Wireless IoT-Based EV Charging Station with Automated Payment System

Abstract

The increasing adoption of electric vehicles has highlighted the need for smarter and more efficient charging infrastructure. This paper presents the design and development of a smart EV charging station integrated with an automated billing system using Internet of Things (IoT) technology. The proposed system aims to overcome the limitations of conventional charging setups, such as manual billing, lack of real-time monitoring, and inefficient resource management. The system is built around a Raspberry Pi Pico microcontroller, which coordinates multiple peripherals including an ultrasonic sensor for vehicle detection, a relay for power control, a GSM module for SMS notifications, and a wireless charging module (TX/RX coils) for contactless power transfer. An LCD display provides real-time visual feedback to the user, while a buzzer offers auditory alerts for charging status and system prompts. The core functionality of the system includes automated vehicle presence detection, dynamic billing based on energy consumption, secure payment verification, and gate access control. The ultrasonic sensor ensures the vehicle is properly aligned before initiating wireless charging. Once charging is complete, the system calculates the billing amount based on the duration and estimated power transfer and displays it on the screen. Payment can be made through integrated digital platforms, and once verified, the system opens the gate for vehicle exit. Real-time updates and system status notifications are delivered through the GSM module, enhancing user convenience and transparency. The system is designed to be scalable and adaptable to various EV types and charging requirements, with potential integration into cloud-based platforms for data analytics and remote management. This IoT-enabled solution offers a fully automated, user-friendly, and efficient approach to EV charging, reducing human intervention, improving resource utilization, and contributing to the development of sustainable, intelligent transportation infrastructure.