A Novel Approach Towards Using Big Data and IoT for Improving the Efficiency of m-Health Systems

  • Kamta Nath MishraEmail author
  • Chinmay Chakraborty
Part of the Studies in Computational Intelligence book series (SCI, volume 875)


The application of big data in healthcare is growing at tremendous speed and many new discoveries and methodologies are published in the last decade in this field. Big data technologies are effectively being used in biomedical informatics and healthcare research. The mobile phones, sensors, patients, hospitals, researchers, and other organizations are generating a huge amount of healthcare data in these days. The large amounts of clinical data are being continuously generated by medical organizations and are used for detecting and curing new diseases. The actual test in m-health systems is the way to discover, gather, examine and administer the information to build a person’s life better and easier, by predicting the life dangers at early stages. A number of technologies have been developed by researchers which can decrease on which overheads for the evasion of overall management of chronic illnesses. The medical devices that continually monitor health system indicators or tracking of online health data in real-time environment as and when patient self-administers physiotherapy are now in huge demand. Many intelligent patients have now started using mobile applications (apps) to manage different daily life-related health needs on regular basis because of easy availability of high-speed Internet connections on smartphone and cybercafes. These devices and mobile applications are now progressively more used and integrated with telemedicine and telehealth via the Internet of Things (IoT). In this chapter, the authors have discussed the applications and challenges of biomedical big data. Further, this chapter presents novel approaches to advancements in healthcare systems using big data technologies and distributed computing systems.


Big data technologies Clinical informatics Healthcare systems Imaging informatics Public health informatics Medical internet of things 


  1. 1.
    Internet of Things (IoT). (2019). Number of connected devices worldwide from 2012 to 2020 (in billions). Available:
  2. 2.
    Institute of Health Metrics and Evaluation. (2015). Available:
  3. 3.
    Andriopoulou F, Dagiuklas T, Orphanoudakis T (2017) Integrating IoT and fog computing for healthcare service delivery. Springer International Publishing, SwitzerlandCrossRefGoogle Scholar
  4. 4.
    Dong B, Yang J, Ma Y, Zhang X (2016) Medical monitoring model of internet of things based on the adaptive threshold difference algorithm. Int J Multimedia and Ubiquitous EngGoogle Scholar
  5. 5.
    Abu KE (2017) Analytics and telehealth emerging technologies: the path forward for smart primary care environment. J Healthc Comm 2(S1):67Google Scholar
  6. 6.
    Chinmay C (2019) Mobile health (m-Health) for tele-wound monitoring. Mobile Health Applications for Quality Healthcare Delivery 5:98–116. Scholar
  7. 7.
    Chinmay C, Gupta B, Ghosh SK (2013) A review on telemedicine-based WBAN framework for patient monitoring. Int J Telemed e-Health 19(8):619–626CrossRefGoogle Scholar
  8. 8.
    Chakraborty C, Gupta B, Ghosh SK (2014) Mobile metadata assisted community database of chronic wound. International Journal of Wound Medicine 6:34–42CrossRefGoogle Scholar
  9. 9.
    Redowan M, Fernando LK, Rajkumar B (2018) Cloud-fog interoperability in IoT-enabled healthcare solutions. In 19th ACM International Conference on Distributed Computing and Networking (pp. 1–10). January 4–7, 2018Google Scholar
  10. 10.
    Ahmad M, Amin MB, Hussain S, Kang BH, Cheong T, Lee S (2016) Health fog: a novel framework for health and wellness applications. J Supercomp 72(10):3677–3695CrossRefGoogle Scholar
  11. 11.
    Rahmani AM, Gia TN, Negash B, Anzanpour A, Azimi I, Jiang M, Liljeberg P (2017) Exploiting smart e-health gateways at the edge of healthcare internet-of-things: a fog computing approach. Future Generation Computer SystemsGoogle Scholar
  12. 12.
    Fazio M, Celesti A, MÃąrquez FG, Glikson A, Villari M (2015) Exploiting the FIWARE cloud platform to develop a remote patient monitoring system. In Proceedings of the IEEE Symposium on Computers and Communication (ISCC) (pp. 264–270).
