Viriyala Sri Anima Padmini, Ganesan Vithya
Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India.
Disabil Rehabil Assist Technol. 2025 Jul 24:1-16. doi: 10.1080/17483107.2025.2530674.
A multi-technology approach is helpful for challenging people to sense, localisation and user-centred route maps to navigate between destinations. Visually challenged people need navigation assistance between source and destination to choose a hazard-free or minimal-hazard optimal path. Navigator invokes online and offline hazard-free route maps to establish a safe and optimised route between source and destination. An online navigation system finds hazard-free optimal paths by artificial intelligence (AI), deep learning (DL), machine learning (ML) and cloud. The offline navigator uses a tensor processing unit (TPU) to generate a path map. Navigator uses AI and DL techniques to identify tree branches, signboards, underside of parked vehicles, open glass windows bumping into another walking person and fast-moving objects in outdoors and predicts artificial and natural hazards for selecting hazard-free optimised paths. The proposed fuzzy trusted hazard free routing path (FTHRP) algorithm utilises the data set "hazard-route data set" to identify the obstacle-free path between the source and destination by path planning and dynamic re-routing to avoid unexpected hazards. The navigation system leverages semantic route mapping based on AI-driven context inference processed by hardware and software.
一种多技术方法有助于促使人们感知、定位并生成以用户为中心的路线图，以便在目的地之间导航。视力障碍者在源地和目的地之间需要导航辅助，以选择无危险或危险最小的最优路径。导航器调用在线和离线无危险路线图，以在源地和目的地之间建立安全且优化的路线。在线导航系统通过人工智能（AI）、深度学习（DL）、机器学习（ML）和云计算来找到无危险的最优路径。离线导航器使用张量处理单元（TPU）生成路径图。导航器使用AI和DL技术识别户外的树枝、路标、停放车辆的底部、敞开的玻璃窗、撞到其他行人以及快速移动的物体，并预测人为和自然危险，以选择无危险的优化路径。所提出的模糊可信无危险路由路径（FTHRP）算法利用“危险路线数据集”，通过路径规划和动态重新路由来识别源地和目的地之间的无障碍路径，以避免意外危险。导航系统利用基于由硬件和软件处理的AI驱动的上下文推理的语义路线映射。
