Development of Cloud-Dust Based Intelligent Maximum Power Analysis System for Photovoltaic

Abstract

In the paper, a cloud-dust based intelligent maximum power analysis system for photovoltaic is proposed. In order to resolve NP problem for photovoltaic, factors of photovoltaic are integrated to cloud-dust based intelligent maximum power analysis system for computing. This study is the development of the maximum power analysis system for photovoltaic, to improve the solar panels effects of the different region and enable them to get maximum efficiency of the power generation. The design methodology of this study includes: (1) The monitoring and control Module (2) The prediction and evaluation module (3) The performance diagnosis module (4) The maintenance prescription module. At last, we can find the advantages of the cloud-dust based intelligent maximum power analysis system for photovoltaic. It increases overall competitive performance of products, reduces cost of products and consummation rates of human resources.

RUbIn: A Framework for Reliable and Ubiquitous Inference in WSNs

“…These advantages provide WSNs with the ability of intelligence, which ensures their deployment as networked embedded systems in smart applications [1]. Development of IoT applications brings a new movement to the functionality of WSNs from only environment sensing and data gath-ering to collaborative inferring and ubiquitous intelligence [2][3][4][5]. The di culty of perceiving the constraints on the resources of nodes and the complexities brought by these constraints to application development should not be a barrier for the development of WSN/IoT applications.…”