  13. 13.
    Hassanalieragh M, Page A, Soyata T, Sharma G, Aktas M, Mateos G, Kantarci B, Andreescu S (2015) Health monitoring and management using internet-of-things (IoT) sensing with cloud-based processing: opportunities and challenges. In Proceedings of the IEEE International Conference on Services Computing (pp. 285–292)Google Scholar
  14. 14.
    Mahmud R, Ramamohanarao K, Buyya R (2017) Fog computing: a taxonomy, survey and future directions. In Di Martino B, Yang L, Li, K-C, Antonio E (eds) Internet of everything: algorithms, methodologies, technologies and perspectives (pp. 103–130). Springer, BerlinGoogle Scholar
  15. 15.
    Gia TN, Jiang M, Rahmani AM, Westerlund T, Liljeberg P, Tenhunen H (2015) In Proceedings of the IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (pp. 356–363)Google Scholar
  16. 16.
    Doukas C, Maglogiannis I (2012) Bringing IoT and cloud computing towards pervasive healthcare. In Proceedings of the Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (pp. 922–926)Google Scholar
  17. 17.
    Tsiachri Renta P, Sotiriadis S, Petrakis EG (2017) Healthcare sensor data management on the cloud. In Proceedings of the 2017 Workshop on Adaptive Resource Management and Scheduling for Cloud Computing (ARMS-CC ’17) (pp. 25–30). ACMGoogle Scholar
  18. 18.
    Mahmud, S., Iqbal, R., & Doctor, F. (2016). Cloud enabled data analytics and visualization framework for health-shocks prediction. Future Generation Computer Systems (Special Issue on Big Data in the Cloud), 65(Supplement C), 169–181Google Scholar
  19. 19.
    Chen M, Qian Y, Chen J, Hwang K, Mao S, Hu L (2017) Privacy protection and intrusion avoidance for cloudlet-based medical data sharing. IEEE Transactions on Cloud Computing 99:1Google Scholar
  20. 20.
    Zhang Y, Qiu M, Tsai CW, Hassan MM, Alamri A (2017) Health-CPS: healthcare cyber-physical system assisted by cloud and big data. IEEE Syst J 11(1):88–95CrossRefGoogle Scholar
  21. 21.
    Vijay BP, Pallavi K, Abdulsalam Y, Parisa P, Shervin S, Ali ANS (2017) An intelligent cloud-based data processing broker for mobile e-health multimedia applications. Future Gener Comput Syst 66(Supplement C):71–86Google Scholar
  22. 22.
    Jindal V (2016) Integrating mobile and cloud for PPG signal selection to monitor heart rate during intensive physical exercise. In Proceedings of International Conference on Mobile Software Engineering and Systems (MOBILESoft’16) (pp. 36–37). ACMGoogle Scholar
  23. 23.
    Muhammad G, Rahman SMM, Alelaiwi A, Alamri A (2017) Smart health solution integrating IoT and cloud: a case study of voice pathology monitoring. IEEE Comm Mag 55(1):69–73CrossRefGoogle Scholar
  24. 24.
    Gupta PK, Maharaj BT, Malekian R (2017) A novel and secure IoT based cloud centric architecture to perform predictive analysis of users activities in sustainable health centres. Multimedia Tools Appl 76(18):18489–18512CrossRefGoogle Scholar
  25. 25.
    Shamim HM, Ghulam M (2016) Cloud-assisted industrial internet of things (IIoT)—Enabled framework for health monitoring. Computer Networks, 101(Supplement C), 192–202. Industrial Technologies and Applications for the Internet of ThingsGoogle Scholar
  26. 26.
    Nguyen GT, Jiang M, Sarker VK, Rahmani AM, Westerlund T, Liljeberg P, Tenhunen H (2017) Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes. In Proceedings of 13th International Wireless Communications and Mobile Computing Conference (IWCMC) (pp. 1765–1770)Google Scholar
  27. 27.
    Chakraborty S, Bhowmick S, Talaga P, Agrawal DP (2016) Fog networks in healthcare application. In Proceedings of 13th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS) (pp. 386–387)Google Scholar
  28. 28.
