https://doi.org/10.4081/jae.2025.1751
Design and test of wireless monitoring system based on expandable awning composite greenhouse
Published: 25 February 2025
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Authors
Wireless technologies like wireless fidelity (WIFI) and ZigBee have drawbacks such as short communication distances or high-power consumption, and the half-duplex nature of long range (LoRa) communication, traditional solutions generally use time division multiple access (TDMA) or polling communication methods，cannot provide differentiated services. Therefore, based on an extensible awning structure with fans and wet communication protocol combining TDMA and random delayed competitive access random delay competitive access (ALOHA) is proposed, which allows for real-time communication with contention nodes that have high real-time requirements, ensuring no data collisions during communication in static timeslot (TS) nodes, reducing node power consumption, and therefore achieved differentiated services. Practical verification demonstrates that the greenhouse achieves a 100% success rate in long-distance communication with low transmission power consumption. Although the competing node communication has data collision, the success of communication can be guaranteed by retransmission mechanism.
Abreu, F.F., Rodrigues, L.H.A. 2022. Monitoring mini-tomatoes growth: A non-destructive machine vision-based alternative. J. Agric. Eng. 53:1366.
DOI: https://doi.org/10.4081/jae.2022.1366
Cesar, T.Q.Z., Leal, P.A.M., Branquinho, O.C., Miranda, F.A.M. 2021. Wireless sensor network to identify the reduction of meteorological gradients in greenhouse in subtropical conditions. J. Agric. Eng. 52:1155.
Dal Magro, S.Z., Chiomento, J.L.T., Werner, H.A., Bortoluzzi, E.C., Bortoluzzi, M.P. 2024. Enhancing greenhouse strawberry irrigation: integrating IoT technologies and low-cost moisture sensors in substrate. Caderno Pedagógico 21:e7258.
DOI: https://doi.org/10.54033/cadpedv21n8-274
Guo, B., Zhou, B., Zhang, Z., Li, K., Wang, J., Chen, J., Papadakis, G.A. 2024. Critical review of the status of current greenhouse technology in China and development prospects. Appl. Sci. (Basel) 14:5952.
DOI: https://doi.org/10.3390/app14135952
Guo, Q., Li, Y. 2019. Study of environmental supervisory system of north house group. J. Agr. Mech. Res. 31.
Ibrahim, M.F., Isa, M.M., Hussin, R., Zakaria, S.M.M.S., Ahmad, N., Yuan, C.K.J., Abdullah, A.F.T. IoT monitoring system for fig in greenhouse plantation. J. Adv. Res. Appl. Sci. Eng. Tech. 31:298-309.
DOI: https://doi.org/10.37934/araset.31.2.298309
Kathrine C.J.W. 2022. Intelligent system with the IoT: a survey on techniques of artificial intelligence over the field of internet of things. Proc. 8th Int. Conf. on Advanced Computing and Communication Systems (ICACCS), Coimbatore, pp. 347-351.
DOI: https://doi.org/10.1109/ICACCS54159.2022.9785282
Lee, H., Kim, S. 2019. Monitoring urban heat island using remote sensing data. Proc. Int. Conf. on Remote Sensing Applications, Paris. pp. 123-135.
Li, G., Zhou, C., Mou, F. 2022. Design of remote monitoring and control system for agricultural greenhouse environment based on ESP32. J. Chin. Agr. Mech. 43.
Li, L., Zhao, W., Qi, K., Li, Y., Yang, J. 2021. Research on intelligent greenhouse remote monitoring system based on Alibaba cloud. Autom. Instrum. 36.
Liu, B., Wang, L., Wang, W., Zhang, Y. 2021. Construction of intelligent greenhouse monitoring system based on IoT and cloud platform. Microcomp. Appl. 37.
Ou, Y., Ma, C., Hao, Y. 2022. Design of vertical aeroponic farming environment data monitoring system based on LoRa. Chin. J. Electr. Dev. 45.
DOI: https://doi.org/10.1051/itmconf/20224501064
Riskiawan, H.Y., Gupta, N., Setyohadi, D.P.S., Anwar, S., Kurniasari, A.A., Hariono, B., Basori, A.H. 2024. Artificial intelligence enabled smart monitoring and controlling of IoT-green house. Arab. J. Sci. Eng. 49:3043-61.
DOI: https://doi.org/10.1007/s13369-023-07887-6
Rong, R., Xiao, J. 2023. Design and Experiment of fruit and vegetable intelligent greenhouse control system based on ZigBee technology. J. Agr. Mech. Res. 45.
Salih, T.A., Noori, M.S. 2020. Using LoRa technology to monitor and control sensors in the greenhouse. IOP Conf. Ser. Mater. Sci. Eng. 928:032058.
DOI: https://doi.org/10.1088/1757-899X/928/3/032058
Singh, K.A.P., Goutam, P.K., Xaxa, S., Pandey S.K., Panotra, N., Rajesh, G.M. 2024. The role of greenhouse technology in streamlining crop production. J. Exp. Agr. Int. 46:776-98
DOI: https://doi.org/10.9734/jeai/2024/v46i62532
Sumalan, R.L., Stroia, N., Moga, D., Muresan, V., Lodin, A., Vintila, T., Popescu, C.A. 2020. A cost-effective embedded platform for greenhouse environment control and remote monitoring. Agronomy (Basel) 10:936.
DOI: https://doi.org/10.3390/agronomy10070936
Teja, G., Pasika, S. 2020. MQTT protocol based smart greenhouse environment monitoring system using machine learning. Int. J. Innov. Technol. Explor. Eng. 9:278-85.
DOI: https://doi.org/10.35940/ijitee.I7149.079920
Tsakmakis, A., Valkanis, A., Beletsioti, G., Kantelis, K., Nicopolitidis, P., Papadimitriou, G. 2022. An adaptive LoRaWAN MAC protocol for event detection applications. Sensors (Basel) 22:3538.
DOI: https://doi.org/10.3390/s22093538
Wang, C. 2024. Intelligent agricultural greenhouse control system based on internet of things and machine learning. arXiv:2402.09488.
Wang, N. 2024. Design of agricultural greenhouse environment measurement and control system based on LoRa wireless sensor network. Comp. Measur. Contr. 32.
Zhang, J., Zhang, K., Liu, X., Yang, N. 2023. Design and implementation of remote greenhouse visual monitoring system based on Internet of Things. J. Chin. Agric. Mech. 44.
Zhu, Z., Li, Y., Gong, S. 2023. Design and experiment of Internet-of-Things cooling system in glass greenhouse based on computational fluid dynamics simulation. J. Agric. Eng. 54:1384.
DOI: https://doi.org/10.4081/jae.2023.1384
How to Cite
Chen, J., Zhang, T. and Yan, X. (2025) “Design and test of wireless monitoring system based on expandable awning composite greenhouse”, Journal of Agricultural Engineering. doi: 10.4081/jae.2025.1751.
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