International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | IOT Based Underground Power Transmission Cable Fault Detection with Data Logging |
|---|---|
| ABSTRACT | Underground power transmission cables play a vital role in modern electrical distribution systems, particularly in urban and industrial areas where safety, reliability, and efficient land usage are critical. Although underground cables offer several advantages over overhead lines, locating and identifying faults in such cables remains a complex and time-consuming task due to their inaccessibility. Conventional fault detection techniques often depend on manual testing, skilled labor, and repeated excavation, which lead to increased maintenance costs, extended power outages, and inconvenience to consumers. To address these challenges, this project proposes an IoT-based underground power transmission cable fault detection system with data logging that enables automated, real-time monitoring of cable conditions. The proposed system continuously monitors key electrical parameters such as voltage and current using appropriate sensors connected to a microcontroller. These parameters are analyzed using predefined threshold values to detect abnormal operating conditions associated with cable faults. When a fault occurs, the system identifies the fault type and estimates its approximate location along the cable. The detected fault information is then transmitted to a cloud platform through IoT communication, allowing remote access and monitoring. In addition to real-time fault notification, the system records all fault events in a cloud database, enabling data logging and historical analysis of cable performance The data logging feature supports effective maintenance planning by providing insights into fault frequency, recurring failure locations, and long-term cable behavior. The system is designed to be simple, cost-effective, and reliable, making it suitable for practical deployment in underground power distribution networks. Experimental evaluation demonstrates that the proposed system reduces fault detection time, minimizes manual intervention, and improves overall system reliability. By combining embedded sensing with IoT-based monitoring, the project offers an efficient and scalable solution for enhancing the management and maintenance of underground power transmission systems without relying on artificial intelligence or complex learning algorithms. |
| AUTHOR | PROF. SEEMA B S, VARSHA R, SHA FAZAL, YASHAVANTHA N Department of Electronics Communication and Engineering, Dr. Ambedkar Institute of Technology, Bengaluru, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312051 |
| pdf/51_IOT Based Underground Power Transmission Cable Fault Detection with Data Logging.pdf | |
| KEYWORDS | |
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