    Dubey H, Yang J, Constant N, Amiri AM, Yang Q, Makodiya K (2015) Fog data: enhancing telehealth big data through fog computing. In Proceedings of the ASE BigData & SocialInformatics 2015 (ASE BD&SI’15). ACM, New York, Article 14, 6Google Scholar
  29. 29.
    Negash B, Gia TN, Anzanpour A, Azimi I, Jiang M, Westerlund T, Rahmani AM, Liljeberg P, Tenhunen H (2018) Leveraging fog computing for healthcare IoT (pp. 145–169). Springer International Publishing, ChamGoogle Scholar
  30. 30.
    Lee C, Yeung C, Cheng M (2015) Research on IoT based cyber physical system for industrial big data analytics. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) (pp. 1855–1859). IEEEGoogle Scholar
  31. 31.
    Rizwan P, Suresh K, Babu MR (2016) Real-time smart traffic management system for smart cities by using internet of things and big data. In International Conference on Emerging Technological Trends (ICETT) (pp. 1–7). IEEEGoogle Scholar
  32. 32.
    Zhang Q, Zhang X, Zhang Q, Shi W, Zhong H (2016) Firework: big data sharing and processing in collaborative edge environment. In Fourth IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb) (pp. 20–25). IEEEGoogle Scholar
  33. 33.
    Rathore MM, Ahmad A, Paul A (2016) Iot-based smart city development using big data analytical approach. In IEEE International Conference on Automatica (ICA-ACCA) (pp. 1–8). IEEEGoogle Scholar
  34. 34.
    Kamta NM, Chakraborty C (2019) A novel approach toward enhancing the quality of life in smart cities using clouds and IoT-based technologies. Digital Twin Technologies and Smart Cities, Internet of Things (Technology, Communications and Computing) (pp. 19–35). Scholar
  35. 35.
    Ahlgren B, Hidell M, Ngai ECH (2016) Internet of things for smart cities: Interoperability and open data. IEEE Internet Computing 20(6):52–56CrossRefGoogle Scholar
  36. 36.
    Sezer OB, Dogdu E, Ozbayoglu M, Onal A (2016) An extended iot framework with semantics, big data, and analytics. In IEEE International Conference on Big Data (Big Data) (pp. 1849–1856). IEEEGoogle Scholar
  37. 37.
    Cheng B, Papageorgiou A, Cirillo F, Kovacs E (2015) Geelytics: geo-distributed edge analytics for large scale iot systems based on dynamic topology. In IEEE 2nd World Forum on Internet of Things (WF-IoT) (pp. 565–570). IEEEGoogle Scholar
  38. 38.
    Wang H, Osen OL, Li G, Li W, Dai HN, Zeng W (2015) Big data and industrial internet of things for the maritime industry in northwestern Norway. In TENCON 2015-2015 IEEE Region 10 Conference (pp. 1–5). IEEEGoogle Scholar
  39. 39.
    Perez JL, Carrera D (2015) Performance characterization of the servioticy api: an iot-as-a-service data management platform. In IEEE First International Conference on Big Data Computing Service and Applications (Big Data Service) (pp. 62–71). IEEEGoogle Scholar
  40. 40.
    Villari M, Celesti A, Fazio M, Puliafito A (2014) Alljoyn Lambda: an architecture for the management of smart environments in IoT. In International Conference on Smart Computing Workshops (SMARTCOMP Workshops) (pp. 9–14). IEEEGoogle Scholar
  41. 41.
    Jara AJ, Genoud D, Bocchi Y (2014) Big data for cyber physical systems: an analysis of challenges, solutions and opportunities. In Eighth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS) (pp. 376–380). IEEEGoogle Scholar
  42. 42.
    Ding Z, Gao X, Xu J, Wu H (2013) IOT-statisticDB: A general statistical database cluster mechanism for big data analysis in the internet of things. In Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing (pp. 535–543). IEEEGoogle Scholar
  43. 43.
