A hybrid artificial intelligence and Internet of Things model for generation of renewable resource of energy
Open accessAbstract
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.
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Puri et al.'s AIoT system, using ANN and ANFIS models, produced accurate results in predicting the power generated from renewable resources.
“The authors built and validated the data collected from the sensors with ANN and ANFIS models to predict generated power output and demonstrated that their system could produce accurate results in predicting the power generated from renewable resources.”
From Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2024) · cites this paper as [16]
An AIoT system developed by Puri et al. generates energy from different sensors, such as piezoelectric sensors, including from stress caused by human body weight, heat generated by the movement of the human body, and sunlight.
“An AIoT system developed by Puri et al. [16] generates energy from different sensors, such as piezoelectric sensors, including from stress caused by human body weight, heat generated by the movement of the human body, and sunlight.”
From Smarter eco-cities and their leading-edge artificial intelligence of things solutions for environmental sustainability: A comprehensive systematic review (2024) · cites this paper as [16]
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- Authors
- Puri, V., Jha, S., Kumar, R., Priyadarshini, I., Hoang Son, L., Abdel-Basset, M., Elhoseny, M., & Viet Long, H.
- Affiliations
- Duy Tan University (VN)
- KIIT University (IN)
- University of Delaware (US)
- Zagazig University (EG)
- Mansoura University (EG)
- ORCID
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 111181-111191
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2967468707
- Cited by
- 154
- References
- 55
- Citations by year
- 2026: 10 · 2025: 19 · 2024: 19 · 2023: 16 · 2022: 23 · 2021: 49 · 2020: 16 · 2019: 2
- FWCI
- 12.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Greater South Information System
- Topics
- Physical Sciences › Engineering › Mechanical Engineering › Innovative Energy Harvesting Technologies
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
- Keywords
- renewable energy generation, Internet of Things, piezoelectric sensors, solar panels, artificial neural networks, adaptive neuro-fuzzy inference system, hybrid AI models, household energy supply, industrial energy supply
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