Real-Time Obstacle Detection and GPS Tracking Assistive Device for Visually Impaired Using Iot

Abstract

Mobility and environmental awareness remain serious challenges for visually impaired individuals navigating daily life without external assistance. Conventional aids such as white canes provide only limited ground-level protection and are incapable of detecting overhead obstacles, tracking the user's outdoor location, or notifying remote caregivers of hazards. This paper presents the design, implementation, and hardware testing of a low-cost, IoT-enabled multifunctional assistive device built around the Raspberry Pi Pico W microcontroller. The system integrates an HC-SR04 ultrasonic sensor for obstacle detection up to 400 cm, an infrared proximity sensor for close range object sensing below 30 cm, a NEO-6M GPS module for real-time outdoor positioning, a 0.96-inch OLED display for local status feedback, an electromagnetic buzzer for differentiated audio alerting, a relay module for external device control, and a ULN2003-driven stepper motor and DC motor actuator subsystem for mechanical feedback. The Pico W's onboard 802.11n Wi-Fi transmits GPS coordinates and sensor states to the Thing Speak IoT cloud platform, giving caregivers real-time visibility of the user's location and device condition through a standard web browser. Firmware is written in Micro Python and developed using the Thonny IDE. Hardware testing confirms obstacle detection accuracy of 98.6%, GPS positioning accuracy of 2.3 m in open-sky conditions, Thing Speak upload latency of 1.74 seconds, and a total component cost of approximately ₹2,500, more than 96% lower than commercially available smart assistive devices.