Design and implementation of an automatic speed control mechanism using arduino, RFID, GPS, and MATLAB for enhancing safety near Schools and Colleges

Abstract

Ensuring road safety in school and college zones remains a critical global concern, as excessive vehicle speeds continue to pose significant risks to pedestrians, particularly children. This study aimed to design and implement an automatic speed control mechanism integrating Arduino, RFID, GPS, and MATLAB to monitor, analyze, and enforce speed limits in designated safety zones. The primary objective was to create a technology-driven system capable of identifying vehicles, measuring their speeds, and triggering corrective actions in real-time. The system utilized RFID tags for vehicle identification, a GPS module for precise location tracking, and an ultrasonic sensor for speed measurements. Data collected were wirelessly transmitted via a Bluetooth module and analyzed in MATLAB to ensure compliance with speed regulations. A sample of 50 vehicles passing through a designated school safety zone was monitored. Results revealed a 90% compliance rate, with compliant vehicles averaging a speed of 32.92 km/h, while non-compliant vehicles recorded an average speed of 42.48 km/h. An independent t-test showed a statistically significant difference (p = 1.52 × 10⁻⁶) between the two groups, validating the system's effectiveness in speed enforcement. Furthermore, the average speed during the morning zone was recorded at 33.87 km/h, indicating temporal variations in driver compliance. The study highlights the potential of combining embedded systems and analytical tools like MATLAB to create scalable and efficient traffic control systems. Practical recommendations include upgrading communication protocols to LoRaWAN or Zigbee, integrating with smart traffic lights, deploying AI-driven predictive analytics, and expanding deployment across larger datasets and varied time zones. This research demonstrates a promising approach to improving road safety and suggests future advancements in automated traffic monitoring technologies.