Smart Embedded Night Vision System for Pedestrian Detection

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Authors: Kalyani Pawar, Akshara Borase, Nisha More, S. S. Aher Darshan Pahade
Cited by: 0
References: 5

Abstract

Night-time driving is risky because humans cannot see clearly in the dark, but unfortunately pedestrians and animals do not glow in the headlights on time. As a result, road accidents increase, and drivers realize the problem only after it is too late. To reduce this issue, this project introduces an Embedded Night Vision System for Pedestrian Detection using an ESP32 microcontroller.The system is mounted on a small car prototype that acts smarter than some real drivers. It uses PIR sensors to detect humans and animals by sensing the heat they naturally emit—because living beings cannot hide their body temperature. Once motion is detected, the ESP32 quickly reacts by alerting the driver and controlling the vehicle movement before panic braking is required.The car can be controlled wirelessly using Bluetooth through a mobile application, while an L298N motor driver ensures smooth movement of the DC motors.Overall, this project proves that with a little intelligence, a car can “see” better at night and help avoid accidents. Future upgrades may include cameras, AI, and IoT—because even cars deserve smarter vision.

Fields of Study & Subjects

IoT and GPS-based Vehicle Safety Systems Autonomous Vehicle Technology and Safety Arduino and IoT Applications

Publication details

Journal / source
International Journal of Advanced Research in Science Communication and Technology
Pages
604–604
Publication date
13 January 2026