Experimental Evaluation of IoT Powered Automated Wheel Chair Controlling Mechanism Based on Artificial Intelligence Principle

This paper presents the experimental evaluation of an IoT-powered automated wheelchair control mechanism based on artificial intelligence (AI) principles. The system integrates smart features such as voice control, obstacle detection, and real-time health monitoring to improve mobility for individuals with disabilities. Key components include Arduino Nano and ESP8266 microcontrollers, 12V DC motors for movement, and various sensors for health monitoring and obstacle detection. The wheelchair can be controlled via smartphone using Bluetooth or Wi-Fi, and voice commands for hands-free operation. Results from the experiment show that the voice control system demonstrated an average recognition delay of 0.5 to 0.7 seconds, while total response times under load averaged around 1.3 seconds. Health monitoring sensors, including heart rate and temperature sensors, exhibited a high accuracy, with an error margin of less than 3% for heart rate and 0.5% for temperature measurements. Obstacle detection proved effective, with an average response time of 1.2 seconds for detecting objects at 50 cm distance. Overall, the system demonstrated reliable performance across different operational conditions, making it suitable for practical applications in healthcare and personal mobility. Future enhancements aim to integrate artificial intelligence for autonomous navigation and multilingual support in the voice recognition system.