IoT-Based Smart Parking System Using Time-of-Flight Sensors with ANPR-Assisted Fault Detection

Abstract

The number of vehicles in crowded cities is increasing rapidly, making it a daily challenge for drivers to find a parking space. Instead of going directly to a free spot, drivers often keep moving around the parking area until they find one, which wastes fuel, adds to congestion, and increases carbon emissions. Although many IoT-based smart parking systems have been proposed in recent years, most of them rely on single-sensor setups and do not provide a reliable way to check whether a sensor is working properly or has failed. In this paper, we present a smart parking system built on a two-tier IoT architecture to improve reliability. VL53L0X Time-of-Flight sensors, connected with ESP32 microcontrollers, are used to detect vehicle presence in each parking slot and send the data through MQTT to a central Raspberry Pi. At the same time, the Raspberry Pi runs an OpenCV-based Automatic Number Plate Recognition (ANPR) module using a CCTV camera feed. This camera setup performs two tasks: it monitors vehicles entering and exiting the parking area, and it also helps verify sensor data to identify faulty or stuck sensors. A mobile application is provided to show drivers real-time availability of parking slots. After reviewing nine recent research papers in this domain, we observed that none of them used ToF sensors for slot detection, and none included a proper hardware fault-detection mechanism. The proposed system attempts to address both of these limitations.

Introduction

The text describes the growing problem of finding parking in crowded urban areas and proposes an IoT-based smart parking system to improve efficiency and reliability. In many cities, drivers waste time searching for empty parking spots because parking facilities still rely on manual management and do not provide real-time space availability. Studies show a significant portion of urban traffic is caused by vehicles looking for parking, highlighting the need for smarter solutions.

To address this, the proposed system uses a smart architecture with VL53L0X Time-of-Flight (ToF) sensors installed at each parking slot to accurately detect vehicle presence. Each slot is connected to an ESP32 microcontroller that sends real-time data via MQTT to a central Raspberry Pi server. The Raspberry Pi processes the data and provides access through a mobile application and REST APIs. Additionally, an OpenCV-based Automatic Number Plate Recognition (ANPR) system is used at entry and exit points to track vehicles and verify sensor data, improving system accuracy and detecting faults.

The literature review shows that most existing smart parking systems rely on sensors like ultrasonic or infrared sensors and often lack reliability checks or backup validation methods. Many systems also do not provide full real-time remote access or cross-verification of data. The proposed system improves on these limitations by introducing ToF sensors, ANPR-based validation, and fault detection mechanisms.

Conclusion

This paper described the design of an IoT-based smart parking system that tries to go beyond what most existing systems currently offer. The two main problems it targets are inaccurate slot detection caused by sensor limitations and the complete lack of fault detection in current designs. The proposed system replaces ultrasonic and infrared sensors with VL53L0X Time-of-Flight sensors. These sensors are not thrown off by temperature changes in the air or bright outdoor light, which makes them a better match for real parking environments. The two-tier setup, with ESP32 nodes at each zone feeding into a central Raspberry Pi, keeps the system practical and easy to grow as a parking facility expands. What sets this work apart from the nine systems reviewed is the use of an ANPR camera not just for identifying vehicles, but as a way to check whether the sensors are still working correctly. By comparing the camera\'s vehicle count with the sensor occupancy data, the system can catch faults that would otherwise go unnoticed and make sure drivers are not sent to a slot that is already taken.

References

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Copyright

Copyright © 2026 Sujal Khant, Ridhdhi Naik . 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.