The contents of this paper include nano-sensor for agricultural product quality and safety, solar insecticidal lamp, clustering routing algorithm, hybrid multi-hop routing algorithm for farmland Internet of Things, development of dissolved oxygen sensor for aquaculture, near-field remote sensing method for soil nutrients, remote intelligent management platform for agricultural machinery, intelligent perception and accurate ratio of water and fertilizer concentration, multi-robot communication in orchard, etc. , for your reading and reference.
Topic-Agricultural Sensors and Internet of Things
Theme-Agricultural Sensors and Internet of Things
[1] Wang Peilong, Tang Zhiyong. Research, Analysis and Prospect on the Application of Nanosensors in the Quality and Safety of Agricultural Products [J]. Smart Agriculture (in Chinese and English), 2020,2 (2):1-10.
Wang Peilong, Tang Zhiyong. Application Analysis and Prospect of Nanosensors in the Quality and Safety of Agricultural Products [J]. Smart Agriculture, 2020,2 (2):1-10.
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[2] Yang Xing, Li, Huo Zhiqiang, Lu Qiaoling, Zhang Yacheng. Fault diagnosis characteristics and potential challenges of the Internet of Things of solar insecticidal lamps [J]. Smart Agriculture (in Chinese and English), 2020,2 (2):11-27.
Yang Xing, Shu Lei, Li, Huo Zhiqiang, Lu Qiaoling, Zhang Yacheng. Characteristic analysis and challenge of fault diagnosis of solar insecticidal lamp [J]. Internet of Things. Smart Agriculture, 2020,2 (2):11-27.
SIL-IoTs is a new physical agricultural pest control tool based on agricultural scenes and Internet of Things technology. By wirelessly transmitting the status data of the solar insecticidal lamp assembly, users can view the running status of the solar insecticidal lamp in real time in the background, which has the functions of pest counting, pest positioning, auxiliary agricultural monitoring and so on. However, with the rapid development and wide application of the Internet of Things, the contradiction between fault diagnosis and maintenance has become increasingly prominent. Based on this, this study first expounds the structure and research status of SIL-IoTs, analyzes the importance of fault diagnosis, and points out that fault diagnosis is the main means to ensure its reliability. Then, the faults of solar insecticidal lamp nodes and their manifestations in wireless sensor networks are introduced, and the faults in wireless sensor networks are further classified, including four types: behavior-based faults, time-based faults, component-based faults and affected area-based faults. Then, the main fault diagnosis methods of wireless sensor networks are discussed, such as statistical method, probability method, hierarchical routing method, machine learning method, topology control method and mobile base station method. In addition, the fault diagnosis strategy of SIL-IoTs is also discussed. Fault diagnosis is divided into active diagnosis and passive diagnosis strategies in behavior, continuous diagnosis, periodic diagnosis, direct diagnosis and indirect diagnosis strategies in monitoring types, and centralized, distributed and mixed strategies in equipment. On the basis of the above-mentioned fault diagnosis methods and strategies, this paper introduces WSNs fault diagnosis and debugging tools, such as Sympathy, Clairvoyance, SNIF and Dustminer, which are suitable for four kinds of fault phenomena, such as abnormal background data, abnormal communication of some nodes, abnormal whole network communication and undiagnosed abnormality. Finally, the potential challenges brought by the characteristics of SIL-IOT to fault diagnosis are emphasized, including complex deployment environment, conflict of node tasks, inability of nodes in continuous areas to transmit data and failure of various fault diagnosis, and reasonable research directions are pointed out for these potential challenges. Because SIL-IoTs is a typical application of agricultural Internet of Things, this study can be extended to other agricultural Internet of Things, providing reference for fault diagnosis of these agricultural Internet of Things.
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Wang Jinhong, Han Yuxing. Clustering routing algorithm for crop phenotypic information edge calculation and acquisition in cognitive wireless sensor networks [J]. Smart Agriculture (Chinese and English), 2020,2 (2): 28-47.
Wang Jinhong, Han Yuxing. Clustering routing algorithm for crop phenotypic information edge calculation and collection in cognitive radio sensor networks [J]. Smart Agriculture, 2020,2 (2): 28-47.
