AI-SenseVision: A Low-Cost Artificial-Intelligence-Based Robust and Real-Time Assistance for Visually Impaired People

IF 3.5 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Human-Machine Systems Pub Date : 2024-03-29 DOI:10.1109/THMS.2024.3375655
Rakesh Chandra Joshi;Nitin Singh;Anuj Kumar Sharma;Radim Burget;Malay Kishore Dutta
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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.
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AI-SenseVision:基于人工智能的低成本视障人士鲁棒实时辅助系统
视障人士(VIP)在日常生活中会遇到各种挑战,因此需要便携式、用户友好型设备为他们提供实时帮助,为他们提供有关周围环境的指导。本文介绍了一种基于人工智能的创新型可穿戴辅助设备--人工智能(AI)--SenseVision,用于分析场景中物体和障碍物的视觉和感官信息,从而感知周围环境。该设备是传感器和计算机视觉技术的完美结合,可生成带有识别物体名称的听觉信息或检测到障碍物的音频警告。经过训练的深度学习模型的性能在复杂的真实场景中进行了严格测试,使用各种统计参数进行实验验证。此外,训练有素的深度学习模型已被集成到一个低成本的单板处理器中,成为一个独立的高性价比设备。所有数据处理都在优化的单一硬件设置内完成,用户可以轻松访问不同的模式,如室内和室外模式,同时还能在观察到的场景中进行物体计数。所提出的系统具有传感器成本低、操作模式多、易于集成和体积小等特点,使这一辅助设备有助于贵宾独立导航和防碰撞。
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来源期刊
IEEE Transactions on Human-Machine Systems
IEEE Transactions on Human-Machine Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
7.10
自引率
11.10%
发文量
136
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.
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