Abstract
Smart agriculture is an emerging concept that helps modern farm management using technologies such as the Internet of Things (IoT), robotics, drones, and artificial intelligence, so that this leads to an increase in the quantity and quality of farm products and optimization of human resources. Efforts have been made in the past to control pests and plant diseases, and this has led to an increase in agricultural products. Control and prevention of crop diseases is the least expensive method of pest control, which also has good results in reducing insect pests. This study develops a crop pest control system based on IoT technology, which includes two parts: (1) hardware as a plant protection machine, and (2) software as an information management system. Here, light trap technology and ozone sterilization are incorporated in the proposed system to control insect pests and diseases of agricultural crops. The information management system consists of IoT technology and a mobile app, which provides remote control capability. In this system, several IoT-based sensor devices are responsible for collecting environmental information in real time. The basic routing protocol for the system implementation is Open Shortest Path First . We present a fuzzy logic-based method for energy-aware routing. We proved the effectiveness of the proposed system through implementation on a greenhouse facility.
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References
Dong, Y., Xu, F., Liu, L., Du, X., Ren, B., Guo, A., & Zhu, Y. (2020). Automatic system for crop pest and disease dynamic monitoring and early forecasting. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 4410–4418.
Wang, L., She, A., & Xie, Y. (2023). The dynamics analysis of Gompertz virus disease model under impulsive control. Scientific Reports, 13(1), 10180.
Cao, Y., Niu, B., Wang, H., & Zhao, X. (2024). Event‐based adaptive resilient control for networked nonlinear systems against unknown deception attacks and actuator saturation. International Journal of Robust and Nonlinear Control. https://doi.org/10.1002/rnc.7231
Wang, S., Qi, P., Zhang, W., & He, X. (2022). Development and application of an intelligent plant protection monitoring system. Agronomy, 12(5), 1046.
Salimian, M., Ghobaei-Arani, M., & Shahidinejad, A. (2021). Toward an autonomic approach for internet of things service placement using gray wolf optimization in the fog computing environment. Software Practice and Experience, 51(8), 1745–1772.
Khayatnezhad, M., Fataei, E., & Imani, A. (2023). Integrated modeling of food–water–energy nexus for maximizing water productivity. Water Supply, 23(3), 1362–1374.
Zhao, J., Sun, M., Pan, Z., Liu, B., Ostadhassan, M., & Hu, Q. (2022). Effects of pore connectivity and water saturation on matrix permeability of deep gas shale. Advances in Geo-Energy Research, 6(1), 54–68.
Wu, C., Zhang, Y., Li, N., & Rezaeipanah, A. (2023). An intelligent fuzzy-based routing algorithm for video conferencing service provisioning in software defined networking. Telecommunication Systems. https://doi.org/10.1007/s11235-023-01044-y
Li, Q. K., Lin, H., Tan, X., & Du, S. (2018). H∞ consensus for multiagent-based supply chain systems under switching topology and uncertain demands. IEEE Transactions on Systems, Man, and Cybernetics Systems, 50(12), 4905–4918.
Zhao, H., Zong, G., Wang, H., Zhao, X., & Xu, N. (2023). Zero-sum game-based hierarchical sliding-mode fault-tolerant tracking control for interconnected nonlinear systems via adaptive critic design. IEEE Transactions on Automation Science and Engineering. https://doi.org/10.1109/TASE.2023.3317902
Huang, S., Zong, G., Zhao, N., Zhao, X., & Ahmad, A. M. (2024). Performance recovery-based fuzzy robust control of networked nonlinear systems against actuator fault: A deferred actuator-switching method. Fuzzy Sets and Systems, 480, 108858.
Guo, H., Gu, W., Khayatnezhad, M., & Ghadimi, N. (2022). Parameter extraction of the SOFC mathematical model based on fractional order version of dragonfly algorithm. International Journal of Hydrogen Energy, 47(57), 24059–24068.
Szumigaj-Tarnowska, J., Szafranek, P., Uliński, Z., & Ślusarski, C. (2020). Efficiency of gaseous ozone in disinfection of mushroom growing rooms. Journal of Horticultural Research, 28(2), 91–100.
Fujiwara, K., & Fujii, T. (2002). Effects of spraying ozonated water on the severity of powdery mildew infection on cucumber leaves. Ozone Science Engineering, 24(6), 463–469.
Díaz-López, M., Siles, J. A., Ros, C., Bastida, F., & Nicolás, E. (2022). The effects of ozone treatments on the agro-physiological parameters of tomato plants and the soil microbial community. Science of the Total Environment, 812, 151429.
Landa Fernández, I. A., Monje-Ramirez, I., Ledesma, O., & de Velásquez, M. T. (2019). Tomato crop improvement using ozone disinfection of irrigation water. Ozone Science Engineering, 41(5), 398–403.
Etemadi, M., Ghobaei-Arani, M., & Shahidinejad, A. (2021). A cost-efficient auto-scaling mechanism for IoT applications in fog computing environment: A deep learning-based approach. Cluster Computing, 24(4), 3277–3292.
Zhao, H., Wang, H., Xu, N., Zhao, X., & Sharaf, S. (2023). Fuzzy approximation-based optimal consensus control for nonlinear multiagent systems via adaptive dynamic programming. Neurocomputing, 553, 126529.
