Internet of Things (IOT) Based Machine Learning Techniques for Wind Energy Harvesting

Abstract

The Internet of Things (IoT) is a significant avenue for research in renewable energy, particularly in enhancing windmill performance, reducing wind energy costs, and mitigating risks in wind power. This article concentrates on leveraging IoT for assessing wind and solar energy, as well as estimating module lifespans. IoT has improved assessment methods, monitoring precision, and product testing, influencing power network reliability and inventory management in green energy. Predicting green energy output is crucial but challenging due to wind speed fluctuations. Machine learning (ML) techniques are applied to predict wind-based electricity output, with a comparative evaluation of forecasting methods. IoT technologies and algorithms enable energy consumption forecasts, yielding more accurate predictions and lower root mean square error (RMSE). Accurate meteorological forecasts are paramount in the green energy sector, necessitating predictive models for authentic wind generator data. The research aims to develop technologies for precise forecasts, with a focus on comprehensive wind forecast algorithms for photovoltaic systems. Various ML techniques and green energy prediction software are assessed for their accuracy in this endeavor.

Keywords:

• Internet of Things
• machine learning
• forecasting
• wind energy

ACKNOWLEDGMENT

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University Abha 61421, Asir, Kingdom of Saudi Arabia for funding this work through the Large Groups Project under grant number RGP.2/9/43.

AUTHORSHIP CONTRIBUTIONS

All authors are contributed equally to this work.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

No participation of humans takes place in this implementation process

HUMAN AND ANIMAL RIGHTS

No violation of Human and Animal Rights is involved.

DATA AVAILABILITY STATEMENT

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study

DISCLOSURE STATEMENT

Conflict of interest is not applicable in this work.

Additional information

Funding

No funding is involved in this work. The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University Abha 61421, Asir, Kingdom of Saudi Arabia for funding this work through the Large Groups Project under grant number RGP.2/9/43.

Notes on contributors

R. Kalpana

R. Kalpana received B.E. and M.E. degrees from Madras University and Sathyabama University in 1991 and 2006 respectively and Ph.D. degree from Anna University Chennai, in 2013, all in Computer Science and Engineering. She is working as a Professor in Computer Science and Engineering department in Madanapalle Institute of Technology & Science, Madanapalle Andhra Prades, India. Her research interests include Network Security, Wireless Networks, Adhoc Networks and Databases.

Subburaj V

V. Subburaj MCA., M.Phil., M.E., Ph.D, Currently working as professor in Dept of CSE, VEMU Institute of Technology, Chittoor, Andhrapradesh. Earlier served as Director in Dept of MCA at VVV College for Women, Virudhunagar, Tamilnadu. He has around 15 years of experience in academics and 4 years of experience in IT industry. He has around 120 articles in the form of conference, articles and journals in both national and international publication. He has solid number in both national and international patents in his name and a reputed trainer in AI, Data science, mobile and cloud apps development.

R. Lokanadham

R. Lokanadham Professor in Mechanical Engineering, Narsimha Reddy Engineering College, Hyderabad, obtained his Ph.D., from Sri Venkateswara University, Tirupati. He has more than 30 years of experience in teaching. He has published 20 papers in reputed journals. He organized National and International conferences and acted as chair for technical programs. His areas of interest are IC Engines, Renewable Sources of Energy etc., He has membership in various professional bodies like ISTE, IAENG etc.,

K. Amudha

K. Amudha received BE degree Electronics and Communication Engineering in the year 2005 in Mahendra Engineering College and ME degree Applied Electronics in Kongu Engineering College in the year 2007 and she completed PhD degree in the year 2017 under Information and Communication Engineering in Anna University, Chennai. She has 17 years of experience in teaching. Currently, she is working as a professor in the department of Electronics and Communication Engineering at Kongunadu College of Engineering and Technology, Trichy. She has published more than 40 papers in international journals and conferences and filed 4 patents. Her research interest includes Image recognition, Medical image security and Network Security. She is a life member of ISTE and IETE.

G. N. Beena Bethel

G. N. Beena Bethel is working as Professor in the Department of Computer Science and Engineering at Gokaraju Rangaraju Institute of Engineering and Technology for the past 13 years out of 20 years of her teaching experience. She has done her BTech(CSE), MTech(CSE) and PhD from Jawaharlal Nehru Technological University, Hyderabad. She has 2 patents and had published several research papers in reputed Journals indexed by Scopus, SCIE and WoS and conferences indexed by Scopus. Her area of interest includes Datamining, Machine Learning, Image Processing, Data Analytics, Software Engineering and Blockchain Technology. She has received Best Teacher’s Award and Best Researcher’s Award from various recognized organizations. She is an active member of IEI and IAENG.

Arvind Kumar Shukla

Arvind Kumar Shukla has an experience of more than 18 years in teaching and Industry field. Currently, He is working as Associate Professor & HoD at Department of Computer Applications, IFTM University, Moradabad. He has got is Ph.D. Computer Science from Banasthali Vidyapith Rajasthan. He published more than 40 research papers in various reputed national/International Journals. Dr. Shukla has associated with Banasthali University, Rajasthan . Dr. Shukla has consistory been active member of Academic Council, Executive Council,Board of Studies, Research Degree Committee of IFTM University, oradabad. Dr. Shukla has supervised the M.tech dissertati Ph.D thesis of 10 Students.

Pravin R. Kshirsagar

Pravin R. Kshirsagar presently serving as a Professor in Department of artificial Intelligence at G. H Raisoni College of Engineering, Nagpur, India. Previously, he served as a Vice Principal, Dean R&D, Head-ETC in the in prominent Institute of India. He has vast experience of 18 years in teaching. He has served as reviewer in many international journals such as Inderscience, Spinger, Elsevier and IEEE Transaction. He has also delivered special talks in National & International conferences and chaired various technical sessions in International conferences. He has published various research papers in reputed journals. He has published more than 80 Papers in National & International levels. He has 6 books in his credential. He is profoundly engrossed in the area of Data Science, Machine Learning, Artificial Intelligence, and Computer Networks.

A. Rajaram

A. Rajaram received the B.E. degree in Electronics and Communication Engineering from the Government, College of Technology, Coimbatore, Anna University, Chennai, India, in 2006, the M.E. degree in Applied Electronics from the Government College of Technology, Anna University, Chennai, India, in 2008 and he received the Full Time Ph.D. degree in Electronics and Communication Engineering from the Anna University of Technology, Coimbatore, India in March 2011. He is currently working as a professor in Department of Electronics and Communication Engineering, E.G.S Pillay Engineering College, Nagapattinam. His research interests include Mobile Ad Hoc networks, wireless communication networks (WiFi, WiMax HighSlot GSM), novel VLSI NoC Design approaches to address issues such as low-power, cross-talk, hardware acceleration, Design issues includes OFDM MIMO and noise Suppression in MAI Systems, ASIC design, Control systems, Fuzzy logic and Networks, AI, Sensor Networks.