Abstract: With the rapid growth of the number of wireless terminals and the increasing demand for high-bandwidth transmission services such as multimedia images, there will be a shortage of wireless spectrum resources in related fields of agricultural Internet of Things. In the crop phenotypic information collection system based on the traditional Internet of Things, the intensive deployment of nodes leads to frequent spectrum competition and data congestion during data transmission, and the unbalanced energy consumption of fixed battery network leads to the shortening of monitoring period. In order to solve these problems, a crop phenotypic information collection model based on cognitive wireless sensor network (CRSN) is established, and an event-driven clustering routing algorithm with edge computing mechanism is proposed. The algorithm includes: (1) dynamic spectrum sensing clustering, combining available channels, distance between nodes, residual energy and neighbor node degree obtained by spectrum sensing as similarity, using hierarchical clustering algorithm to cluster nodes in the monitoring area and select cluster heads, and introducing reward and punishment factors into the balance of cluster size in the process of constructing clustering topology to improve the average spectrum utilization rate of each cluster in the network; (2) integrating the event-triggered data routing calculated by the edge, and forwarding the event triggered by the abnormal phenotypic information of each area to be detected to a sink node in an alternating iterative manner of intra-cluster aggregation and inter-cluster relay, wherein intra-cluster aggregation includes direct transmission and intra-cluster relay, and inter-cluster relay includes two situations: a main gateway node and a secondary gateway node-a main gateway node; (3) Adaptive re-clustering based on spectrum change and communication quality of service (QoS): Based on the interference of available channel change or poor clustering effect caused by the change of primary user behavior on communication quality, CRSN is triggered to perform adaptive re-clustering. In addition, a new energy consumption balancing strategy is proposed to disperse energy consumption (assuming sink as the center), that is, a weight coefficient proportional to the distance between nodes and sink is introduced into the calculation formula of gateway or cluster head node selection. The simulation results show that, compared with the event-driven clustering (ERP) routing scheme based on K-medoid clustering and energy awareness, the clustering routing algorithm based on DSEB has a certain improvement in network lifetime and energy efficiency under the premise of a fixed number of CRSN nodes. When the number of primary user nodes is fixed, this algorithm has higher spectrum utilization than the other two algorithms.
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Gu Hao, Wang Zhiqiang, Wu Hao, Jiang Yongnian, Guo Ya. Development and experiment of dissolved oxygen sensor based on fluorescence principle [J]. Smart Agriculture (Chinese and English), 2020,2 (2): 48-58.
Gu Hao, Wang Zhiqiang, Wu Hao, Jiang Yongnian, Guo Ya. A dissolved oxygen sensor based on fluorescence [J]. Smart Agriculture, 2020,2 (2): 48-58.
The measurement of dissolved oxygen content is of great significance to aquaculture. However, the dissolved oxygen sensors in China's market are expensive, unable to measure continuously on line, and the components are difficult to maintain and update, so it is difficult to popularize and play a role in aquaculture Internet of Things. Based on the principle of fluorescence quenching, a low-cost and easy-to-maintain dissolved oxygen sensor is developed by using the relationship between dissolved oxygen concentration in water and the phase difference of fluorescence signal. Firstly, a self-made dissolved oxygen sensitive membrane is used to generate red fluorescence under excitation light, and the fluorescence lifetime can be adjusted by dissolved oxygen concentration. Then the photoelectric conversion circuit is designed by using optical signal sensitive devices to realize optical signal perception; Then, taking STM32F 103 microprocessor as the main control chip, the lower computer program is written to realize the generation of excitation light pulses. The phase difference between excitation light and reference light is calculated by using the principle of phase-sensitive detection and fast Fourier transform, and then converted into dissolved oxygen concentration, thus realizing the measurement of dissolved oxygen. The fluorescence detection part and the main control part of the system adopt the separated design idea, and the shielded flat cable is used to plug and connect directly, which is convenient for the disassembly, replacement and maintenance of the sensor probe and remote on-line measurement. The measurement range of the dissolved oxygen sensor is 0~20 mg/L, the response delay is less than 2 s, and the service life of the dissolved oxygen sensitive membrane is about 1 year, which can continuously measure the dissolved oxygen concentration in real time. At the same time, the sensor has the characteristics of convenient measurement, low manufacturing cost and small volume, which lays a good foundation for the research and development and marketization of low-cost dissolved oxygen sensors for aquaculture in China.