Wu, W., Zhang, L., Wu, Y., & Zhao, H. (2024). Adaptive saturated two-bit-triggered bipartite consensus control for networked MASs with periodic disturbances: a low-computation method. IMA Journal of Mathematical Control and Information. https://doi.org/10.1093/imamci/dnae002
Zhao, Y., Liang, H., Zong, G., & Wang, H. (2023). Event-based distributed finite-horizon H∞ consensus control for constrained nonlinear multiagent systems. IEEE Systems Journal. https://doi.org/10.1109/JSYST.2023.3318525
Zhao, H., Zong, G., Zhao, X., Wang, H., Xu, N., & Zhao, N. (2023). Hierarchical sliding-mode surface-based adaptive critic tracking control for nonlinear multiplayer zero-sum games via generalized fuzzy hyperbolic models. IEEE Transactions on Fuzzy Systems, 31(11), 4010–4023.
Tu, H., Tang, N., Hu, X., Yao, Z., Wang, G., & Wei, H. (2016). LED multispectral circulation solar insecticidal lamp application in rice field. Transactions of the Chinese Society of Agricultural Engineering, 32(16), 193–197.
Bian, L., Cai, X. M., Luo, Z. X., Li, Z. Q., & Chen, Z. M. (2018). Decreased capture of natural enemies of pests in light traps with light-emitting diode technology. Annals of Applied Biology, 173(3), 251–260.
de Carvalho, M. W., Hickel, E. R., Bertoldi, B., Knabben, G. C., & Novaes, Y. R. D. (2021). Design of a smart LED lamp to monitor insect populations in an integrated pest management approach. Revista Brasileira de Engenharia Agrícola e Ambiental, 25, 270–276.
Wang, H., Ren, H., Han, K., Li, G., Zhang, L., Zhao, Y., & Liu, P. (2023). Improving the net energy and energy utilization efficiency of maize production systems in the North China plain. Energy, 274, 127340.
Lam, H. B., Phan, T. T., Vuong, L. H., Huynh, H. X., & Pottier, B. (2013). Designing a brown planthoppers surveillance network based on wireless sensor network approach. arXiv preprint arXiv:1312.3692.
Wang, T., Zhang, L., Xu, N., & Alharbi, K. H. (2023). Adaptive critic learning for approximate optimal event-triggered tracking control of nonlinear systems with prescribed performances. International Journal of Control. https://doi.org/10.1080/00207179.2023.2250880
Berahmand, K., Mohammadi, M., Sheikhpour, R., Li, Y., & Xu, Y. (2023). WSNMF: Weighted symmetric nonnegative matrix factorization for attributed graph clustering. Neurocomputing, 566, 127041.
Gao, D., Sun, Q., Hu, B., & Zhang, S. (2020). A framework for agricultural pest and disease monitoring based on Internet-of-Things and unmanned aerial vehicles. Sensors, 20(5), 1487.
Li, L., & Yao, L. (2023). Fault tolerant control of fuzzy stochastic distribution Systems with packet dropout and time delay. IEEE Transactions on Automation Science and Engineering. https://doi.org/10.1109/TASE.2023.3266065
Zhong, Y., Chen, L., Dan, C., & Rezaeipanah, A. (2022). A systematic survey of data mining and big data analysis in internet of things. The Journal of Supercomputing, 78(17), 18405–18453.
Cao, C., Wang, J., Kwok, D., Cui, F., Zhang, Z., Zhao, D., & Zou, Q. (2022). webTWAS: A resource for disease candidate susceptibility genes identified by transcriptome-wide association study. Nucleic Acids Research, 50(D1), D1123–D1130.
Yue, S., Niu, B., Wang, H., Zhang, L., & Ahmad, A. M. (2023). Hierarchical sliding mode-based adaptive fuzzy control for uncertain switched under-actuated nonlinear systems with input saturation and dead-zone. Robotic Intelligence and Automation, 43(5), 523–536.
Jannesari, V., Keshvari, M., & Berahmand, K. (2023). A novel nonnegative matrix factorization-based model for attributed graph clustering by incorporating complementary information. Expert Systems with Applications, 242, 122799.
Luo, J., Zhao, C., Chen, Q., & Li, G. (2022). Using deep belief network to construct the agricultural information system based on Internet of Things. The Journal of Supercomputing, 78(1), 379–405.
Zhang, H., Zou, Q., Ju, Y., Song, C., & Chen, D. (2022). Distance-based support vector machine to predict DNA N6-methyladenine modification. Current Bioinformatics, 17(5), 473–482.
Gong, J., & Rezaeipanah, A. (2023). A fuzzy delay-bandwidth guaranteed routing algorithm for video conferencing services over SDN networks. Multimedia Tools and Applications, 82, 25585–25614.
Cao, Y., Xu, N., Wang, H., Zhao, X., & Ahmad, A. M. (2023). Neural networks-based adaptive tracking control for full-state constrained switched nonlinear systems with periodic disturbances and actuator saturation. International Journal of Systems Science, 54(14), 2689–2704.
Xue, B., Yang, Q., Xia, K., Li, Z., Chen, G. Y., Zhang, D., & Zhou, X. (2022). An AuNPs/mesoporous NiO/nickel foam nanocomposite as a miniaturized electrode for heavy metal detection in groundwater. Engineering. https://doi.org/10.1016/j.eng.2022.06.005
Zhang, J., Khayatnezhad, M., & Ghadimi, N. (2022). Optimal model evaluation of the proton-exchange membrane fuel cells based on deep learning and modified African vulture optimization algorithm. Energy Sources Part A Recovery Utilization and Environmental Effects, 44(1), 287–305.
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Wang, X., Jannesari, V. Towards a crop pest control system based on the Internet of Things and fuzzy logic. Telecommun Syst 85, 665–677 (2024). https://doi.org/10.1007/s11235-024-01106-9
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DOI: https://doi.org/10.1007/s11235-024-01106-9