    Vuppalapati C, Ilapakurti A, Kedari S (2016) The role of big data in creating sense ehr, an integrated approach to create next generation mobile sensor and wearable data driven electronic health record (ehr). In IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService) (pp. 293–296). IEEEGoogle Scholar
  44. 44.
    Ahmad A, Rathore MM, Paul A, Rho S (2016) Defining human behaviors using big data analytics in social internet of things. In IEEE 30th International Conference on Advanced Information Networking and Applications (AINA) (pp. 1101–1107). IEEEGoogle Scholar
  45. 45.
    Ahmed E, Rehmani MH (2017) Introduction to the special section on social collaborative internet of things. Computers & Electrical Engineering, 382–384Google Scholar
  46. 46.
    Arora D, Li KF, Loffler A (2016) Big data analytics for classification of network enabled devices. In 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA) (pp. 708–713). IEEEGoogle Scholar
  47. 47.
    Yen LL, Zhou G, Zhu W, Bastani F, Hwang SY (2015) A smart physical world based on service technologies, big data, and game-based crowd sourcing. In IEEE International Conference on Web Services (ICWS) (pp. 765–772). IEEEGoogle Scholar
  48. 48.
    Wassnaa A (2015) Privacy and security issues in IoT healthcare applications for the disabled users. A survey (pp. 1–40). Master Degree Thesis, Western Michigan UniversityGoogle Scholar
  49. 49.
    Santucci G (2011) From internet to data to internet of things. In Proceedings of the International Conference on Future Trends of the Internet. Journal of Wireless Personal Communications, 58(1):49–69CrossRefGoogle Scholar
  50. 50.
    Atzori L, Lera A, Morabito G (2010) The internet of things: asurvey. Comput Netw 54(15):1–17CrossRefGoogle Scholar
  51. 51.
    Hussain S, Schaffner S, Moseychuck D (2009) Applications of wireless sensor networks and RFID in a smart home environment. In IEEE 7th Annual Conference on Communication Networks and Services Research, Moncton, NB (pp. 153–157)Google Scholar
  52. 52.
    Jia X, Feng Q, Fan T, Lei Q (2012) RFID technology and its applications in internet of things (IoT). In IEEE 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet), Yichang (pp. 1282–1285), April 2012Google Scholar
  53. 53.
    Annette CN (2016) Internet & audiology—ehealth in the large perspective. Vingstedkursus (pp. 1–52). Erikholm Research Centre, Part of Oticon, August 25–26, 2016Google Scholar
  54. 54.
    Milovanovic DA, Bojkovic ZS (2017) New generation IoT-based healthcare applications: requirements and recommendations. Int J Syst Appl Eng Devel 11:17–20Google Scholar
  55. 55.
    Higinio M, David G, Rafael MT, Jorge A, Julian S (2017) An IoT-based computational framework for healthcare monitoring in mobile environments. Sensors Journal 17:1–25CrossRefGoogle Scholar
  56. 56.
    Christos P, Christoph T, Nikolaos G, Pantelis A, Nigel J, Bin Z, Guixia K, Cindy F, Clara L, Chunxue B, Kostas D, Katarzyna W, Panayiotis K (2016) A new generation of e-health systems powered by 5G, WWRF WG e/m-health and wearable vertical industries platform. Wireless World Research Forum, White Paper (pp. 1–37)Google Scholar
  57. 57.
    Joyia GJ, Liaqat RM, Farooq A, Rehman S (2017) Internet of medical things (IOMT): Applications, benefits and future challenges in healthcare domain. J Comm 12(4):240–247Google Scholar
  58. 58.
    Patan R, Rajasekhara BM, Suresh K (2017) Design and development of low investment smart hospital using internet of things through innovative approaches. Biomedical Research Journal 28(11):4979–4985Google Scholar
  59. 59.
    Kubo (2014) The research of IoT based on RFID technology. In IEEE 7th International Conference on Intelligent Computation Technology and Automation, China, Changsha (pp. 832–835)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Science and EngineeringBirla Institute of TechnologyRanchiIndia
  2. 2.Electronics and Communication EngineeringBirla Institute of TechnologyRanchiIndia

Personalised recommendations