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AI and IoT Enabled Smart Hospital Management Systems

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Data Science in Societal Applications

Part of the book series: Studies in Big Data ((SBD,volume 114))

Abstract

With the rapid increase in the advancement of different methods and technologies, efficient and optimized solutions have been introduced for providing support in the healthcare sector. With the steady increase in the population, smart healthcare system requires optimized data management algorithms for storing various data that is collected from various applications and sensors. For obtaining these objectives, integration of such modern techniques including artificial intelligence, the Internet of Things, machine learning, etc. becomes a mandatory step in developing smart hospital-based services. Artificial intelligence-based robots for surgery and diagnoses of various medical imaging are providing better results over time for smart hospital systems. IoT-based temperature management systems, sensors for checking the health of instruments, and many more applications are available for the smart hospital management system. Researchers are now becoming more penchant toward the smart hospitals, cities, etc. based development domains and have proposed various architectures which contribute to the same. These modern techniques are solving major chunks of problems in a faster way by providing good results and more facilities when compared to aged techniques. In this paper, the main focus is to provide various aspects and factors of AI and IoT-based smart hospital systems and the role of AIoT in the growth of the modern world as a combination of these niche areas is giving outstanding results in the field of healthcare. We also provide various hurdles which are encountered during the development of smart hospital management systems.

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References

  1. Xia, F., Yang, L.T., Wang, L., Vinel, A.: Internet of things. Int. J. Commun. Syst. 25(9), 1101 (2012)

    Article  Google Scholar 

  2. Nilsson, N.J.: The Quest for Artificial Intelligence. Cambridge University Press (2009)

    Book  Google Scholar 

  3. Hashimoto, D.A., Rosman, G., Rus, D., Meireles, O.R.: Artificial intelligence in surgery: promises and perils. Ann. Surg. 268(1), 70 (2018)

    Article  Google Scholar 

  4. Pineau, J., Montemerlo, M., Pollack, M., Roy, N., Thrun, S.: Towards robotic assistants in nursing homes: challenges and results. Robot. Auton. Syst. 42(3–4), 271–281 (2003)

    Article  MATH  Google Scholar 

  5. Schmidt-, U., Waldstein, S.M., Klimscha, S., Sadeghipour, A., Hu, X., Gerendas, B.S., Bogunović, H.: Prediction of individual disease conversion in early AMD using artificial intelligence. Invest. Ophthalmol. Vis. Sci. 59(8), 3199–3208 (2018)

    Article  Google Scholar 

  6. Ghosh, A., Chakraborty, D., Law, A.: Artificial intelligence in Internet of Things. CAAI Trans. Intell. Technol. 3(4), 208–218 (2018)

    Article  Google Scholar 

  7. Ramakrishnan, S., Nagarkar, K., DeGennaro, M., Srihari, M., Courtney, A. K., Emick, F.: A study of the CT scan area of a healthcare provider. In: Proceedings of the 2004 Winter Simulation Conference, vol. 2, pp. 2025–2031. IEEE (2004)

    Google Scholar 

  8. Rodríguez-Ruiz, A., Krupinski, E., Mordang, J.J., Schilling, K., Heywang-Köbrunner, S.H., Sechopoulos, I., Mann, R.M.: Detection of breast cancer with mammography: effect of an artificial intelligence support system. Radiology 290(2), 305–314 (2019)

    Article  Google Scholar 

  9. Borrelli, P., Ly, J., Kaboteh, R., Ulén, J., Enqvist, O., Trägårdh, E., Edenbrandt, L.: AI-based detection of lung lesions in [18 F] FDG PET-CT from lung cancer patients. EJNMMI Phys. 8(1), 1–11 (2021)

    Article  Google Scholar 

  10. Chen, M., Zhang, B., Topatana, W., Cao, J., Zhu, H., Juengpanich, S., Cai, X.: Classification and mutation prediction based on histopathology H&E images in liver cancer using deep learning. NPJ Precis. Oncol. 4(1), 1–7 (2020)

    Article  Google Scholar 

  11. Yang, C.H.H., Huang, J.H., Liu, F., Chiu, F.Y., Gao, M., Lyu, W., Tegner, J.: A novel hybrid machine learning model for auto-classification of retinal diseases (2018). arXiv preprint arXiv:1806.06423

  12. Priya, R., Aruna, P.: Diagnosis of diabetic retinopathy using machine learning techniques. ICTACT J. Soft Comput. 3(4), 563–575 (2013)

    Article  Google Scholar 

  13. Lakhani, P., Sundaram, B.: Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks. Radiology 284(2), 574–582 (2017)

    Article  Google Scholar 

  14. Alharbe, N.: ‘A fuzzy-Delphi based decision-making process for measuring usable-security of Web based smart hospital management system. ICIC Express Lett. 14(1), 15–21 (2020)

