Design of an Intelligent Assistive Cane Integrating Obstacle Detection and Emotion Recognition Using AI and IoT

Visually impaired individuals face significant challenges in independent navigation due to limited environmental awareness and lack of real-time feedback from traditional assistive tools. Existing walking canes primarily support obstacle detection and fail to provide contextual information such as human interaction cues, navigation guidance, and emotional awareness. This paper presents the design and development of a Smart Visionary Navigation Cane that integrates Artificial Intelligence (AI), Internet of Things (IoT), and embedded systems to enhance mobility, safety, and social confidence of visually impaired users. The proposed system employs Raspberry Pi, machine learning and deep learning algorithms, camera modules, GPS, ultrasonic sensors, and Bluetooth-based audio feedback to enable face recognition, object and obstacle detection, emotion recognition, and real-time navigation assistance. The system aims to empower visually impaired individuals by offering an intelligent, affordable, and scalable assistive solution.