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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM59757
Volume:
10 |
4 |
April 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
EEE
Vimal Jyothi Engineering College, Chemperi, Kannur, India
EEE
Vimal Jyothi Engineering College, Chemperi, Kannur, India
EEE
Vimal Jyothi Engineering College, Chemperi, Kannur, India
EEE
Vimal Jyothi Engineering College, Chemperi, Kannur, India
EEE
Vimal Jyothi Engineering College, Chemperi, Kannur, India
EEE
Vimal Jyothi Engineering College, Chemperi, Kannur, India
The AI-Powered Smart Distribution Board is designed to address critical inefficiencies in conventional electrical systems, such as load imbalance, low power factor, and the absence of real-time monitoring. By integrating artificial intelligence and automation, the system provides advanced energy management features. The primary functions include predicting electrical load demand using AI-based forecasting, which is crucial for optimized energy management. It automatically balances phase loads through intelligent switching mechanisms using relays or contactors. Power quality is improved, and energy costs are reduced by integrating capacitor banks for automated power factor correction. Furthermore, the system incorporates an IoT-enabled, real-time dashboard that facilitates remote monitoring, control, and fault alerts, significantly enhancing operational reliability and efficiency. This innovative solution is scalable, promotes sustainable energy practices, and is ideal for modern residential and commercial applications.
KEYWORDS
The AI-Powered Smart Distribution Board successfully proposes a comprehensive solution to overcome the limitations of conventional electrical distribution systems. By leveraging Artificial Intelligence and IoT, the system provides automatic load balancing, dynamic power factor correction, and real-time remote monitoring. These objectives ensure enhanced system efficiency, greater reliability, and substantial energy cost savings, positioning it as a viable and sustainable energy management solution for the future. The implementation of automated control mechanisms including capacitor banks and relay-based load switching enables timely corrective actions. The integration of cloud connectivity and mobile/web dashboard allows operators to monitor remotely and receive instant alerts, thereby improving operational efficiency and reducing manual effort. Overall, the proposed system provides a cost-effective, scalable, and user-friendly approach to electrical distribution management. It enhances productivity, optimizes resource utilization, and supports sustainable energy practices. By leveraging IoT and smart AI technologies, this system offers a practical solution advancing intelligent energy infrastructure.
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Publication Date
7/15/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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