An Intelligent Multi-Floor Navigational System Based on Speech, Facial Recognition and Voice Broadcasting Using...

Area of Science:

• Robotics and Human-Computer Interaction
• Artificial Intelligence and Machine Learning
• Ubiquitous Computing and Navigation Systems

Background:

• Modern technologies like the Internet of Things (IoT) and mobile devices are crucial for navigation in unfamiliar environments.
• Indoor navigation systems are essential for locating specific places within buildings.
• Existing systems benefit from mobile integration, increasing user acceptance and adoption.

Purpose of the Study:

• To present a novel, adaptable, and changeable multistory indoor navigation system.
• To implement the system in diverse environments such as libraries, grocery stores, shopping malls, and official buildings.
• To utilize facial and speech recognition with voice broadcasting for enhanced user interaction.

Main Methods:

• Development of an Android-based platform with separate administrative and robot-deployed applications.
• Integration of robots on each floor for inter-robot and user communication.
• Implementation of facial and speech recognition for user identification and interaction.
• Testing through system evaluation (accuracy of recognition) and user evaluation (usability and helpfulness).

Main Results:

• The proposed system achieved high accuracy rates of 97.92% and 97.88% for voice and face recognition tasks.
• User evaluation in multi-story libraries indicated high user satisfaction and perceived usefulness.
• Users found the robot assistance and automatic recognition features beneficial for navigation.

Conclusions:

• The developed indoor navigation system is effective and adaptable for various multi-story environments.
• The integration of robotics, AI-driven recognition, and mobile technology significantly improves indoor navigation experiences.
• The system demonstrates potential for widespread implementation in public and commercial spaces.