Internet of Things for the Future of Smart Farming – Prof. L. P. Saikia
Emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software-defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. Classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. A brief idea about agricultural IoTs is being tried here to give.; highlighting open research challenges and possible future research directions for agricultural IoTs.
The four agricultural revolutions.
PHOTOVOLTAIC PANEL CLEANING AND COMPREHENSIVE UTILIZATION OF WATER RESOURCES.
According to the amount of dust accumulation, photovoltaic panels need to be cleaned in time to ensure power generation efficiency. Meanwhile, sufficient water supply is also necessary for the whole process of agricultural production to ensure soil moisture. The combination of both panel cleaning and crops irrigation (Fig. 6) can effectively improve the water resources utilization rate. In PA, the conditions for photovoltaic panel cleaning are inconsistent with the conditions for crops irrigation and livestock farm cleaning. For simplicity, most times of the day, the cleaning frequency of the panels is not synchronized with the frequency of crops irrigation and livestock farm cleaning. Note that the internet of things technology can effectively solve this problem by taking the following factors into consideration, e.g., cleaning time of the day, cleaning frequency, different water requirements in different growth stages of the crop, different water requirements of different species of crop, soil moisture, and so on. In the PAIoT, the status of photovoltaic panel power generation is monitored to
make the judgment whether to clean the panels, and the amount of irrigation water is determined based on the situation of agricultural production, both of which are considered to choose a proper time for the cleaning and the irrigation. And these intelligent cleaning tasks will be finished by the cleaning robots with high efficiency.
Intelligent cleaning and intelligent utilization of water resources.
Fault diagnosis of the photovoltaic module.
FAULT DIAGNOSIS OF PHOTOVOLTAIC MODULE AND SENSORS IN AGRICULTURAL PRODUCTION.
With the faults of the photovoltaic module being accurately detected and identified, the technology, i.e., fault diagnosis will provide effective support for the stable operation of the Photovoltaic Agricultural Internet of Things (PAIoT fig. above), especially the power grid maintenance, further providing a basis for solving the security and safety problems in PAIoT. We observed that there are three common sources of photovoltaic module faults as follows:
- Shadow: temporary shadows (e.g., snow, fallen leaves, birds.), site shadow (e.g., terrain, trees.), architectural shadows(e.g., building construction, electric towers.), and self shadow
(e.g., photovoltaic component shadow, other device shadows.);
- Equipment aging: external high temperatures cause device aging or performance degradation; the performance of photovoltaic modules is inconsistent, causing Hot Spots and
accelerating aging; the system is limited by photovoltaic components under poor working conditions; the lack of reverse-control for the equipment;
- Line damage: electrical faults (e.g., lightning strike, fuse blow.), other (e.g., intentional attack from human and animal.).
Meanwhile, the effect of the security and safety problems caused by the above-mentioned faults and sensors faults of agricultural production in PAIoT maybe not be obvious in the short term, particularly in agricultural production where the crop can perform some tolerance to the improper environmental conditions, yet leading to the severe yield reduction after a long time in the future. Then, we observed that every challenge posed for researchers needs to be considered seriously while developing novel faults diagnosis technology in PAIoT. Through the analysis of the above complicated key issues, the PAIoT needs to face more challenges than PA. It also means that the PAIoT can efficiently cope with the actual production, further greatly promoting the development of smart farming in the future.
Conclusion: With the reduction of photovoltaic panel manufacturing costs and the improvement of photoelectric conversion efficiency, PA has developed rapidly and has good application prospects,
increasing the income of agricultural production while solving the problem of energy shortage. This paper briefly introduces the current application of PA, and a new agricultural Internet of Things, i.e., PAIoT, is proposed with the combination of both PA and IoT technology. Through the analysis of key issues that concern feasibility of PAIoT (i.e., photovoltaic panel cleaning and comprehensive utilization of water resources, node deployment and cost optimization for sensor networks for multi-function and multi-monitoring standards, transmission optimization of image data acquisition, the influence of photovoltaic panel power generation on the environmental climate, and fault diagnosis of photovoltaic
module.), we can know how to better realize the PAIoT, further improving the level of agricultural informatization and promoting the continuous upgrading of agriculture, which is also the typical application of “smart farming”.
References:
- Friha et. al, “Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies” IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 8, NO. 4, APRIL 2021 pp 718-752
- KAI HUANG, LEI SHU, “Photovoltaic Agricultural Internet of Things towards Realizing the Next Generation of Smart Farming”, IEEE TRANSACTIONS and JOURNALS, 2017
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Author’s Name & contact no.
Prof.(Dr.) Lakshmi Prasad Saikia
Professor in CSE Department. Email: lp_saikia@yahoo.co.in /lps_cse@gimt-guwahati.ac.in
GIMT-Guwahati (ASTU) Ph.: 9854040442(M)
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