1
Department of Computing Technologies, College of Engineering and Technology, Faculty of Engineering and Technology, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai -603203, Tamil Nadu, India
(jn8261@srmist.edu.in)
2
Department of Computing Technologies, College of Engineering and Technology, Faculty of Engineering and Technology, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai -603203, Tamil Nadu, India
(selvarap@srmist.edu.in)
Abstract :
Agricultural use of alternative energy has become more prevalent. Utilizing the alternative source when it is widely accessible is economical and prudent. Drip irrigation may be even more effective when alleviated with renewable energy via a power grid link. Fog computing is a cutting-edge method for extending cloud services to the network's edge. With compute and storage capabilities, it offers a widely dispersed, virtualized platform. Fog could analyze vast volumes of data before sending it to the cloud. This work proposes an innovative agricultural system with integrated hydropower management and its functional blocks. For processing and decision- making in this system, the fog router received field data from the aggregator. To use the data for analysis in the future, it will be stored in the cloud. We have constructed an intelligent irrigation and power management system based on the IoT in our suggested design with IIPMS. This prototype model detects heat and light using temperature and light sensors. If this dual parameter is discovered to be sufficient, the intelligent switch automates the switchover to solar power. The gadget and motor operate on a regular power supply from the power plant. Through GSM technology, the cloud informs the farmer about the type of electricity being used and information linked to power, such as voltage. To inform the farmer of the availability of solar power, a built-in prediction module was also proposed with the Time Series Analysis based forecasting to carry out forecasting duties (TSA). Based on the simulation study, we claimed that the proposed approach performs better in various real-world agricultural scenarios. We also compared our energy consumption model with the existing models and claimed the efficacies of the proposed approach.
Keywords :
Smart Farming; IoT; Fog Computing; Dual Power management
References :
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| Style | # |
|---|---|
| MLA | J. Chandraleka, P. Selvaraj. "Energy-Efficient Smart Farming with IoT-Fog- Based Dual Power Management System." Journal of Cognitive Human-Computer Interaction, Vol. 5, No. 1, 2023 ,PP. 32-41 (Doi : https://doi.org/10.54216/JCHCI.050103) |
| APA | J. Chandraleka, P. Selvaraj. (2023). Energy-Efficient Smart Farming with IoT-Fog- Based Dual Power Management System. Journal of Journal of Cognitive Human-Computer Interaction, 5 ( 1 ), 32-41 (Doi : https://doi.org/10.54216/JCHCI.050103) |
| Chicago | J. Chandraleka, P. Selvaraj. "Energy-Efficient Smart Farming with IoT-Fog- Based Dual Power Management System." Journal of Journal of Cognitive Human-Computer Interaction, 5 no. 1 (2023): 32-41 (Doi : https://doi.org/10.54216/JCHCI.050103) |
| Harvard | J. Chandraleka, P. Selvaraj. (2023). Energy-Efficient Smart Farming with IoT-Fog- Based Dual Power Management System. Journal of Journal of Cognitive Human-Computer Interaction, 5 ( 1 ), 32-41 (Doi : https://doi.org/10.54216/JCHCI.050103) |
| Vancouver | J. Chandraleka, P. Selvaraj. Energy-Efficient Smart Farming with IoT-Fog- Based Dual Power Management System. Journal of Journal of Cognitive Human-Computer Interaction, (2023); 5 ( 1 ): 32-41 (Doi : https://doi.org/10.54216/JCHCI.050103) |
| IEEE | J. Chandraleka, P. Selvaraj, Energy-Efficient Smart Farming with IoT-Fog- Based Dual Power Management System, Journal of Journal of Cognitive Human-Computer Interaction, Vol. 5 , No. 1 , (2023) : 32-41 (Doi : https://doi.org/10.54216/JCHCI.050103) |