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@article{188277,
        author = {Mrigesh Janbandhu and Atharv Misal and Sharang Naladkar and Mayank Yadav},
        title = {IoT and AI-Enabled Underground Cable Fault Detection and Predictive Maintenance System using Ohm’s Law and GIS Mapping},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {3105-3112},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188277},
        abstract = {This project proposes a smart underground cable monitoring system that extends the principle of Ohm’s Law–based fault localization into a real-time, IoT-integrated, and AI-enhanced platform. Traditional underground cable fault locators are limited to measuring voltage drops to identify faults, lacking predictive capability and remote access. The proposed system overcomes these limitations by combining Arduino UNO with IoT communication modules (ESP32/LoRa/GSM), a multi-sensor fault classification setup (voltage, current, temperature, leakage, moisture sensors), and a cloud-based AI model for predictive maintenance. The system continuously monitors cable parameters, detects the exact fault location in kilometers, and transmits real-time data to a centralized server. A GIS-based mapping interface displays the fault coordinates, enabling rapid deployment of repair teams. Moreover, the AI model analyzes historical fault data to predict potential failures, minimizing downtime and ensuring grid reliability. The integration of IoT, AI, and GIS mapping with Ohm’s Law fault detection introduces novelty, practical utility, and non-obvious innovation, making the system patentable and highly applicable to smart grids, industrial power networks, and urban infrastructure. The incorporation of GIS mapping allows precise visualization of fault locations and cable networks. Experimental results demonstrate that the proposed approach enhances fault detection accuracy, reduces downtime, and supports efficient resource allocation for power utilities.},
        keywords = {Underground Cable, Fault Locator, Arduino UNO, Voltage Drop, LCD Display, Fault Simulation, Distance calculation using Ohm’s Law},
        month = {December},
        }