Smart Vehicle Load Management with Arduino Sensors

M. A. Pandiyan, Kayyuru Sarvani, Nesanuru Shireesha, V. Sanjunadha Reddy, K Nithish Kumar and Akula Pushpak

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 3, 10-15

Abstract: In the context of road safety, vehicle overloading remains a persistent concern, posing a risk of accidents, infrastructure damage, and potential harm to human life. This project introduces an innovative solution for mitigating this issue through an Arduino-based smart vehicle load management The system incorporates load cell, Ultrasonic sensor, an LCD display, and a buzzer to effectively detect and prevent vehicle overloading, contributing to improved road safety. The smart vehicle load management with arduino sensors is designed to monitor the weight distribution on a vehicle using strategically placed load cells and detect variations in vehicle obstacle detection through Ultrasonic sensors. Upon detecting an overload condition, the system promptly triggers a response by stopping the motor, which prevents further loading, and immediately displays a warning on the LCD screen. Simultaneously, it activates an audible alert through the buzzer. This rapid reaction not only averts potential accidents resulting from overloading but also extends the vehicle's operational life by minimizing wear and tear. The Arduino-based Vehicle Overload Detection System represents a cost-effective and efficient approach to addressing the critical issue of vehicle overloading. Its monitoring capabilities, coupled with instant warnings and alerts, establish it as a valuable tool in enhancing road safety and reducing the risks associated with overloading.

Keywords: Arduino; Ultrasonic Sensor; Overload Detection; Accident Prevention and Alert (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT24102131
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i3:id:169

DOI: 10.32628/CSEIT24102131

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