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Zi, Dong Daming, Zhao Xiande, Tian Hongwu. Study on near-field remote sensing method of soil nutrients based on modulated near-infrared reflectance spectrum [J]. Smart Agriculture (Chinese and English), 2020,2 (2): 59-66.
Jiao Leizi, Dong Daming, Zhao Xiande, Tian Hongwu. Near-field Remote Sensing Detection of Soil Nutrients Based on Modulated Near Infrared Reflectance Spectrum [J]. Smart Agriculture, 2020,2 (2): 59-66.
Abstract: As an important index of agricultural production, too little soil nutrients will reduce crop yield, while too much soil nutrients will cause environmental pollution. Therefore, rapid and accurate detection of soil nutrients is of great significance for accurate fertilization and improving crop yield. Traditional methods based on sampling and chemical analysis can comprehensively and accurately detect soil nutrients, but the sampling and pretreatment process of soil in the detection process is complex, time-consuming and laborious, and it is impossible to realize in-situ rapid detection of soil nutrients. Based on modulated near infrared spectroscopy, an active near-field soil nutrient remote sensing method is proposed, which can effectively avoid the interference of natural light reflected by soil. In this method, an 8-channel narrow-band laser diode with the wavelength range of1260 ~1610 nm is used as the near infrared light source. By measuring the soil reflectivity of the 8-channel laser beam, the measurement model of nitrogen (N) in soil nutrients is established, and the rapid detection of N is realized. Among 74 groups of soil samples with known nitrogen content, 54 groups were selected as training sets and 20 groups as prediction sets. Based on the general linear model, the quantitative parameters of soil N content and soil reflectivity in the training set were trained, and the econometric model R2 after screening significant bands reached 0.97. Based on the established econometric model, the determination coefficient R2 between the predicted value and the reference value of soil N content under the predicted concentration reaches 0.9, and the results show that this method has the ability to quickly detect soil nutrients on the spot.
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Zhu Dengsheng, Fang Hui, Hu, Zhou Yansuo,,, He Yong. Development and Application of Remote Intelligent Management Platform for Agricultural Machinery [J]. Intelligent Agriculture (Chinese and English), 2020,2 (2): 67-81.
Zhu Dengsheng, Hu, Zhou Yansuo,,, He Yong. Development and application of intelligent remote management platform for agricultural machinery [J]. Smart Agriculture, 2020,2 (2): 67-81.
In view of the lack of real-time data in agricultural machinery management, the difficulty in monitoring the real-time operation of agricultural machinery and the asymmetry of service information, this study first puts forward five principles when designing a professional remote management platform: specialization, standardization, cloud platform, modularization and openness. Based on these principles, this study designed a customizable remote intelligent management platform for general agricultural machinery based on intelligent sensing technology, Internet of Things technology, positioning technology, remote sensing technology and geographic information system. The platform has designed and implemented several practical modules based on WebGIS, such as agricultural machinery information base and agricultural machinery location service, real-time monitoring and management of agricultural machinery operation, basic information management of farmland, basic information management of field crops, agricultural machinery dispatching management, agricultural machinery subsidy management, agricultural machinery operation order management and so on. This paper focuses on the realization methods of some key technologies of the platform under the current technical background, including the calculation method of working area under the premise of using low-precision GNSS positioning system, the analysis of data problems in the processing of GNSS positioning data, the scheduling algorithm of agricultural machinery, and the fusion of working sensor information. , put forward the idea of building a management platform with land as the core; At the same time, it is proposed that the agricultural machinery operation management platform will gradually change from simple operation management to comprehensive management of agricultural machinery in the field. This platform has certain reference significance for the research and development of similar management platforms.
