Risk-Based Safety Strategies for Preventing Electrical and Fire Hazards in Industrial Power Networks: Development of a Cable Health Monitoring System (ECHMS)

Abstract

This thesis aims to design and implement an intelligent system for real-time monitoring of the condition of electrical cables, using Internet of Things (IoT) technologies and embedded systems. The project addresses critical challenges in industrial settings, such as overheating, overcurrents, mechanical vibrations, and insulation degradation, which can lead to fires or unexpected power outages. A functional prototype was developed using Arduino UNO and ESP32 microcontrollers, along with high-precision sensors: DHT22 (temperature and humidity), ACS712 (current), ZMPT101B (AC voltage), and MPU6050 (vibration via accelerometer and gyroscope). The data is stored and analyzed in real time using the Firebase cloud platform. An interactive web dashboard, developed with HTML, CSS, JavaScript, and Chart.js, allows users to visualize measurements and generate alerts based on predefined thresholds (normal, alert, danger). The original contribution of this work lies in the development of an intelligent simulation system that emulates four operational scenarios and calculates a dynamic health index (ranging from 0 to 100%), with detailed logs and CSV export functionality. The system achieved an accuracy of 98.7% with a response time below 320 ms.