Leveraging Massive Information from Diverse Devices: An Intelligent, Low-Cost, Voice-Controlled Autonomous Wheelchair for Enhanced Mobility

Authors

  • Asim Sattar Department of Mechanical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs, Pakistan
  • Sayed Mazhar Ali Department of Electrical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs, Pakistan
  • Bhawani Shankar Chowdhry NCRAAI, Mehran University of Engineering and Technology, Jamshoro, Pakistan
  • Mushtaque Ahmed Rahu Department of Electronic Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah-67480, Pakistan
  • Sarang Karim Department of Telecommunication Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah-67480, Pakistan https://orcid.org/0000-0002-1983-0843

DOI:

https://doi.org/10.13052/jmm1550-4646.2062

Keywords:

Artificial intelligence, autonomous wheelchair, Low-Cost Mobility Solutions, Solar Energy, Voice-Controlled Mobility

Abstract

This paper explores the development of an intelligent, low-cost, voice-controlled autonomous wheelchair designed to enhance mobility for individuals with disabilities. The wheelchair integrates diverse data from multiple devices, including a voice recognition module, joystick module, ultrasonic sensors, and solar panels, to provide a comprehensive and adaptive user experience. Leveraging massive information from these interconnected devices, the wheelchair employs artificial intelligence and machine learning algorithms to refine its responsiveness to users’ voice commands, improving adaptability to individual speech patterns over time. The solar panels contribute to the wheelchair’s sustainability by harnessing solar energy for battery charging, ensuring prolonged operation without frequent recharging. This study details the design methodology, fabrication process, and performance testing of the wheelchair, showcasing its capabilities such as an optimum speed of 0.89 m/s, a load capacity of 20 kg, and effective obstacle avoidance. Additionally, the paper addresses the wheelchair’s advantages, potential limitations, and future enhancements. By leveraging diverse data sources and intelligent systems, this innovative wheelchair aims to significantly improve mobility, individuality, and worth of life for beings with mobility challenges and the elderly.

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Author Biographies

Asim Sattar, Department of Mechanical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs, Pakistan

Asim Sattar received a Bachelor’s degree in Mechanical engineering from Mehran University of Engineering and Technology SZAB Campus Khairpur Mirs Pakistan in 2021. He is currently working as a Trainee Engineer at Al-Noor MDF Lasani Board Division Plant Shahpur Jahania, Pakistan. His research areas include the Internet of Things, Renewable Energy, Material Engineering, AI, and Robotics. He is a lifetime member of the Pakistan Engineering Council.

Sayed Mazhar Ali, Department of Electrical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs, Pakistan

Sayed Mazhar Ali received a Bachelor’s degree in Electronic engineering from Quaid-e-Awam University of Engineering and Technology Nawabshah, Pakistan in 2016, a Master’s degree in Industrial Automation and control from Quaid-e-Awam University of Engineering and Technology Nawabshah, Pakistan in 2022. He is currently working as a Lecturer at the Department of Electrical Engineering, Mehran University of Engineering and Technology SZAB Campus Khairpur Mirs, Pakistan. His research areas include the Internet of Things, Machine Learning, Deep Learning, Robotics, Smart Agriculture, Energy Systems, and Control Systems. He has been serving as a reviewer for many highly respected journals and international conferences. He is a lifetime member of the Pakistan Engineering Council.

Bhawani Shankar Chowdhry, NCRAAI, Mehran University of Engineering and Technology, Jamshoro, Pakistan

Bhawani Shankar Chowdhry (Senior Member, IEEE) received the Ph.D. degree from the School of Electronics \& Computer Science, University of Southampton, U.K., in 1990. He is currently a Full Professor and former Dean of Faculty of Electrical Electronics and Computer Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan. He is having teaching and research experience of more than 30 years. He has the honor of being one of the editors of several books Wireless Networks, Information Processing and Systems (CCIS 20), Emerging Trends and Applications in Information Communication Technologies (CCIS 281), Wireless Sensor Networks for Developing Countries (CCIS 366), and Communication Technologies, Information Security and Sustainable Development (CCIS 414), published by Springer Verlag, Germany. He has also been serving as a Guest Editor of Wireless Personal Communications, which is a Springer International Journal. He has produced more than 13 Ph.D. degrees and supervised more than 50 M.Phil./master’s Theses in the area of ICT. His list of research publication crosses to over 60 in national and international journals, IEEE and ACM proceedings. Also, he has Chaired Technical Sessions in USA, U.K., China, UAE, Italy, Sweden, Finland, Switzerland, Pakistan, Denmark, and Belgium. He is a member of various professional bodies including: the Chairman IEEE Karachi Section, Region10 Asia/Pacific, Fellow IEP, Fellow IEEEP, Senior Member, IEEE Inc., USA, SM ACM Inc., USA. He is a Lead Person at MUET of several EU funded Erasmus Mundus Program, including Mobility for Life, StrongTies, INTACT, and LEADERS. He has organized several International Conferences, including IMTIC08, IMTIC12, IMTIC13, IMTIC15, WSN4DC13, IEEE SCONEST, IEEE PSGWC13, and the Track Chair in Global Wireless Summit (GWS 2014), and the Chief Organizer of GCWOC’16, GCWOC’18 and GCWOT’20 in Universidad de Malaga, Malaga, Spain.

Mushtaque Ahmed Rahu, Department of Electronic Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah-67480, Pakistan

Mushtaque Ahmed Rahu received a B.Eng. degree in electronic engineering and an M.Eng. Degree in industrial automation and control from the Quaid-e-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Pakistan, in April 2010 and 2016, respectively, where he is currently pursuing the Ph.D. degree. His research interests include the Internet of Things, wireless sensor networks, Machine learning, and Smart agriculture. He is a Lifetime Member of the Pakistan Engineering Council.

Sarang Karim, Department of Telecommunication Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah-67480, Pakistan

Sarang Karim received the B.Eng. degree in electronic engineering from Mehran University of Engineering and Technology (MUET), Jamshoro, Pakistan, in April 2011, and the M.Eng. degree in electronic systems engineering from the Institute of Information and Communication Technologies (IICT), MUET in 2015. He received the Ph.D. degree from the IICT, MUET, Jamshoro in December 2023. He was attached with ETSI, Universidad de Malaga, Malaga, Spain, as a Mobility Researcher from September 2017 to February 2018. He is currently working as an Assistant Professor in the Department of Telecommunication Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Pakistan. He published more than 26 research papers in reputed journals and conference proceedings. His research interests include Internet of Things, wireless sensor network, underwater wireless sensor networks, and smart agriculture. He is a Lifetime Member of Pakistan Engineering Council.

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Published

2025-02-07

How to Cite

Sattar, A. ., Ali, S. M. ., Chowdhry, B. S. ., Rahu, M. A. ., & Karim, S. . (2025). Leveraging Massive Information from Diverse Devices: An Intelligent, Low-Cost, Voice-Controlled Autonomous Wheelchair for Enhanced Mobility. Journal of Mobile Multimedia, 20(06), 1181–1210. https://doi.org/10.13052/jmm1550-4646.2062

Issue

2024: Vol 20 Iss 6

Section

SW2023: Massive Information by A Plethora of Devices (AIMS)

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