AI Driven Smart Prosthetics Arm Using IOT Integration for Adaptive Control and Feedback System
Sakshi Balaso Chavan1, Sakshi Mohan Gawademane2, Tasnim TahirHusen Kale3, Shreeja Mahadev Yangal4, Divya Satish Patil5, U.P.Kamble6
1,2,3,4,5Student , Automation And Robotics Department, S.I.T.Polytechnic, Engineering Yadrav (Ichalkaranji), Maharashtra, India
6Professor, Automation And Robotics Department, S.I.T.Polytechnic, Engineering Yadrav (Ichalkaranji), Maharashtra, India
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Abstract –
Millions of individuals worldwide suffer from limb loss due to accidents, congenital conditions, or medical issues, making daily tasks a challenge. Traditional prosthetics often lack adaptability, intuitive control, and sensory feedback, limiting their usability and effectiveness. There is a growing need for intelligent, affordable, and responsive prosthetic solutions that restore independence and improve quality of life. This project introduces an AI-driven, IoT-integrated smart prosthetic arm designed to enhance the independence and quality of life for individuals with disabilities. The arm is constructed using a 3D-printed modular design to ensure affordability, customization, and sustainability. It incorporates advanced sensors including EMG, force, temperature, and bending sensors that continuously monitor user input and environmental conditions. EMG signals serve as the primary input for intuitive control, while a joystick offers an alternative method. Sensor data is preprocessed using an IoT-enabled controller and transmitted to the AWS cloud via MQTT or HTTP protocols. A machine learning model deployed on a Raspberry Pi analyzes this data in real-time to predict appropriate movements, dynamically adjust grip strength, and provide haptic feedback, ensuring safe and precise object handling. The accompanying Android application allows users and caregivers to monitor the system’s performance remotely, enhancing usability and diagnostic capabilities. This solution addresses the shortcomings of traditional prosthetics namely high cost, limited adaptability, and lack of sensory feedback by leveraging artificial intelligence, real-time control, and edge-cloud integration. The arm finds applications in healthcare, rehabilitation, industry, defense, and agriculture, offering a scalable, sustainable, and user-centric approach to assistive technology.
Key Words: AI-driven prosthetic, EMG sensor, IoT-enabled control, real-time feedback, haptic feedback, adaptive grip, 3D-printed arm, assistive technology, smart prosthetics, Raspberry Pi, AWS IoT, Android monitoring
