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IoT for Smart Cities: Machine Learning Approaches in Smart Healthcare—A Review

Author

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  • Taher M. Ghazal

    (Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebansaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
    School of Information Technology, Skyline University College, Sharjah 1797, United Arab Emirates)

  • Mohammad Kamrul Hasan

    (Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebansaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia)

  • Muhammad Turki Alshurideh

    (Department of Marketing, School of Business, The University of Jordan, Amman 11942, Jordan
    Department of Management, College of Business, University of Sharjah, Sharjah 27272, United Arab Emirates)

  • Haitham M. Alzoubi

    (School of Business, Skyline University College, Sharjah 1797, United Arab Emirates)

  • Munir Ahmad

    (School of Computer Science, National College of Business Administration & Economics, Lahore 54000, Pakistan)

  • Syed Shehryar Akbar

    (School of Computer Science, National College of Business Administration & Economics, Lahore 54000, Pakistan)

  • Barween Al Kurdi

    (Department of Business Administration, Faculty of Economics and Administrative Sciences, The Hashemite University, Zarqa 13115, Jordan)

  • Iman A. Akour

    (Department of Information Systems, College of Computing and Informatics, University of Sharjah, Sharjah 27272, United Arab Emirates)

Abstract

Smart city is a collective term for technologies and concepts that are directed toward making cities efficient, technologically more advanced, greener and more socially inclusive. These concepts include technical, economic and social innovations. This term has been tossed around by various actors in politics, business, administration and urban planning since the 2000s to establish tech-based changes and innovations in urban areas. The idea of the smart city is used in conjunction with the utilization of digital technologies and at the same time represents a reaction to the economic, social and political challenges that post-industrial societies are confronted with at the start of the new millennium. The key focus is on dealing with challenges faced by urban society, such as environmental pollution, demographic change, population growth, healthcare, the financial crisis or scarcity of resources. In a broader sense, the term also includes non-technical innovations that make urban life more sustainable. So far, the idea of using IoT-based sensor networks for healthcare applications is a promising one with the potential of minimizing inefficiencies in the existing infrastructure. A machine learning approach is key to successful implementation of the IoT-powered wireless sensor networks for this purpose since there is large amount of data to be handled intelligently. Throughout this paper, it will be discussed in detail how AI-powered IoT and WSNs are applied in the healthcare sector. This research will be a baseline study for understanding the role of the IoT in smart cities, in particular in the healthcare sector, for future research works.

Suggested Citation

  • Taher M. Ghazal & Mohammad Kamrul Hasan & Muhammad Turki Alshurideh & Haitham M. Alzoubi & Munir Ahmad & Syed Shehryar Akbar & Barween Al Kurdi & Iman A. Akour, 2021. "IoT for Smart Cities: Machine Learning Approaches in Smart Healthcare—A Review," Future Internet, MDPI, vol. 13(8), pages 1-19, August.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:8:p:218-:d:619616
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    References listed on IDEAS

    as
    1. Linda Nordling, 2019. "A fairer way forward for AI in health care," Nature, Nature, vol. 573(7775), pages 103-105, September.
    2. Nahla Nurelmadina & Mohammad Kamrul Hasan & Imran Memon & Rashid A. Saeed & Khairul Akram Zainol Ariffin & Elmustafa Sayed Ali & Rania A. Mokhtar & Shayla Islam & Eklas Hossain & Md. Arif Hassan, 2021. "A Systematic Review on Cognitive Radio in Low Power Wide Area Network for Industrial IoT Applications," Sustainability, MDPI, vol. 13(1), pages 1-20, January.
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    Citations

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    Cited by:

    1. Daniela REISZ & Raluca TUDOR & Iulia CRISAN, 2022. "The Role of Small Medical Units in a Smart City The Case of Timisoara," Smart Cities International Conference (SCIC) Proceedings, Smart-EDU Hub, vol. 10, pages 289-298, November.
    2. Sarantis Kalafatidis & Sotiris Skaperas & Vassilis Demiroglou & Lefteris Mamatas & Vassilis Tsaoussidis, 2022. "Logically-Centralized SDN-Based NDN Strategies for Wireless Mesh Smart-City Networks," Future Internet, MDPI, vol. 15(1), pages 1-21, December.
    3. Alper Ozpinar, 2023. "A Hyper-Integrated Mobility as a Service (MaaS) to Gamification and Carbon Market Enterprise Architecture Framework for Sustainable Environment," Energies, MDPI, vol. 16(5), pages 1-22, March.
    4. Adwitiya Mukhopadhyay & Aryadevi Remanidevi Devidas & Venkat P. Rangan & Maneesha Vinodini Ramesh, 2024. "A QoS-Aware IoT Edge Network for Mobile Telemedicine Enabling In-Transit Monitoring of Emergency Patients," Future Internet, MDPI, vol. 16(2), pages 1-22, February.
    5. Salem Ahmed Alabdali & Salvatore Flavio Pileggi & Dilek Cetindamar, 2023. "Influential Factors, Enablers, and Barriers to Adopting Smart Technology in Rural Regions: A Literature Review," Sustainability, MDPI, vol. 15(10), pages 1-38, May.
    6. Divya Biligere Shivanna & Thompson Stephan & Fadi Al-Turjman & Manjur Kolhar & Sinem Alturjman, 2022. "IoMT-Based Automated Diagnosis of Autoimmune Diseases Using MultiStage Classification Scheme for Sustainable Smart Cities," Sustainability, MDPI, vol. 14(21), pages 1-15, October.
    7. Urmila Pilania & Rohit Tanwar & Mazdak Zamani & Azizah Abdul Manaf, 2022. "Framework for Video Steganography Using Integer Wavelet Transform and JPEG Compression," Future Internet, MDPI, vol. 14(9), pages 1-16, August.
    8. Fabián Silva-Aravena & Jenny Morales, 2022. "Dynamic Surgical Waiting List Methodology: A Networking Approach," Mathematics, MDPI, vol. 10(13), pages 1-23, July.
    9. Tariq Ahamed Ahanger & Fadl Dahan & Usman Tariq & Imdad Ullah, 2022. "Quantum Inspired Task Optimization for IoT Edge Fog Computing Environment," Mathematics, MDPI, vol. 11(1), pages 1-28, December.
    10. Ilja Nastjuk & Simon Trang & Elpiniki I. Papageorgiou, 2022. "Smart cities and smart governance models for future cities," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 1917-1924, December.
    11. Yehia Ibrahim Alzoubi & Ahmad Al-Ahmad & Hasan Kahtan & Ashraf Jaradat, 2022. "Internet of Things and Blockchain Integration: Security, Privacy, Technical, and Design Challenges," Future Internet, MDPI, vol. 14(7), pages 1-48, July.
    12. Vijendra Kumar & Hazi Md. Azamathulla & Kul Vaibhav Sharma & Darshan J. Mehta & Kiran Tota Maharaj, 2023. "The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management," Sustainability, MDPI, vol. 15(13), pages 1-33, July.
    13. Amit Sundas & Sumit Badotra & Salil Bharany & Ahmad Almogren & Elsayed M. Tag-ElDin & Ateeq Ur Rehman, 2022. "HealthGuard: An Intelligent Healthcare System Security Framework Based on Machine Learning," Sustainability, MDPI, vol. 14(19), pages 1-16, September.

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