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Smart City Technologies for Next Generation Healthcare

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Data-Driven Mining, Learning and Analytics for Secured Smart Cities

Abstract

A smart city is a municipal area aimed at managing the expanding urbanization through a vast exchange of information using technologies. It is the concept of bringing technology, society, and government together to refine the quality of the living standards of their citizens. As the number of urban areas is increasing day by day and the citizens are becoming ambitious for a living style with a secured environment, the demand for a proper and safer healthcare system with tech connectivity is increasing rapidly. Therefore, the next-generation smarter healthcare receives considerable attention from academics, governments, businesses, and the health care sector through the growth of information and communication technology infrastructure. From the personal level to community level, information and communication technology driven healthcare is becoming the ultimate role player. In this study, we have briefly described the overview of a smart city and its components. Among all these components, smart healthcare is our target component for further studies. We presented current informative views regarding next-generation healthcare system modules such as data collection through mobile sensors and ambient sensors; usability of data processing using edge computing and cloud computing applications; privacy and security of data; and connectivity with other ‘Smart City’ services like smart infrastructure, medical waste management, health education. Finally, we discussed underlying opportunities and challenges so that a path towards the optimization of current healthcare technologies is disclosed.

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References

  1. Afsana F, Mamun SA, Kaiser MS, Ahmed MR (2015) Outage capacity analysis of cluster-based forwarding scheme for body area network using nano-electromagnetic communication. In: 2015 2nd international conference on electrical information and communication technologies (EICT), pp 383–388. https://doi.org/10.1109/EICT.2015.7391981

  2. Akhund TMNU et al (2018) Adeptness: Alzheimer’s disease patient management system using pervasive sensors-early prototype and preliminary results. In: International conference on brain informatics, pp. 413–422. Springer

    Google Scholar 

  3. Al Mamun A, Jahangir MUF, Azam S, Kaiser MS, Karim A (2021) A combined framework of interplanetary file system and blockchain to securely manage electronic medical records. In: Proceedings of international conference on trends in computational and cognitive engineering, pp 501–511. Springer

    Google Scholar 

  4. Al Nahian MJ et al (2020) Towards artificial intelligence driven emotion aware fall monitoring framework suitable for elderly people with neurological disorder. In: Mahmud M, Vassanelli S, Kaiser MS, Zhong N (eds) Brain informatics. Springer International Publishing, Cham, Lecture notes in computer science, pp 275–286

    Google Scholar 

  5. Asif-Ur-Rahman M et al (2018) Toward a heterogeneous mist, fog, and cloud-based framework for the internet of healthcare things. IEEE Internet Things J 6(3):4049–4062

    Article  Google Scholar 

  6. Atherton J (2011) Development of the electronic health record. AMA J Ethics 13(3):186–189

    Article  Google Scholar 

  7. Bhuyan SS, Kim H, Isehunwa OO, Kumar N, Bhatt J, Wyant DK, Kedia S, Chang CF, Dasgupta D (2017) Privacy and security issues in mobile health: current research and future directions. Health Policy Technol 6(2):188–191. https://www.sciencedirect.com/science/article/pii/S2211883717300047

  8. Bibri SE, Krogstie J (2017) On the social shaping dimensions of smart sustainable cities: a study in science, technology, and society. Sustain Cities Soc 29:219–246

    Article  Google Scholar 

  9. Biswas S, Akhter T, Kaiser M, Mamun S et al (2014) Cloud based healthcare application architecture and electronic medical record mining: an integrated approach to improve healthcare system. In: 2014 ICCIT, pp 286–291. IEEE

    Google Scholar 

  10. Carrasco-Saez JL, Careaga Butter M, Badilla-Quintana MG (2017) The new pyramid of needs for the digital citizen: a transition towards smart human cities. Sustainability 9(12):2258

    Article  Google Scholar 

  11. Chakraborty C Smart medical data sensing and iot systems design in healthcare. IGI Global. www.igi-global.com/book/smart-medical-data-sensing-iot/227593. publication Title: https://services.igi-global.com/resolvedoi/resolve.aspx?, https://doi.org/10.4018/978-1-7998-0261-7

  12. Chakraborty C (2021) Advanced classification techniques for healthcare analysis. IGI Global. www.igi-global.com/book/advanced-classification-techniques-healthcare-analysis/210213

  13. Chakraborty C, Banerjee A, Kolekar MH, Garg L, Chakraborty B (eds) (2021) Internet of things for healthcare technologies, voice In settings. In: Studies in big data. Springer Singapore. https://doi.org/10.1007/978-981-15-4112-4, https://www.springer.com/gp/book/9789811541117

