/10.14419/ijet.v7i1.3.9671.
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Wireless Sensor Networks (WSNs) are a kind of ad-hoc networks where the nodes in the network have sensors on board and can sense different phenomena around the sensors deployed in the field. WSNs became very popular due to its diverse nature of applications including Cyber-Physical Systems (CPS), Precision Agriculture, Disaster relief & Rescue operation, Object Tracking in terrestrial environment, Health care application to monitor the physical parameters of a human, space application etc. Most applications use the location information of a sensor node as an inherent characteristic. Location information is mandatory in order to identify in which spatial coordinate the sensor data originates. Broadly, the localization techniques are classified as: range based and range free methods. Hence study of localization techniques for Wireless Sensor Networks is highly significant today for different kind of applications. This paper gives an overview on survey of localization techniques in Wireless Sensor Networks and its current significance.
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S., Anulekshmi. "Comprehensive Study and Research on Wireless Sensor Network and Internet of Things for Precision Agriculture." Journal of Advanced Research in Dynamical and Control Systems 24, no. 4 (2020): 150–58. http://dx.doi.org/10.5373/jardcs/v12i4/20201427.
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Seth, Avalokita Anupam, and Ritu Singh. "A Prototype of Wireless Sensor Network Used In Precision Agriculture." International Journal of Computer Sciences and Engineering 6, no. 5 (2018): 712–16. http://dx.doi.org/10.26438/ijcse/v6i5.712716.
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LI, Zhen, Tian-sheng HONG, and WANG Ning. "Review on wireless sensor network technology applications in precision agriculture." JOURNAL OF HUNAN AGRICULTURAL UNIVERSITY 37, no. 5 (2011): 576–80. http://dx.doi.org/10.3724/sp.j.1238.2011.00576.
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Shouyi, Yin, Liu Leibo, Zhou Renyan, Sun Zhongfu, and Wei Shaojun. "Design of wireless multi-media sensor network for precision agriculture." China Communications 10, no. 2 (2013): 71–88. http://dx.doi.org/10.1109/cc.2013.6472860.
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R. Bindu, L., P. Titus, and D. Dhanya. "Clustered Wireless Sensor Network in Precision Agriculture via Graph Theory." Intelligent Automation & Soft Computing 36, no. 2 (2023): 1435–49. http://dx.doi.org/10.32604/iasc.2023.030591.
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Sahota, Herman, Ratnesh Kumar, and Ahmed Kamal. "A wireless sensor network for precision agriculture and its performance." Wireless Communications and Mobile Computing 11, no. 12 (2011): 1628–45. http://dx.doi.org/10.1002/wcm.1229.
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Fahmi, Nurul, Eko Prayitno, and Siti Fitriani. "Web of Thing Application for Monitoring Precision Agriculture Using Wireless Sensor Network." JURNAL INFOTEL 11, no. 1 (2019): 22. http://dx.doi.org/10.20895/infotel.v11i1.421.
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Wireless Sensor Network (WSN) is a technology that can help humans solve problems in daily life for monitoring the environment. This can be done to help farmers in monitoring and making decisions for watering plants. In this study, temperature, humidity and soil moisture sensors were used to help farmers monitor web-based precision agriculture, and the system we built could make a decision to automatically water plants based on soil conditions. The results of measuring precision agriculture from the sensor node will be se nt to the gateway using Zigbee 802.15.4. The data will be stored in the MySQL database provided by the gateway. Then it will be synchronized to the cloud using IoT technology, so users can access it in real time by using web -based application. From the system that we developed, it really helps farmers to complete their work and make innovations in the digital era
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García, Laura, Lorena Parra, Jose M. Jimenez, Jaime Lloret, and Pascal Lorenz. "Practical Design of a WSN to Monitor the Crop and its Irrigation System." Network Protocols and Algorithms 10, no. 4 (2019): 35. http://dx.doi.org/10.5296/npa.v10i4.14147.
