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It is generally agreed that solar energy, which can be converted into usable electricity by means of solar panels, is one of the most important renewable energy sources. An energy and exergy study of these panels is the first step in developing this technology. This will provide a fair standard by which solar panel efficiency can be evaluated. In this study, the MATLAB tool was used to find the answers to the math problems that describe this system. The system’s efficiency has been calculated using the modeled data created in MATLAB. When solving equations, the initial value of the independent system parameters is fed into the computer in accordance with the algorithm of the program. A simulation and a parametric analysis of a thermal PV system with a sheet and spiral tube configuration have been completed. Simulations based on a numerical model have been run to determine where precisely the sheet and helical tubes should be placed in a PV/T system configured for cold water. Since then, the MATLAB code for the proposed model has been developed, and it agrees well with the experimental data. There is an RMSE of 0.94 for this model. The results indicate that the modeled sample achieves a thermal efficiency of between 43% and 52% and an electrical efficiency of between 11% and 11.5%.

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In mobile nodes in the network, they are unstable, so single-path communication does not provide sufficient results. In the alternative single path, communication is very difficult to handle the heavy load. The poor connectivity among the mobile node makes the uncertainty of packet loss; the path link is not measured in this network. The communication cost is also focused to achieve valid packet transmission. Because the high distance path selected for packet transmission causes a high cost for communication. It increases energy consumption and packet loss rate. So, the proposed dispersed path selection for communication (DPAC) method is constructed to obtain the best minimum distance routing path, this path operates with the help of queue variation that handled the data packet’s maintenance, and the time slot exceeds its limit. Packets are kept waiting, to increase the packet broadcasting efficiency. The multipath jamming detection algorithm is constructed to provide link-based path packet overload detection scheme to identify the packet overload. Also, separate the path based on its characteristics, to control overload. It reduces energy consumption and packet loss rate.

The Wireless Sensor Network is a network formed in areas human beings cannot access. The data need to be sensed by the sensor and transferred to the sink node. Many routing protocols are designed to route data from a single node to the sink node. One of the routing protocols is the hierarchical routing protocol, which passes on the sensed data hierarchically. The Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the hierarchical methods in which communication happens in two steps: the setup phase and the steady-state phase. The efficiency of the LEACH has to be optimized to improve the network lifetime. Therefore, the k-means clustering algorithm, which comes under the unsupervised machine learning method, is incorporated with the LEACH algorithm and has shown better results. But the selection of cluster head needs to improvise because it will transfer the summed-up data to the sink node, so it is to be efficient enough. So, this paper proposes the modified k-means algorithm with LEACH protocol for optimizing the Wireless Sensor Network. In the modified k-means algorithm, the weight of the cluster head is tested and elected, and the clusters are formed using the Euclidean distance formula. The proposed work yields 48.85% efficiency compared to the existing protocol. It is also proven that the proposed work showed more successful data transfer to the sink node. The cluster head selection process elects the more efficient node as the head with less failure rate. The proposed work optimistically balanced the whole network in terms of energy and successful data transfer.