# Harnessing the Cloud: A Novel Approach to Smart Solar Plant Monitoring
###### 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. solar plant monitoring; industrial internet of things; IoT systems; cyber-physical systems; cloud-based architecture; decentralized architecture; cloud continuum; edge computing +
Footnote †: journal: _Future Internet_  
solutions for sustainable energy generation. According to an International Energy Agency (IEA) report, 28% of the world's energy demand will be met by renewable sources by 2021 [3]. Among RESs, solar energy has emerged as the cleanest, cost-effective, efficient, and reliable solution. Moreover, its most prominent feature is its ubiquitous presence and sharply falling costs with technological advancements. In 90 min, enough sunlight strikes the earth's surface to provide the entire world's energy demand for one whole year. Over the last decade, equipment cost has dropped 60% from USD 2/watt to USD 0.2/watt [4]. Solar energy can play a vital role in filling electricity demand gaps without having the danger of GHG emissions. With the exponential increase in installed solar capacity, the need for more accurate, low-cost monitoring and performance prediction systems has become imperative. With advancements in technology, IoT (Internet of Things)-based solar plant monitoring systems are increasingly becoming viable [5]. Such IoT-based systems are instrumental in optimizing solar plants' performance through predictive diagnosis and performance evaluation, thus mitigating unwanted power disruptions. Salient features for employing such systems are mentioned as:  
1. Monitoring of solar plants installed in remote and hard-to-reach areas. Manual monitoring of solar plants in such areas is expensive, both in terms of cost and manpower needed. 2. A solar plant's performance is highly dependent on meteorological parameters (such as solar irradiance, ambient temperature, sunlight spectrum, and dust particles), resulting in unexpected power fluctuations [6; 7]. 3. In [8], it has been reported that about 14% of solar panels develop a major fault within a year of operations. Therefore, panel-level monitoring in real time can help in undertaking in-time diagnostics, evaluation, and performance enhancement strategies [9; 10]. 4.