{"title":"AI-SenseVision: A Low-Cost Artificial-Intelligence-Based Robust and Real-Time Assistance for Visually Impaired People","authors":"Rakesh Chandra Joshi;Nitin Singh;Anuj Kumar Sharma;Radim Burget;Malay Kishore Dutta","doi":"10.1109/THMS.2024.3375655","DOIUrl":null,"url":null,"abstract":"Visually impaired people (VIPs) encounter various challenges in their daily lives, and there is a need for portable, user-friendly device for real-time assistance to give them guidance regarding their surroundings. This article presents an artificial-intelligence-based innovative wearable assistive device—artificial intelligence (AI)-SenseVision—to analyze visual and sensory information about the objects and obstacles present in the scene to perceive the surrounding environment. The device is a complete amalgamation of sensor and computer-vision-based technologies that generate auditory information with the name of identified objects or audio warnings for detected obstacles. The performance of the trained deep-learning model is rigorously tested in complex and real-life scenarios using various statistical parameters for experimental validation. Moreover, the trained deep-learning models have been integrated into a low-cost single-board processor to make a standalone cost-effective device. All data processing is done within an optimized single hardware setup, and the user can easily access different modes, such as indoor and outdoor mode, while also enabling object counting in observed scenes. The proposed system has low-cost sensors, multiple operational modes, easy integration, and small volume, making this assistive device helpful for VIPs for independent navigation and collision prevention.","PeriodicalId":48916,"journal":{"name":"IEEE Transactions on Human-Machine Systems","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Human-Machine Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10485529/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Visually impaired people (VIPs) encounter various challenges in their daily lives, and there is a need for portable, user-friendly device for real-time assistance to give them guidance regarding their surroundings. This article presents an artificial-intelligence-based innovative wearable assistive device—artificial intelligence (AI)-SenseVision—to analyze visual and sensory information about the objects and obstacles present in the scene to perceive the surrounding environment. The device is a complete amalgamation of sensor and computer-vision-based technologies that generate auditory information with the name of identified objects or audio warnings for detected obstacles. The performance of the trained deep-learning model is rigorously tested in complex and real-life scenarios using various statistical parameters for experimental validation. Moreover, the trained deep-learning models have been integrated into a low-cost single-board processor to make a standalone cost-effective device. All data processing is done within an optimized single hardware setup, and the user can easily access different modes, such as indoor and outdoor mode, while also enabling object counting in observed scenes. The proposed system has low-cost sensors, multiple operational modes, easy integration, and small volume, making this assistive device helpful for VIPs for independent navigation and collision prevention.
期刊介绍:
The scope of the IEEE Transactions on Human-Machine Systems includes the fields of human machine systems. It covers human systems and human organizational interactions including cognitive ergonomics, system test and evaluation, and human information processing concerns in systems and organizations.