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Due to environmental problems, such as the lack of water for irrigation, each day it becomes more necessary to control crops. Therefore, the use of precision agriculture becomes more evident. When it comes to making decisions on crops, it is evident the need to apply the concept of Smart Agriculture, that focuses on utilizing different sensors and actuators. As the number of IoT devices used in agriculture grows exponentially, it is necessary to design the implemented network so that the data is transmitted without problems. The present work shows a wireless network design, in which we use the information collected by the sensors of a Wireless Sensor Network (WSN), and a Wireless Mesh Network (WMN) formed by Access Points (AP) to transmit the data to a network that monitors agriculture for smart irrigation. In addition, through simulations we have presented a proposal of the maximum number of nodes that must be connected to an AP so that the network is efficient.
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Romanov, Volodymyr, Igor Galelyuka, Volodymyr Hrusha, et al. "Smart-Systems for Precision Agriculture, Environmental Protection and Healthcare." Cybernetics and Computer Technologies, no. 2 (July 28, 2023): 69–90. http://dx.doi.org/10.34229/2707-451x.23.2.7.
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Appearance of innovative tools of informatics in the world is determined by development of information-communication technology, microelectronics, sensor and biosensor technologies. Spreading of these technologies on precision agriculture, environmental protection and health care gives opportunity to create smart fields, gardens, greenhouses, forests and parks, and also smart health monitors, which estimate the health state of person as in rehabilitation, so in emergency situations. Results of research of authors in the development of new information technologies and creation of main components of the smart systems for different purposes on this base are shows in this paper. Main requirements for knowledge bank for precision agriculture and ecological monitoring are defined. Main principles of creating knowledge bank on base of requirements are proposed. The typical smart system models and their development stages are considered. Structure of wireless multilevel networks for the estimation of state of biological objects of different origin and their nodes are described. Developed sensor networks and smart systems for agriculture are considered. Structure of proposed smart system for agriculture and ecological monitoring is given. Approaches for chlorophyll fluorescence induction curves analysis are studied. Results of network testing for the estimation of the autonomous work time of network nodes and possible errors are given. Wireless sensor network and smart system for remote medical monitoring are described. Diagnostic smart systems for estimation of quality of life are considered. Medical communicator, computer device on base of tablet computer, was used for their development. The short form of Survey Instrument (SF-36) for life quality estimation and abnormal uterine bleeding questionnaire, which was developed in State Scientific Institution "Center for Innovative Medical Technologies of the National Academy of Sciences of Ukraine", were embedded in communicator. STEPS questionnaire which was designed for epidemiological monitoring of the prevalence of noncommunicable diseases and their risk factors in the target subpopulations could be added to communicator. Development of smart systems for estimation of quality of life and prevalence of noncommunicable diseases was made in cooperation with R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology NAS of Ukraine (department of research management and innovation), Chebotarev Institute of Gerontology of the National Academy of Medical Sciences of Ukraine, Center for Innovative Medical Technologies of the National Academy of Sciences of the Ukraine. Keywords: wireless sensor network, precision agriculture, chlorophyll fluorescence induction, express-diagnostics of plant state, quality of life, SF-36.
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Križanović, Višnja, Krešimir Grgić, Josip Spišić, and Drago Žagar. "An Advanced Energy-Efficient Environmental Monitoring in Precision Agriculture Using LoRa-Based Wireless Sensor Networks." Sensors 23, no. 14 (2023): 6332. http://dx.doi.org/10.3390/s23146332.
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Sensor networks, as a special subtype of wireless networks, consist of sets of wirelessly connected sensor nodes often placed in hard-to-reach environments. Therefore, it is expected that sensor nodes will not be powered from the power grid. Instead, sensor nodes have their own power sources, the replacement of which is often impractical and requires additional costs, so it is necessary to ensure minimum energy consumption. For that reason, the energy efficiency of wireless sensor networks used for monitoring environmental parameters is essential, especially in remote networking scenarios. In this paper, an overview of the latest research progress on wireless sensor networks based on LoRa was provided. Furthermore, analyses of energy consumption of sensor nodes used in agriculture to observe environmental parameters were conducted using the results of real measurements in the field, as well as simulations carried out based on collected data about real equipment. Optimization methods of energy consumption, in terms of choosing the appropriate data collection processes from the conducted field measurements, as well as the settings of network radio parameters imitating real conditions used in conducted simulations were highlighted. In the analyses, special emphasis was placed on choosing the optimal packet size. Unlike in other papers analyzing energy efficiency of LoRa communication, in this paper, it was proven that the adjustment of the transmission speed to the actual size of the packet is important for better energy efficiency of communication and that it can reduce energy consumption considerably. Moreover, in the paper, the contents of a packet that can be used in precision agriculture is suggested in order to prove that the 6-bit packet is sufficient for energy-efficient collection of parameters from the environment, in contrast to the 11-bit packets used in standard commercially available equipment.
