A Hybrid Artificial Intelligence and Internet of Things Model for Generation of Renewable Resource of Energy

IEEE Access

Vikram Puri¹  Raghvendra Kumar²  Ishaani Priyadarshini³  Mohamed Abdel-Basset⁴  Hoang Viet Long⁵  Mohamed Elhoseny⁶  Sudan Jha⁷  Le Hoang Son⁸ 

[1] Center for Visualization and Simulation, Duy Tan University, Da Nang, Vietnam;Department of Computer Science and Engineering, LNCT College, Jabalpur, India;Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, USA;Department of Operations Research, Faculty of Computers and Informatics, Zagazig University, Zagazig, Egypt;Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam;Faculty of Computers and Information, Mansoura University, Dakahlia, Egypt;School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India;VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam;

关键词: Internet of Things;    artificial intelligence;    piezoelectricity;    sensors;    energy types;    human body heat dissipation;   

DOI  :  10.1109/ACCESS.2019.2934228

来源: DOAJ

【 摘 要 】

The world is consuming large amounts of energy in various forms like electric energy and mechanical energy. Since the electrical energy is an important factor for the development of the world, many researchers tried to generate electricity from renewable energy sources collected by sensors in order to overcome the shortage of electrical energy for household appliances and industrial areas. In this paper, we develop Internet-of-Things (IoT) based system to generate electrical energy from multiple sensors for household appliances and industrial areas. Different sensors namely piezoelectric sensor, body heat to electric converter and solar panel are utilized and connected to the power storage circuit for generation of electrical energy. Two different Artificial Intelligence (AI) models such as Artificial Neural Network (ANN), Adaptive Network based Fuzzy Inference System (ANFIS) are utilized for the total power generated from renewable energy resources. Validation is done through the statistical parameters such as Root Mean Square Error (RMSE) and R2 coefficient of correlation. Result outcome from the models shows that ANN performance is better than ANFIS.

【 授权许可】

Unknown