A Unified IoT–RTC Enabled Smart Urban Utility Framework for Real-Time Fault Localization, Autonomous Control, and Energy-Efficient Infrastructure Management

Authors

  • I. Vasantha Kumari Author
  • Akula Bharath Kumar Author
  • Narasimhulu Abhinay Author

DOI:

https://doi.org/10.64751/wwj80t39

Keywords:

Ultrasonic Sensor, Smart Municipal System, Smart Street Lighting, RTC-Based Scheduling, Urban Infrastructure Management

Abstract

Municipal infrastructure management has traditionally relied on manual monitoring and fixed operational schedules, which often lead to inefficiencies, delayed responses, and resource wastage. Over time, the rapid growth of urban populations has increased the demand for reliable water distribution, effective drainage systems, and energy-efficient street lighting. Conventional systems for controlling water pumps and monitoring manholes lack real-time data acquisition and automation, making them prone to overflow incidents, equipment failures, and increased maintenance costs. With the advent of the Internet of Things (IoT), there has been a significant transformation in how urban utilities are managed, enabling real-time monitoring, remote control, and intelligent decision-making. Modern microcontrollers like ESP32, combined with sensors and communication technologies, provide a cost-effective and scalable solution for smart city applications. The proposed system focuses on integrating IoT technology into municipal operations by automating water pump control, monitoring manhole water levels, and managing street lighting efficiently. The system utilizes sensors for continuous data collection, an RTC module for precise scheduling, and IoT connectivity for remote supervision and alerts. This evolution from manual to intelligent systems not only improves operational efficiency but also enhances public safety, reduces human intervention, and supports sustainable urban development.

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Published

2026-04-23

How to Cite

A Unified IoT–RTC Enabled Smart Urban Utility Framework for Real-Time Fault Localization, Autonomous Control, and Energy-Efficient Infrastructure Management. (2026). International Journal of AI Electronics and Nexus Energy, 2(2), 541-549. https://doi.org/10.64751/wwj80t39

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