Enhancing Heavy-Vehicle Safety Utilizing Proximity Sensor and Microcontroller for Proactive Blind Spot Detection - Zulfa, Bilqisthi Ananda; Hersyah, Mohammad Hafiz (CHIPSET, 2026)
While Heavy Goods Vehicles (HGVs) are essential to the global economy, their massive size creates dangerous visibility gaps, or "blind spots," that place both drivers and other road users at risk. Traditional mirrors often fail to provide a complete view, making maneuvers like lane changes and reversing a constant safety challenge. This research introduces a practical, microcontroller-based intervention designed to act as a "second set of eyes" for the driver. By integrating ultrasonic proximity sensors around the vehicle’s periphery, the system provides immediate auditory warnings when an object enters a hazardous zone. Testing confirms that the system reliably distinguishes between immediate threats and clear paths, using a precise 10 cm threshold to trigger alerts. To further empower the driver, the system incorporates an ESP32-CAM module, which streams a live visual feed of the rear blind spot to a web-based interface. By combining the immediacy of sound with the clarity of real-time video, this dual-layered approach moves beyond passive monitoring to provide a proactive safety net. Ultimately, this study offers a scalable and accessible solution to human error caused by limited visibility in large-scale transportation.