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Yu, Cunjiang. "Low Cost Locating Method of Wireless Sensor Network in Precision Agriculture." Cybernetics and Information Technologies 16, no. 6 (2016): 123–32. http://dx.doi.org/10.1515/cait-2016-0082.
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Abstract The wireless sensor network covers more scale with more sensor nodes for larger scale agriculture. The article describes improvement of DV-Hop Algorithm to locate the nodes with quadrilateral range positioning method, so that the difficulty of dilatation method in agriculture actual application to be solved. The analog test for the algorithm is conducted and is mainly developed for the average locating error with illustration and discussion on the proportion relations of average error, average connectivity and anchor nodes. According to the analog results, the algorithm obtains better effect on the average locating error, which improves the accuracy of the algorithm.
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Dey, Sreedeep, and Sreejita Das. "Sowing the Seeds of Precision: Innovations in Wireless Sensor Networks for Agricultural Environmental Monitoring." International Journal on AdHoc Networking Systems 14, no. 2/3 (2024): 01–17. http://dx.doi.org/10.5121/ijans.2024.14301.
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Wireless Sensor Networks (WSNs) are used in precision agriculture to provide real-time environmental parameter monitoring that is essential to crop productivity. This study looks at the most current advancements in WSN technology and its application in monitoring vital factors including temperature, humidity, soil moisture, and light intensity in agricultural contexts, with an emphasis on the agricultural region of Bardhaman District, West Bengal, India. For sustainable and long-term sensor network functioning in this area, the study looks into several sensor placement procedures, creative data aggregation strategies, and energy-efficient protocols. To improve data accuracy and decision-making abilities, contemporary analytics techniques like machine learning and data fusion are also used. The results highlight how well WSNs work in Bardhaman District to maximise agricultural sustainability and productivity. The study discusses issues with WSN deployment, like network connectivity and power management, and suggests solutions specific to the region's agricultural environment. The goal of future study is to improve the precision agricultural utility of WSNs even more, with an emphasis on boosting resilience and productivity in farming operations in Bardhaman District.
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Said, Maroua, Jaouhar Fattahi, Said Ghnimi, Ridha Ghayoula, and Noureddine Boulejfen. "Measuring Electromagnetic Properties of Vegetal Soil for Wireless Underground Sensor Networks in Precision Agriculture." Applied Sciences 14, no. 24 (2024): 11884. https://doi.org/10.3390/app142411884.
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This research examines and analyzes the measured electromagnetic characteristics of vegetal soil for Wireless Underground Sensor Networks applied to precision agriculture. For this, we used Wireless Underground Sensor Network (WUSN) technology, which consists of sensors that communicate through the soil to collect data on irrigation, such as temperature and humidity, for good plant growth. However, underground communication channels and signal transmission are required to travel through a dense and heterogeneous soil mixture. For the measurement results of the vegetal soil dielectric parameters, a precision domain sensing probe operating at 433 Mhz was used. Moreover, the different choices of capacitance, inductance, and varactor were included, with a reasonable estimation of the dielectric permittivity, ranging from 2 to 15, and an unlimited range of conductivities. Despite promising results in predicting the dielectric permittivities, several improvements were made to the mode for low permittivity values, and it was designed to accommodate a wide range of dielectric permittivities.
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Solanki, Parimal, Dr Dipak M Patel, and Dr Darshak G Thakore. "A Survey on Smart Agricultural System Using LoRa Wireless Technology." International Journal for Modern Trends in Science and Technology 6, no. 5 (2020): 13–18. http://dx.doi.org/10.46501/ijmtst060503.
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Over the past few years, the designing in smart agriculture system is a very important concept. Using smart farming techniques we can build up the crop yield, and concurrently attain better output from the input. In precision agriculture, a wireless sensor network brings a cost-effective solution to watch and manipulate. We already have many wireless protocols like Wi-Fi, Cellular, BLE (Bluetooth low energy), etc. Although this automation, not optimal for cultivation sensor nodes, there is a demand to send information to a great distance without an internet connection. This leads to boost the LoRa (Long range) technology, which can do very long-range transmission with the lowest cost [14]. The paper provides a brief survey of certain requirements for Smart Agriculture such as wireless sensor networks.