  14. Chui KT, Alhalabi W, Pang SSH, Pablos POD, Liu RW, Zhao M (2017) Disease diagnosis in smart healthcare: innovation, technologies and applications. Sustainability 9(12):2309. https://doi.org/10.3390/su9122309, https://www.mdpi.com/2071-1050/9/12/2309. Publisher: Multidisciplinary Digital Publishing Institute

  15. Cook DJ, Duncan G, Sprint G, Fritz RL (2018) Using smart city technology to make healthcare smarter. Proc IEEE 106(4):708–722

    Article  Google Scholar 

  16. Farhin F, Kaiser MS, Mahmud M (2021) Secured smart healthcare system: blockchain and bayesian inference based approach. In: Proceedings of international conference on trends in computational and cognitive engineering, pp 455–465. Springer

    Google Scholar 

  17. Fleming NS et al (2014) The impact of electronic health records on workflow and financial measures in primary care practices. Health Serv Res 49(1pt2):405–420

    Google Scholar 

  18. Glasmeier A et al (2015) Thinking about smart cities. Camb J Reg Econ Soc 8(1):3–12

    Article  Google Scholar 

  19. Gouveia JP, Seixas J, Giannakidis G (2016) Smart city energy planning: integrating data and tools. In: Proceedings of the 25th international conference companion on world wide web, pp 345–350

    Google Scholar 

  20. Harrison C, Eckman B, Hamilton R, Hartswick P, Kalagnanam J, Paraszczak J, Williams P (2010) Foundations for smarter cities. IBM J Res Dev 54(4):1–16

    Article  Google Scholar 

  21. Hern´andez-Mun˜oz et al (2011) Smart cities at the forefront of the future internet. In: Future internet assembly, pp 447–462

    Google Scholar 

  22. Istepanian R, Laxminarayan S, Pattichis CS (2007) M-health: emerging mobile health systems. Springer Science & Business Media

    Google Scholar 

  23. Jensen PB, Jensen LJ, Brunak S (2012) Mining electronic health records: towards better research applications and clinical care. Nat Rev Genet 13(6):395–405

    Article  Google Scholar 

  24. Jesmin S, Kaiser MS, Mahmud M (2020) Artificial and Internet of Healthcare Things Based Alzheimer Care During COVID 19. In: Mahmud M, Vassanelli S, Kaiser MS, Zhong N (eds) Brain informatics. Springer International Publishing, Cham, Lecture notes in computer science, pp 263–274

    Chapter  Google Scholar 

  25. Kaiser MS et al (2021) iworksafe: towards healthy workplaces during covid-19 with an intelligent health app for industrial settings. IEEE Access 9:13814–13828. https://doi.org/10.1109/ACCESS.2021.3050193

    Article  Google Scholar 

  26. Kaiser MS, Al Mamun S, Mahmud M, Tania MH (2020) Healthcare robots to combat covid-19. In: COVID-19: prediction, decision-making, and its impacts, pp 83–97. Springer

    Google Scholar 

  27. Kaiser MS et al (2016) A neuro-fuzzy control system based on feature extraction of surface electromyogram signal for solar-powered wheelchair. Cogn Comput 8(5):946–954

    Article  Google Scholar 

  28. Kaiser MS et al (2021) 6g access network for intelligent internet of healthcare things: opportunity, challenges, and research directions. In: Proceedings of international conference on trends in computational and cognitive engineering. pp 317–328. Springer

    Google Scholar 

  29. Kaiser MS et al (2017) Advances in crowd analysis for urban applications through urban event detection. IEEE Trans ITS 19(10):3092–3112

    Google Scholar 

  30. Khanam S et al (2014) Improvement of RFID tag detection using smart antenna for tag based school monitoring system. In: 2014 ICEEICT, pp 1–6. IEEE

    Google Scholar 

  31. Kourtit K, Nijkamp P (2012) Smart cities in the innovation age. The Eur J Soc Sci Res 25(2):93–95

    Article  Google Scholar 

  32. Mahmud M, Kaiser MS, Hussain A, Vassanelli S (2018) Applications of deep learning and reinforcement learning to biological data. IEEE Trans Neural Netw Learn Syst 29(6):2063–2079. https://doi.org/10.1109/TNNLS.2018.2790388

    Article  MathSciNet  Google Scholar 

  33. Mahmud M, Kaiser MS (2020) Machine learning in fighting pandemics: a covid-19 case study. In: COVID-19: prediction, decision-making, and its impacts, pp 77–81. Springer

    Google Scholar 

  34. Mahmud M, Kaiser MS, McGinnity TM, Hussain A (2020) Deep learning in mining biological data. Cogn Comput 1–33

    Google Scholar 

  35. Mahmud M et al (2018) A brain-inspired trust management model to assure security in a cloud based iot framework for neuroscience applications. Cogn Comput 10(5):864–873

