en 2-Integrated Circuits: Digital, Analog Integrated Circuits: Digital, Analog Research Paper Research Paper <div style="text-align: justify;"><span style="text-justify:inter-ideograph"><span style="font-family:&quot;Times New Roman&quot;"><span style="font-family:'Times New Roman'">The present paper introduces a real-time intelligent assistive system that uses a pre-trained Artificial Intelligence (AI) model to estimate relative distance and detect common items/living beings and known people to help visually impaired people. A lightweight and accurate object identification framework based on YOLOv8 algorithm is used in the proposed system and tailored for embedded and portable devices for facilitating real-time detection. The system continually analyses live video data, recognizes objects and people within its range of vision, even moving towards the impaired with a significant relative velocity; and uses depth mapping or stereo vision algorithms to determine their relative distances. Relative distance is measured with accuracy varying from 98.66% to 99.8% for static objects and 98.67% to 99.47% for dynamic objects and both indoor and outdoor environments, with maximum variance of 1.21 and 5.76 respectively for static and moving objects, far superior compared to earlier results for more than 200 cm distance. With approximate 30% improvement in confidence score for static objects with 2.5% enhancement in mean average precision and 15% improvement in FPS, the proposed study presents a practical and scalable assistive solution that integrates AI perception and distance awareness to support independent navigation for visually impaired users.</span><span style="font-family:'Times New Roman'"></span></span></span><br> &nbsp;</div> <div style="text-align: justify;"></div>&nbsp; Pre-trained A.I Model, Relative Distance Measurement, Real-Time Detection, Visually Impaired People 4202 4202 http://ijeee.iust.ac.ir/browse.php?a_code=A-10-5119-4&slc_lang=en&sid=1 Arpan Deyasi arpan.deyasi@rcciit.org.in 1800319475328460018039 1800319475328460018039 Yes Department of Electronics and Communication Engineering Diptadip Barai diptadipbarai20@gmail.com 1800319475328460018040 1800319475328460018040 No Hardware Engineer, EzeRx Pampa Debnath pampa.debnath@rcciit.org.in 1800319475328460018041 1800319475328460018041 No Department of Electronics and Communication Engineering, RCC Institute of Information Technology