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Jinzhou District, Zhang Junqing, Guo Hongyan, Hu Yimin, Chen Xiangyu, Yellow River and Wang Hongyan. Development and Experiment of Intelligent Sensing Accurate Proportioning System for Water and Fertilizer Concentration [J]. Intelligent Agriculture (Chinese and English), 2020,2 (2): 82-93.
Jinzhou, Zhang Junqing, Guo Hongyan, Hu Yimin, Chen Xiangyu, Yellow River and Wang Hongyan. Development and experiment of intelligent sensing precise proportioning system for water and fertilizer concentration [J]. Smart Agriculture, 2020,2 (2): 82-93.
In order to solve the problem of accurate proportion of compound fertilizer in local farms at that time, this study took the intelligent irrigation and fertilization system of water and fertilizer integration as the research object, and constructed the intelligent perception and accurate proportion system of water and fertilizer concentration. Firstly, a method for quickly establishing an online intelligent perception model of water and fertilizer solution is proposed, and the model is mined from a series of concentration gradient fertilizer solutions monitored by sensors in real time by using data analysis algorithm. Secondly, based on the above model, the frame structure of the intelligent sensing accurate ratio system of water and fertilizer concentration is designed, and the working principle of the system is expounded. The effectiveness of the system in guiding the water-fertilizer concentration ratio in situ was verified by simulating online fertilizer distribution in three kinds of water bodies, and the interference of water conductivity on the water-fertilizer concentration ratio was evaluated. The experimental results show that quadratic polynomial fitting curve is the best model to express the relationship between solution conductivity and water and fertilizer concentration, and the correlation coefficient R2 is greater than 0.999. From this model, the concentration of various indexes of compound fertilizer that users care about can be obtained. The results of simulated online fertilization of three kinds of water bodies show that the water body interferes with the conductivity, and the specific concentration of water and fertilizer cannot be accurately retrieved, and the relative deviation value exceeds 0. 1. Therefore, the online intelligent perception and accurate ratio system of water and fertilizer proposed in this study can eliminate the interference of local water conductivity on the accuracy of water and fertilizer ratio, realize the accurate ratio of compound fertilizer through model calculation, and get the concentration of each index. The system is simple in structure, accurate in proportion, easy to be combined with the existing water and fertilizer integrated machine or artificial fertilizer blending system, and can be widely used for precise and intelligent fertilization in facilities agriculture cultivation, orchard cultivation, field cash crop cultivation and other environments.
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Sun Haoran, Sun Lin, Bi Chunguang, Yu and Long. Hybrid multi-hop farmland Internet of Things routing algorithm based on particle swarm optimization and simulated annealing [J]. Smart Agriculture (Chinese and English), 2020,2 (3): 98-107.
Sun Haoran, Sun Lin, Bi Chunguang, Yu and Long. Hybrid Multi-hop Routing Algorithm for Farmland Internet of Things Based on Particle Swarm Optimization and Simulated Annealing [J]. Smart Agriculture, 2020,2 (3): 98-107.
Abstract: Agricultural wireless sensor network plays a key role in obtaining multi-source heterogeneous information such as farmland soil, environment and crop growth. Aiming at the problem of uneven distribution and limited energy of sensors in farmland, a hybrid multi-hop routing algorithm based on particle swarm optimization and simulated annealing is proposed. Firstly, cluster heads are selected by weighted residual energy and node degree, and efficient dynamic networking of heterogeneous networks is realized by clustering structure. Then the multi-hop data structure between cluster heads is used to solve the high energy consumption problem of long-distance transmission of cluster heads, and the collaborative optimization method of particle swarm optimization and simulated annealing is used to improve the convergence speed of the algorithm, so that the sink node can accelerate the collection of aggregated data in cluster heads. The simulation results show that compared with the multi-path routing strategy method based on energy-saving load balancing (PSMR), the life cycle of wireless sensor networks is increased by 57%. Compared with greedy peripheral stateless routing algorithm (GPSR-A), in the same network life cycle, the 1 th death sensor node is delayed by two rounds, and the standard deviation of residual energy is reduced by 0.04 J, which has good network energy balance. The PSMR algorithm proposed in this study reduces the extra energy consumption of remote cluster heads through multi-hop between cluster heads, improves the energy consumption balance performance of cluster heads at different distances, provides a technical basis for long-term, efficient and stable data collection and monitoring in large-scale complex farmland environment, and can improve the resource utilization efficiency of agricultural Internet of Things.