    Google Scholar 

  15. Lakhoua, N.: Review on smart hospital management system technologies. Res. Sci. Today 1, 187–194 (2019)

    Google Scholar 

  16. Lin, C.L., Chen, J.K., Ho, H.H.: BIM for smart hospital management during COVID-19 using MCDM. Sustainability 13(11), 6181 (2021)

    Article  Google Scholar 

  17. Kumar, J.N.A., Suresh, S.: A proposal of smart hospital management using hybrid cloud, IoT, ML, and AI. In: 2019 International Conference on Communication and Electronics Systems (ICCES), pp. 1082–1085). IEEE (2019)

    Google Scholar 

  18. Bender, B.G., Chrystyn, H., Vrijens, B.: Smart pharmaceuticals. In: Health 4.0: How virtualization and big data are revolutionizing healthcare, pp. 61–90). Springer, Cham (2017)

    Google Scholar 

  19. Islam, M.M., Rahaman, A., Islam, M.R.: Development of smart healthcare monitoring system in IoT environment. SN Comput. Sci. 1, 1–11 (2020)

    Article  Google Scholar 

  20. Kumar, A., Dhanagopal, R., Albreem, M.A., Le, D.N.: A comprehensive study on the role of advanced technologies in 5G based smart hospital. Alex. Eng. J. 60(6), 5527–5536 (2021)

    Article  Google Scholar 

  21. Amudha, S., Murali, M.: Enhancement of IoT-based smart hospital system survey paper. In: Edge Computing and Computational Intelligence Paradigms for the IoT, pp. 238–261. IGI Global (2019)

    Google Scholar 

  22. Afferni, P., Merone, M., Soda, P. Hospital 4.0 and its innovation in methodologies and technologies. In: 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), pp. 333–338). IEEE (2018)

    Google Scholar 

  23. Jordan, M.I., Mitchell, T.M.: Machine learning: trends, perspectives, and prospects. Science 349(6245), 255–260 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  24. Khare, S., Gourisaria, M.K., Harshvardhan, G.M., Joardar, S., Singh, V.: Real estate cost estimation through data mining techniques. In: IOP Conference Series: Materials Science and Engineering, vol. 1099, No. 1, p. 012053. IOP Publishing (2021)

    Google Scholar 

  25. Alom, M.Z., Taha, T.M., Yakopcic, C., Westberg, S., Sidike, P., Nasrin, M.S., Asari, V.K.: A state-of-the-art survey on deep learning theory and architectures. Electronics 8(3), 292 (2019)

    Article  Google Scholar 

  26. Gourisaria, M.K., Das, S., Sharma, R., Rautaray, S.S., Pandey, M.: A deep learning model for malaria disease detection and analysis using deep convolutional neural networks. Int. J. Emerg. Technol. 11(2), 699–704 (2020)

    Google Scholar 

  27. Sahu, A., Harshvardhan, G.M., Gourisaria, M.K.: A dual approach for credit card fraud detection using neural network and data mining techniques. In: 2020 IEEE 17th India Council International Conference (INDICON), pp. 1–7. IEEE (2020)

    Google Scholar 

  28. Wu, Y.C., Feng, J.W.: Development and application of artificial neural network. Wireless Pers. Commun. 102(2), 1645–1656 (2018)

    Article  Google Scholar 

  29. Khemphila, A., Boonjing, V.: Heart disease classification using neural network and feature selection. In: 2011 21st International Conference on Systems Engineering, pp. 406–409. IEEE (2011)

    Google Scholar 

  30. Pezeshki, Z., Tafazzoli-Shadpour, M., Nejadgholi, I., Mansourian, A., Rahbar, M.: Model of cholera forecasting using artificial neural network in Chabahar City, Iran. Int. J. Enteric. Pathog. 4(1), 1–8 (2016)

    Article  Google Scholar 

  31. Sun, R.: Optimization for deep learning: theory and algorithms (2019). arXiv preprint arXiv:1912.08957

  32. Mohsen, H., El-, E.S.A., El-, E.S.M., Salem, A.B.M.: Classification using deep learning neural networks for brain tumors. Futur. Comput. Inform. J. 3(1), 68–71 (2018)

    Article  Google Scholar 

  33. Goyal, M., Hassanpour, S.: A refined deep learning architecture for diabetic foot ulcers detection (2020). arXiv preprint arXiv:2007.07922

  34. Bhatia, S., Sinha, Y., Goel, L.: Lung cancer detection: a deep learning approach. In: Soft Computing for Problem Solving, pp. 699–705. Springer, Singapore (2019)

