EnerPulse-IoT: Design and Implementation of an ESP32-Based Prepaid Smart Energy Meter with Real-Time Monitoring and Automated Load Control

Abstract

Energy meters are essential devices used to measure and record electrical energy consumption in residential, commercial, and industrial environments. This paper presents EnerPulse-IoT, an ESP32-based prepaid smart energy meter designed for accurate energy monitoring, automated billing, and efficient load management. The proposed system integrates voltage and current sensing modules to acquire real-time electrical parameters and calculate power usage continuously. Energy consumption data are processed by the ESP32, enabling dynamic balance deduction based on prepaid credit. A relay mechanism automatically disconnects the electrical supply when the available balance reaches zero, preventing unpaid consumption and promoting responsible energy utilization. An integrated LCD displays consumption statistics, remaining balance, and system status for enhanced user awareness. Wireless connectivity enables remote monitoring, recharge management, and alert notifications through an IoT-enabled platform. The system also incorporates theft detection and tamper indication features using a buzzer-based warning mechanism, improving operational security. Experimental implementation demonstrates reliable performance in measuring energy usage, maintaining billing accuracy, and controlling connected loads. The proposed solution reduces manual intervention, supports transparent energy management, and sustainability.

Introduction

The text presents an IoT-enabled prepaid smart energy meter system designed to improve electricity monitoring, billing accuracy, energy conservation, and security. The proposed system, called EnerPulse-IoT, uses modern IoT technologies to overcome limitations of traditional electricity meters.

Background and Motivation

Electricity is essential for homes, businesses, industries, and technology. Increasing energy demand requires efficient monitoring and management of consumption. Traditional electricity billing systems face issues such as:

• Manual meter reading and delayed billing.
• Human errors in consumption recording.
• Lack of real-time energy usage information.
• Electricity theft and unauthorized usage.
• Low transparency between consumers and utility providers.

IoT-based smart meters provide automated monitoring, remote communication, and real-time analysis, improving energy management and user awareness.

Proposed System: IoT-Based Prepaid Smart Energy Meter

The proposed system integrates:

• ESP32 microcontroller for processing and communication.
• Voltage and current sensors to measure electrical parameters.
• LCD display to show consumption and balance information.
• Relay module for automatic load control.
• IoT communication for remote monitoring.
• Theft detection mechanisms for improved security.

The system works on a prepaid model where users recharge energy credits in advance. The meter continuously calculates electricity usage and deducts the cost from the available balance. When the balance reaches a set limit, the relay automatically disconnects the power supply.

Literature Survey Findings

Previous research shows that IoT-based smart meters have improved:

• Real-time electricity monitoring.
• Automated billing.
• Remote access to consumption data.
• Reduction of manual work.
• Energy conservation awareness.

Existing systems have used technologies such as:

• Arduino and sensors for low-cost monitoring.
• ESP8266/ESP32 for wireless communication.
• GSM for remote data transmission.
• Cloud platforms for data visualization.
• Prepaid models for automated billing and load control.

Recent studies focus on combining IoT, prepaid billing, theft detection, and smart energy management for reliable modern power systems.

Problem Statement

Conventional electricity meters have several drawbacks:

• Manual reading is slow and error-prone.
• Postpaid billing can cause revenue losses.
• Consumers cannot easily track real-time usage.
• Electricity theft and meter tampering remain challenges.
• Lack of remote control reduces system efficiency.

Objectives

The project aims to:

1. Develop a real-time IoT-based energy monitoring system.
2. Replace traditional billing with prepaid energy management.
3. Provide users with continuous consumption information.
4. Automatically disconnect power when balance is exhausted.
5. Reduce human intervention and billing errors.
6. Improve energy transparency, security, and efficiency.

Methodology

The system architecture combines four major components:

1. Sensing Unit
   • Measures voltage and current continuously.
   • Calculates energy consumption.
2. Processing Unit
   • ESP32 processes sensor data.
   • Updates balance and controls operations.
3. Communication Unit
   • Sends energy data through IoT connectivity.
   • Enables remote monitoring.
4. Control Unit
   • Relay module controls electricity supply.
   • Disconnects load during low or zero balance conditions.

Conclusion

In this research, an IoT-enabled prepaid smart energy metering system was successfully presented to improve electricity monitoring, billing transparency, and energy utilization efficiency. The proposed framework integrated voltage and current sensing modules, an ESP32 microcontroller, wireless communication capabilities, a relay control mechanism, and a display interface to provide continuous monitoring of electrical energy consumption. Real-time measurement and automated balance deduction enabled effective management of prepaid electricity usage while reducing dependency on conventional billing procedures. The automated load control feature ensured disconnection of supply when the available balance was exhausted, preventing unauthorized energy consumption. Remote monitoring functionality enhanced accessibility and user awareness regarding electricity usage patterns. The incorporation of alert and security mechanisms further improved operational reliability and protection against potential misuse. The study demonstrated that intelligent metering solutions can significantly reduce manual intervention, improve billing accuracy, and support efficient energy management. Future work may focus on integrating cloud-based analytics, mobile payment gateways, advanced theft detection algorithms, renewable energy monitoring capabilities, and machine learning techniques for consumption forecasting. Additional enhancements may include smart grid interoperability, multi-user billing support, and large-scale deployment for advanced energy management applications across diverse sectors and environments.

References

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Copyright

Copyright © 2026 Asst. Prof. Laxmi, Ayesha , Soha Fatima, Poornima . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.