Enhancing Indoor Navigation for Visually Impaired Individuals with an AI Chatbot Utilizing VEO Optimized Nodes and Natural Language Processing
Nagaraju Thandu, Murugeswari R- Electrical and Electronic Engineering
- Control and Optimization
- Computer Networks and Communications
- Computer Science Applications
Aims and Background:
Visually impaired people face numerous challenges when it comes to indoor navigation. While outdoor navigation benefits from advancements in GPS and related technologies, indoor spaces present intricate, complex, and often less accessible environments for those with visual impairments.
Objective and Methodology:
In response to these challenges, we propose an innovative approach to enhance indoor navigation for individuals with visual impairments, leveraging the power of an AI chatbot. Our AI chatbot employs cutting-edge artificial intelligence techniques to provide realtime assistance and guidance, facilitating independent navigation within intricate indoor settings. By harnessing natural language processing technologies, the chatbot engages in intuitive interactions with users, comprehending their queries and offering detailed instructions for efficient indoor navigation. The main goal of this research is to enhance the independence of people with visual impairments by offering them a reliable and easily accessible tool.
Results and conclusion:
This tool, driven by our Volcano Eruption Optimization Network, promises to significantly enhance the independence and overall indoor navigation experience for visually impaired people, ultimately fostering a greater sense of autonomy in navigating complex indoor spaces.
method:
Self-Attention-Based Multimodality Convolutional Volcano Eruption optimization
result:
Optimizing Weight Parameters with Volcano Eruption-Based Optimization (VEO)
conclusion:
our AI chatbot-based approach presents a promising solution to the pressing issue of indoor navigation for individuals with visual impairments. We have successfully harnessed cutting-edge artificial intelligence techniques, including natural language processing and computer vision, to empower visually impaired users with real-time assistance and guidance within complex indoor environments.
other:
none