An ESP32-Based IoT System for Blind Spot Detection in Logistics Vehicles - Ilamsyah, Ilamsyah; Kusumah, Hendra; Astriyani, Erna; Taufik, Muhamad Ikhsan (UNIVERSITAS RAHARJA, 2025)
The increasing number of vehicles in the logistics industry has led to a higher risk of accidents due to vehicle blind spots. PT. Aerofood ACS requires a real-time, cost-effective, and easily deployable monitoring system to enhance the safety and operational efficiency of their EBRO trucks. To address this need, this research develops an Internet of Things (IoT)-based blind spot monitoring system using ESP32. The device design methodology includes a prototyping approach and data collection through observation, interviews with stakeholders, and literature studies in system development. This system utilizes HC-SR04 ultrasonic sensors to detect objects in blind spot areas, where the obtained data is processed by ESP32 and displayed on an LCD. Additionally, information is transmitted to the cloud for real-time monitoring. The primary objective of this study is to design and implement a monitoring system capable of providing early warnings to drivers to reduce accident risks. Alerts are provided through LED indicators, buzzers, and IoT notifications, ensuring that drivers can promptly respond to potential hazards. The research findings indicate that the developed system can accurately detect blind spots and effectively issue warnings. Thus, this system serves as an innovative solution that can be implemented for various logistics needs in compliance with PT. Aerofood ACS's safety standards.