    Google Scholar 

  35. Sharma, R., Gourisaria, M.K., Rautaray, S.S., Pandey, M., Patra, S.S.: ECG classification using deep convolutional neural networks and data analysis. Int. J. Adv. Trends Comput. Sci. Eng. 9, 5788–5795 (2020)

    Article  Google Scholar 

  36. Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Trans. Knowl. Data Eng. 22(10), 1345–1359 (2009)

    Article  Google Scholar 

  37. Punn, N.S., Sonbhadra, S.K., Agarwal, S.: COVID-19 epidemic analysis using machine learning and deep learning algorithms. MedRxiv (2020)

    Google Scholar 

  38. Cooper, G.F., Aliferis, C.F., Ambrosino, R., Aronis, J., Buchanan, B.G., Caruana, R., Spirtes, P.: An evaluation of machine-learning methods for predicting pneumonia mortality. Artif. Intell. Med. 9(2), 107–138 (1997)

    Article  Google Scholar 

  39. Harshvardhan, G.M., Gourisaria, M.K., Rautaray, S.S., Pandey, M.: Pneumonia detection using CNN through chest X-ray. J. Eng. Sci. Technol. 16(1), 861–876 (2021)

    Google Scholar 

  40. Unlersen, M.F., Sabanci, K., Özcan, M.: Determining cervical cancer possibility by using machine learning methods. Int. J. Latest Res. Eng. Technol. 3(12), 65–71 (2017)

    Google Scholar 

  41. Nayak, S., Gourisaria, M.K., Pandey, M., Rautaray, S.S.: Prediction of heart disease by mining frequent items and classification techniques. In: 2019 International Conference on Intelligent Computing and Control Systems (ICCS), pp. 607–611. IEEE (2019)

    Google Scholar 

  42. Nayak, S., Gourisaria, M.K., Pandey, M., Rautaray, S.S.: Heart disease prediction using frequent item set mining and classification technique. Int. J. Inf. Eng. & Electron. Bus. 11(6) (2019)

    Google Scholar 

  43. Podoleanu, A.G., Rogers, J.A., Jackson, D.A., Dunne, S.: Three dimensional OCT images from retina and skin. Opt. Express 7(9), 292–298 (2000)

    Article  Google Scholar 

  44. Hegde, S., Mundada, M.R.: Early prediction of chronic disease using an efficient machine learning algorithm through adaptive probabilistic divergence based feature selection approach. Int. J. Pervasive Comput. Commun. (2020)

    Google Scholar 

  45. Shahbaz, M., Ali, S., Guergachi, A., Niazi, A., Umer, A.: Classification of Alzheimer's disease using machine learning techniques. In: DATA, pp. 296–303 (2019)

    Google Scholar 

  46. Bodenstedt, S., Wagner, M., Müller-Stich, B.P., Weitz, J., Speidel, S.: Artificial intelligence-assisted surgery: potential and challenges. Visc. Med. 36(6), 450–455 (2020)

    Article  Google Scholar 

  47. McGrow, K.: Artificial intelligence: essentials for nursing. Nursing 49(9), 46 (2019)

    Article  Google Scholar 

  48. Al-Ali, A.R., Zualkernan, I.A., Rashid, M., Gupta, R., AliKarar, M.: A smart home energy management system using IoT and big data analytics approach. IEEE Trans. Consum. Electron. 63(4), 426–434 (2017)

    Article  Google Scholar 

  49. Yu, L., Lu, Y., Zhu, X.: Smart hospital based on internet of things. J. Networks 7(10), 1654 (2012)

    Article  Google Scholar 

  50. Hauben, M.: History of ARPANET. Site de l’Instituto Superior de Engenharia do Porto 17 (2007)

    Google Scholar 

  51. Sikder, A.K., Acar, A., Aksu, H., Uluagac, A.S., Akkaya, K., Conti, M.: IoT-enabled smart lighting systems for smart cities. In: 2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC), pp. 639–645. IEEE (2018)

    Google Scholar 

  52. Zhao, L., Matsuo, I.B.M., Zhou, Y., Lee, W.J.: Design of an industrial IoT-based monitoring system for power substations. IEEE Trans. Ind. Appl. 55(6), 5666–5674 (2019)

    Article  Google Scholar 

  53. Shah, R., Satam, P., Sayyed, M.A., Salvi, P.: Wireless smoke detector and fire alarm system. Int. Res. J. Eng. Technol. (IRJET) 6(1), 1407–1412 (2019)

    Google Scholar 

  54. Gunawan, T.S., Munir, Y.M.S., Kartiwi, M., Mansor, H.: Design and implementation of portable outdoor air quality measurement system using Arduino. Int. J. Electr. Comput. Eng. 8(1), 280 (2018)

    Google Scholar 

  55. Karami, M., McMorrow, G.V., Wang, L.: Continuous monitoring of indoor environmental quality using an Arduino-based data acquisition system. J. Build. Eng. 19, 412–419 (2018)