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Goel, Swati, Kalpna Guleria, and Surya Narayan Panda. "Machine Learning Techniques for Precision Agriculture Using Wireless Sensor Networks." ECS Transactions 107, no. 1 (2022): 9229–38. http://dx.doi.org/10.1149/10701.9229ecst.
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In India, approximately 70% of the total population is dependent on agriculture for their livelihood. Hence, it is essential to pay attention to agriculture to increase crop quality and quantity, thus increasing the overall cultivation yield. The traditional methods used require a lot of farmer’s effort and hard work, which results in delayed crop cultivation. Moreover, it’s challenging to predict the environmental conditions and detect the particular area where there are weeds, insects, etc., which requires immediate treatments, thus affecting overall crop production. So, there is a need to make it automated, and this can be done by adopting advanced techniques of precision agriculture (PA) or intelligent agriculture. Precision agriculture is one of the fields in which wireless sensor networks (WSNs) are widely adopted, which consists of a large number of sensors placed in the field to monitor and measure the various environmental parameters, such as humidity, temperature, soil moisture, soil PH value, precipitation, water level, etc., for enhancing the productivity, profitability, quantity, and quality of crops. The machine learning techniques can be applied to precision agriculture to increase crop growth, manage the process of crop cultivation, and create a perfect environment for the crops to increase productivity with less human effort. This paper provides an insight into various machine learning techniques used for precision agriculture using wireless sensor networks.
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Kaushal, N. V. "Precision Agriculture using LoRaWAN." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 3867–71. http://dx.doi.org/10.22214/ijraset.2021.35818.
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The growing world population as well as increased awareness of the stress, agriculture places on the atmosphere has put farmers beneath intense pressure. Its value is noting that the farmers have long leveraged the technological breakthroughs and to adapt agricultural practices to ever-changing in times and this era is no exception, significantly with the emergency of fine Agriculture. Advanced commercial enterprise is fully dependent on power to efficiently manage resources so as to cut back the environmental impact, minimize the price and maximize the yield. Farmers are facing the associate degree interconnected to host of challenges and thus, having interest in incorporating the innovative technological solutions. Harnessing technology to alter precision agriculture has emerged to produce farmers with the tools they need to serve a half-hour larger population within the future in a very property approach that's harmonical with nature. The wireless sensor network (WSN) is a technology that has quickly been evolved over the years by enabling the spectrum of applications like industry, military, and agriculture. The LoRa devices have provided the ability to mechanically monitor the crops and the animals, which further provides the profitable knowledge which has been collected manually. During this project we tend to come up with a technology, to form a wireless network and alter the irreversible consequences of poor irrigation management. By dispersing the sensors that are connected to the phones or computers of the farmers will instantly receive the data on soil moisture and temperature, weather and rain, crop growth, and also receive the alerts on fire or theft and will activate irrigation instrumentation. All the data collected can feed into call management tools that helps the farmers to take the correct call at the correct time to get optimized results and will guarantee the property of his farm so high price knowledge are often transmitted over distances of up to fifteen metric linear unit from the sensors whose batteries which is lasting up to 10 years, leading to lower the maintenance and in operation prices beside the larger operational visibility, that successively empowers farmers to build their businesses.
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Abbas, Ash Mohammad. "Target Tracking in Wireless Sensor Networks." Journal of Computer Science and Technology 21, no. 1 (2021): e8. http://dx.doi.org/10.24215/16666038.21.e8.
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A Wireless Sensor Network (WSN) consists of a group of tiny devices called sensors that communicate throughwireless links. Sensors are used to collect data about some parameters and send the collected data for furtherprocessing to a designated station. The designated station is often called command and control center (CCC),fusion center (FC), or sink. Sensors forward the collected data to their leaders or cluster heads, which in turn sendit to the centralized station. There are many applications of a WSN such as environmental monitoring, raisingalarms for fires in forests and multi-storied buildings, monitoring habitats of wild animals, monitoring children ina kindergarten, support system in play grounds, monitoring indoor patients in a hospital, precision agriculture,detection of infiltration along international boundaries, tracking an object or a target, etc.