Performance analysis of REST API in a real-time IoT-based vehicle monitoring system

Abstract

This study studies the design and implementation of a REST API and its performance analysis for an internet of things (IoT)-based vehicles monitoring system. This system incorporates brake pad sensors, a tire pressure monitoring system (TPMS) for assessing tire pressure and temperature, light detection and ranging (LIDAR) for measuring tire thickness, and radio frequency identification (RFID) for tire identification. Data is gathered using an ESP32 microcontroller and transmitted in real-time to the server via a REST API over a wireless network. The JSON Web Token (JWT) authentication mechanism is employed to ensure data security. Testing indicates that this system has an average response time of 4–11 ms, with optimal performance recorded at 3.93 ms for the RFID sensor and peak performance at 9.19 ms for the LIDAR sensor. Load testing with 100 concurrent users demonstrates that the system maintains stability with a 100% data delivery success rate. Authentication testing demonstrates that the API is accessible solely with a valid token, hence preventing unauthorized access. This study's results demonstrate that integrating REST API with IoT monitoring systems facilitates real-time vehicle monitoring, enhances maintenance efficiency, and offers viable solutions for future predictive maintenance systems.