ArticleSensors (Basel, Switzerland)2026
AI-Assisted Vision Alarming System for Blind and Vision- Impaired People.
Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
Funding
Abstract
Navigating through everyday environments, like walking down a sidewalk, which many people often take for granted, is a difficult task for millions of people with vision impairments since it involves sophisticated object detection, depth perception, and situational awareness, all working seamlessly to guide a person through complex surroundings. Many current assistive devices for vision-impaired people are either expensive, information-overabundant, or missing critical information. This paper details our Vision Alarming System (VAS), which can improve the safety for blind and vision-impaired people by providing awareness of both positions and nature of nearby obstacles; thus, assisting users to make decisions to avoid collisions, reduce accidents and casualties, while enhance their experience, independence, and confidence when participating in traffic. VAS is an Artificial Intelligence/Internet-of-Things (AI/IoT)-powered system developed utilizing the cutting-edge Raspberry Pi 5, a Light Detection and Ranging (LiDAR) sensor, and an AI depth camera, operating as different containers in a Docker architecture, and leveraging a Robotic Operating System 2 (ROS 2) backbone. VAS communicates the obstacle detections to users via Bluetooth interface, using the neural Text-To-Speech (TTS) system, namely, Piper, and the Sound eXchange (SoX) technologies. Our proof-of-concept system proves that VAS can be a standalone, open-source, extremely low cost, low power consumption assistive device which can synergistically utilize the cutting-edge AI/IoT technologies to provide blind and vision-impaired users with an appropriate amount of critical information about their surrounding environments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.