    Article  Google Scholar 

  56. Hossein, N., Mohammadrezaei, M., Hunt, J., Zakeri, B.: Internet of Things (IoT) and the energy sector. Energies 13(2), 494 (2020)

    Article  Google Scholar 

  57. Jayanth, S., Poorvi, M.B., Sunil, M.P.: Inventory management system using IOT. In: Proceedings of the First International Conference on Computational Intelligence and Informatics, pp. 201–210. Springer, Singapore (2017)

    Google Scholar 

  58. Cho, B.H., Ahn, H.H.: Analysis and design of smart vending machine system based on IoT. J. Inst. Internet, Broadcast. Commun. 19(3), 121–126 (2019)

    Google Scholar 

  59. Penna, M., Arjun, B., Goutham, K.R., Madhaw, L.N., Sanjay, K.G. Smart fleet monitoring system using Internet of Things (IoT). In: 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp. 1232–1236. IEEE (2017)

    Google Scholar 

  60. Dragojević, M., Stević, S., Stupar, G., Živkov, D.: Utilizing iot technologies for remote diagnostics of next generation vehicles. In: 2018 IEEE 8th International Conference on Consumer Electronics-Berlin (ICCE-Berlin), pp. 1–4. IEEE (2018)

    Google Scholar 

  61. Vaishali, S., Suraj, S., Vignesh, G., Dhivya, S., Udhayakumar, S.: Mobile integrated smart irrigation management and monitoring system using IOT. In: 2017 international conference on communication and signal processing (ICCSP), pp. 2164–2167. IEEE (2017)

    Google Scholar 

  62. Chandana, L.S., Sekhar, A.R.: Weather monitoring using wireless sensor networks based on IOT. Int. J. Sci. Res. Sci. Technol 4, 525–531 (2018)

    Google Scholar 

  63. Ayele, T.W., Mehta, R.: Air pollution monitoring and prediction using IoT. In: 2018 second international conference on inventive communication and computational technologies (ICICCT), pp. 1741–1745). IEEE (2018)

    Google Scholar 

  64. Basu, M.T., Karthik, R., Mahitha, J., Reddy, V.L. IoT based forest fire detection system. Int. J. Eng. Technol. 7(2.7), 124–126 (2018)

    Google Scholar 

  65. Retrieved on 27th August 2021 from https://cprimestudios.com/blog/what-smart-hospital-and-how-build-your-own-solution

  66. Gourisaria, M.K., Agrawal, R., Harshvardhan, G.M., Pandey, M., Rautaray, S.S.: Application of machine learning in industry 4.0. Mach. Learn.: Theor. Found. Pract. Appl. 57–87 (2021)

    Google Scholar 

  67. Gourisaria, M.K., Harshvardhan, G.M., Agrawal, R., Patra, S.S., Rautaray, S.S., Pandey, M.: Arrhythmia detection using deep belief network extracted features from ECG signals. Int. J. E-Health Med. Commun. (IJEHMC) 12(6), 1–24 (2021)

    Article  Google Scholar 

  68. Lahtela, A.: A short overview of the RFID technology in healthcare. In: 4th International Conference on Systems and Networks Communication, pp. 165–169 (2009)

    Google Scholar 

  69. Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)

    Article  MATH  Google Scholar 

  70. Qi, J., Yang, P., Min, G., Amft, O., Dong, F., Xu, L.: Advanced internet of things for personalized healthcare systems: a survey. Pervasive Mob. Comput. 41, 132–149 (2017)

    Article  Google Scholar 

  71. Sebastian, M.P.: Smart Healthcare: Challenges and Opportunities. International Academic Conference on Management, Economics and Marketing, July 06–07, Vienna, pp. 396–403 (2018)

    Google Scholar 

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Authors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to Be University, Bhubaneswar, Odisha, 751024, India

    Mahendra Kumar Gourisaria, Rakshit Agrawal, Vinayak Singh, Siddharth Swarup Rautaray & Manjusha Pandey

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  1. Mahendra Kumar Gourisaria
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Correspondence to Mahendra Kumar Gourisaria .

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Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India

    Siddharth Swarup Rautaray

  2. School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India

    Manjusha Pandey

  3. Graduate School, Duy Tan University, Danang, Vietnam

    Nhu Gia Nguyen

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Gourisaria, M.K., Agrawal, R., Singh, V., Rautaray, S.S., Pandey, M. (2022). AI and IoT Enabled Smart Hospital Management Systems. In: Rautaray, S.S., Pandey, M., Nguyen, N.G. (eds) Data Science in Societal Applications. Studies in Big Data, vol 114. Springer, Singapore. https://doi.org/10.1007/978-981-19-5154-1_6

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