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Mao Wenju, Liu Heng, Wang Dongfei, Yang Fuzeng, Liu Zhijie. Improved design and test of AODV routing protocol for multi-robot communication in orchard [J]. Intelligent Agriculture (in Chinese and English), 202 1, 3 (1): 96- 108.
Mao Wenju, Liu Heng, Wang Dongfei, Yang Fuzeng, Liu Zhijie. Improved AODV routing protocol for multi-robot communication in orchard [J]. Intelligent Agriculture, 202 1, 3( 1): 96- 108.
Aiming at the communication requirements of multi-robots working in orchards, an improved on-demand plane distance vector routing protocol (AODV-SP) is proposed based on the Taoyuan Wi-Fi signal receiving strength prediction model and introducing priority nodes and path signal strength thresholds. The AODV-SP packet is designed, and the performance of on-demand plane distance vector routing protocol (AODV) and AODV-SP is compared from four aspects: initiation frequency, routing overhead, average end-to-end delay and packet delivery rate by using NS2 simulation software. The simulation results show that the performance of AODV-SP routing protocol proposed in this paper is better than AODV protocol in four aspects: startup frequency, routing overhead, average end-to-end delay and packet delivery rate. When the node moves at a speed of 5 m/s, the routing initiation frequency and routing overhead of AODV-SP are 3.65% and 7.09% lower than those of AODV, and when the node moves at a speed of 8 m/s, AODV-SP. In order to further verify the performance of AODV-SP protocol, a small multi-robot wireless communication physical platform based on pilot following method is built in the laboratory environment, and AODV-SP is applied to this platform, and the static packet loss rate and dynamic test are carried out. The test results show that the static packet loss rate is 0 when the distance between nodes is 25 m, and 21.05438+0% when the distance is 100 m; The robot can maintain the chain topology when driving dynamically. This study can provide reference for the construction of multi-robot communication system in orchard in practical environment.
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[10],, Li,, Yang Xing,,, Sugar Singing. Design and Prospect of Anti-theft and Anti-destruction of Solar Insect-killing Lights in the Internet of Things [J]. Smart Agriculture (in Chinese and English), 202 1, 3 (1): 65438.
Shu Lei, Li, Yang Xing, Wang Xiaochan,. Design and Prospect of Anti-theft and Anti-destruction of Solar Insect-killing Lights in the Internet of Things [J]. Smart Agriculture, 202 1, 3 (1):129-143.
Abstract: Solar insecticidal lamp can effectively control pests and reduce the use of pesticides. With the increase of its deployment, there are more and more reports of theft and destruction, which seriously affects the effect of pest control and causes great economic losses. In order to effectively solve the problem that the nodes of the Internet of Things of solar insecticidal lamps are stolen and damaged, this study takes the Internet of Things of solar insecticidal lamps as an application scenario, designs the hardware of solar insecticidal lamps, and obtains more sensing information. The auxiliary equipment of solar insecticidal lamp-unmanned aerial vehicle insecticidal lamp is put forward, which is used for emergency applications such as deployment, tracking and inspection after being stolen and damaged. More comprehensive information can be obtained to judge the theft and destruction of the Internet of Things node of the solar insecticidal lamp through the above-mentioned hardware level transformation design and the addition of auxiliary equipment. However, considering the short time of theft and destruction, it is not enough to realize fast and accurate judgment only from the hardware level. Therefore, from three aspects of internal hardware, software algorithm and external structure design, this study further discusses six key research issues, namely, the optimal design of equipment anti-theft, the establishment of equipment anti-theft judgment rules, the rapid and accurate judgment of equipment theft and damage, the emergency measures of equipment theft and damage, the prediction and prevention of equipment theft and damage, and the optimal calculation of reducing network data transmission load. Finally, the application of equipment anti-theft technology in the Internet of Things scene of solar insecticidal lamp is prospected.
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