Harnessing the Cloud: A Novel Approach to Smart Solar Plant Monitoring

Mohammad Imran Ali (), Shahi Dost (), Khurram Shehzad Khattak, Muhammad Imran Khan and Riaz Muhammad
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Mohammad Imran Ali: National Center for Big Data & Cloud Computing, University of Engineering and Technology (UET), Peshawar 2023, Pakistan
Shahi Dost: TIB—Leibniz Information Centre for Science and Technology, 30167 Hannover, Germany
Khurram Shehzad Khattak: National Center for Big Data & Cloud Computing, University of Engineering and Technology (UET), Peshawar 2023, Pakistan
Muhammad Imran Khan: Department of Mechanical Engineering, College of Engineering, Prince Mohammad Bin Fahd University, Al-Khobar 34754, Saudi Arabia
Riaz Muhammad: Mechanical Engineering Department, College of Engineering, University of Bahrain, Isa Town Campus, Isa Town 810, Bahrain

Future Internet, 2024, vol. 16, issue 6, 1-22

Abstract: Renewable Energy Sources (RESs) such as hydro, wind, and solar are merging as preferred alternatives to fossil fuels. Among these RESs, solar energy is the most ideal solution; it is gaining extensive interest around the globe. However, due to solar energy’s intermittent nature and sensitivity to environmental parameters (e.g., irradiance, dust, temperature, aging and humidity), real-time solar plant monitoring is imperative. This paper’s contribution is to compare and analyze current IoT trends and propose future research directions. As a result, this will be instrumental in the development of low-cost, real-time, scalable, reliable, and power-optimized solar plant monitoring systems. In this work, a comparative analysis has been performed on proposed solutions using the existing literature. This comparative analysis has been conducted considering five aspects: computer boards, sensors, communication, servers, and architectural paradigms. IoT architectural paradigms employed have been summarized and discussed with respect to communication, application layers, and storage capabilities. To facilitate enhanced IoT-based solar monitoring, an edge computing paradigm has been proposed. Suggestions are presented for the fabrication of edge devices and nodes using optimum compute boards, sensors, and communication modules. Different cloud platforms have been explored, and it was concluded that the public cloud platform Amazon Web Services is the ideal solution. Artificial intelligence-based techniques, methods, and outcomes are presented, which can help in the monitoring, analysis, and management of solar PV systems. As an outcome, this paper can be used to help researchers and academics develop low-cost, real-time, effective, scalable, and reliable solar monitoring systems.

Keywords: solar plant monitoring; industrial internet of things; IoT systems; cyber-physical systems; cloud-based architecture; decentralized architecture; cloud continuum; edge computing (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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