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Research and Development of an AI-Powered Robotic Arm for Domestic Assistance and Social Interaction
ME-E-43
Shahaf Mizrahi; shahafmizrahi1999@gmail.com
Advisor: Dr. Yoav Y. Biton
SCE - Shamoon College of Engineering, Be’er-Sheva
Robotic arms integrated with AI offer significant potential for enhancing physical and social support within domestic environments. This project investigates the development of a robotic arm system capable of autonomous interaction and intelligent responses to voice commands. Simulations were performed to evaluate obstacle-aware motion planning, object detection accuracy, and successful completion of user-defined pick-and-place tasks. Additionally, an AI-driven conversational interface enabled natural interactions, supporting intuitive communication and promoting user engagement by expressive robotic gestures. Initial findings demonstrate effective robot responsiveness and enhanced social connection, highlighting the importance of integrating advanced simulation and AI methodologies. These insights provide a foundation for future development of accessible robotic solutions, addressing both practical assistance and social interaction.
Keywords: artificial intelligence, domestic robotics, human interaction, robotic arm, simulation
Voice Volume Monitoring System for People with Hearing Impairment
ME-E-44
Shoham Taichman; shohamt066@gmail.com Yair Lavee; yairlavee@gmail.com
Advisors: Dr. Etan Fisher1, Dr. Nir Trabelsi1
1SCE - Shamoon College of Engineering, Be’er-Sheva
People with hearing impairments often struggle to regulate their speaking volume, especially in noisy environments, leading to social discomfort. This project aims to develop an accessible system that provides real-time feedback when the user speaks too loudly or softly, helping them adjust their voice according to ambient noise. A PC-based prototype was developed using MATLAB and Simulink, analyzing the user’s speech and background noise via a single microphone. The data was processed to generate visual graphs illustrating volume differences. A key aspect of the work involves setting appropriate volume thresholds, with the goal of implementing an adaptive threshold mechanism using self-learning algorithms. The system’s physical interface will be intuitive, incorporating tactile or visual feedback to help users adjust their speaking volume.
Keywords: assistive technology, hearing impairment, real-time feedback, social communication, voice control