    Article  Google Scholar 

  36. Noor MBT et al (2019) Detecting neurodegenerative disease from MRI: a brief review on a deep learning perspective. In: International conference on brain informatics, pp 115–125. Springer

    Google Scholar 

  37. Pandian PS, Mohanavelu K, Safeer KP, Kotresh TM, Shakunthala DT, Gopal P, Padaki VC (2008) Smart vest: wearable multi-parameter remote physiological monitoring system. Med Eng Phys 30(4):466–477. https://doi.org/10.1016/j.medengphy.2007.05.014, https://www.sciencedirect.com/science/article/pii/S1350453307000975

  38. Paul MC, Sarkar S, Rahman MM, Reza SM, Kaiser MS (2016) Low cost and portable patient monitoring system for e-health services in Bangladesh. In: 2016 international conference on computer communication and informatics (ICCCI), pp 1–4. IEEE

    Google Scholar 

  39. Rahman S, Al Mamun S, Ahmed MU, Kaiser MS (2016) Phy/mac layer attack detection system using neuro-fuzzy algorithm for iot network. In: 2016 ICEEOT, pp 2531–2536. IEEE

    Google Scholar 

  40. Rashid TA, Chakraborty C, Fraser K (2020) Advances in telemedicine for health monitoring: technologies. Des Appl. IET Digital Library. https://doi.org/10.1049/PBHE023E, https://digital-library.theiet.org/content/books/he/pbhe023e

  41. Sardini E, Serpelloni M (2014) T-shirt for vital parameter monitoring. In: Baldini F et al (eds) Sensors. Lecture notes in electrical engineering. Springer, New York, NY, pp 201–205

    Google Scholar 

  42. Silva BM, Rodrigues JJ, de la Torre Díez I, López-Coronado M, Saleem K (2015) Mobile-health: a review of current state in 2015. J Biomed Inf 56:265–272

    Google Scholar 

  43. Sprint G, Cook DJ, Shelly R, Schmitter-Edgecombe M et al (2016) Using smart homes to detect and analyze health events. Computer 49(11):29–37

    Article  Google Scholar 

  44. Sumi AI et al (2018) Fassert: a fuzzy assistive system for children with autism using internet of things. In: International conference on brain informatics. pp 403–412. Springer

    Google Scholar 

  45. Sánchez L, Elicegui I, Cuesta J, Muñoz L, Lanza J (2013) Integration of utilities infrastructures in a future internet enabled smart city framework. Sensors (Basel, Switzerland) 13(11):14438–14465. https://doi.org/10.3390/s131114438, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3871114/

  46. Visvizi A, Lytras MD, Damiani E, Mathkour H (2018) Policy making for smart cities: innovation and social inclusive economic growth for sustainability. J Sci Technol Policy Manage

    Google Scholar 

  47. Wang X, Sontag D, Wang F (2014) Unsupervised learning of disease progression models. In: Proceedings of ACM SIGKDD, pp 85–94

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Information Technology, Jahangirnagar University, Savar, Dhaka, 1342, Bangladesh

    Tahmina Harun Faria, M. Shamim Kaiser & Shamim Al Mamun

  2. Department of EEE, American International University-Bangladesh, Dhaka, 1229, Bangladesh

    Chowdhury Akram Hossian

  3. Department of Computer Science, Nottingham Trent University, Clifton, Nottingham, NG11 8NS, UK

    Mufti Mahmud

  4. Department of Electronics & Communication Engineering, Birla Institute of Technology, Ranchi, Jharkhand, India

    Chinmay Chakraborty

Authors
  1. Tahmina Harun Faria
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  2. M. Shamim Kaiser
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  3. Chowdhury Akram Hossian
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  4. Mufti Mahmud
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  5. Shamim Al Mamun
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  6. Chinmay Chakraborty
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Corresponding author

Correspondence to M. Shamim Kaiser .

Editor information

Editors and Affiliations

  1. Birla Institute of Technology, Mesra, Jharkhand, India

    Chinmay Chakraborty

  2. Computer Science, Electrical Engineering, Western Norway University of Applied Sci, Bergen, Norway

    Jerry Chun-Wei Lin

  3. Casuarina Campus, Purple 12.3.6, Charles Darwin University, Darwin, NT, Australia

    Mamoun Alazab

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Faria, T.H., Shamim Kaiser, M., Hossian, C.A., Mahmud, M., Al Mamun, S., Chakraborty, C. (2021). Smart City Technologies for Next Generation Healthcare. In: Chakraborty, C., Lin, J.CW., Alazab, M. (eds) Data-Driven Mining, Learning and Analytics for Secured Smart Cities. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-72139-8_12

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  • DOI: https://doi.org/10.1007/978-3-030-72139-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-72138-1

  • Online ISBN: 978-3-030-72139-8

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