IoT Sensors in a Wireless Environment for Healthcare Monitoring: A Framework for Fault Detection

被引:0
作者
Mulani, Altaf O. [1 ]
Liyakat, Kazi Kutubuddin Sayyad [2 ]
Warade, Nilima S. [3 ]
Patil, Alaknanda [4 ]
Kolte, Mahesh T. [5 ]
Kinage, Kishor [5 ]
Rana, Manish [6 ]
Salunkhe, Shweta Sadanand [7 ]
Jadhav, Vaishali Satish [8 ]
Nagrale, Megha [9 ]
机构
[1] SKN Sinhgad Coll Engn, Dept Elect & Telecommun, Pandharpur 413304, Maharashtra, India
[2] BMIT, Dept Elect & Telecommun, Solapur, Maharashtra, India
[3] AISSMS Inst Informat Technol, Dept Elect & Telecommun, Pune, Maharashtra, India
[4] JSPM NTC, Dept Elect & Telecommun, Pune, Maharashtra, India
[5] Savitribai Phule Pune Univ, Pimpri Chinchwad Coll Engn, Dept Elect & Telecommun Engn, Pune, Maharashtra, India
[6] St John Coll Engn & Management SJCEM, Dept Comp Engn, Palghat, Maharashtra, India
[7] Bharati Vidyapeeths Coll Engn Women, Dept Elect & Telecommun, Pune, Maharashtra, India
[8] D Y Patil Univ, Ramrao Adik Inst Technol, Dept Elect Engn, Navi Mumbai, Maharashtra, India
[9] Sardar Patel Coll Engn, Dept Mech Engn, Mumbai, India
关键词
Healthcare; wireless sensor networks; Internet of Things; fault detection; sensors; framework;
D O I
10.1177/0976500X251324735
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Background The Internet of Things (IoT) and wireless sensor networks (WSNs) are now being explored and used in various sectors, thanks to recent technological advancements.Purpose The healthcare sector is one of the areas we will examine in this research. This study's primary focus will be on the fault detection framework (FDF) for healthcare monitoring employing IoT sensors in a wireless environment.Methods Because isolating defects yields more pertinent information about the issues, fault detection first finds weaknesses in a system or process before isolating the intricate process or variable.Results and Discussion The outcome demonstrates that the suggested strategy achieves an acceptable level of 80% accuracy in problem identification, in addition to the greater number of patients recorded.Conclusion The outcomes show that the defect-detection system for wireless IoT sensor-based healthcare monitoring is efficient.
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页数:7
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共 28 条
  • [1] Basawaraj BG., 2024, Int J Comput Dig Syst, V16, P2210
  • [2] An improved incipient fault detection method based on Kullback-Leibler divergence
    Chen, Hongtian
    Jiang, Bin
    Lu, Ningyun
    [J]. ISA TRANSACTIONS, 2018, 79 : 127 - 136
  • [3] A Distributed Canonical Correlation Analysis-Based Fault Detection Method for Plant-Wide Process Monitoring
    Chen, Zhiwen
    Cao, Yue
    Ding, Steven X.
    Zhang, Kai
    Koenings, Tim
    Peng, Tao
    Yang, Chunhua
    Gui, Weihua
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (05) : 2710 - 2720
  • [4] Deshpande HS, 2015, 2015 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP), P10, DOI 10.1109/ICCSP.2015.7322746
  • [5] Deshpande HS., 2014, International Conference on Communication and Signal Processing, V2014, P1895, DOI [10.1109/ICCSP.2014.6950174, DOI 10.1109/ICCSP.2014.6950174]
  • [6] Refrigerant charge fault detection method of air source heat pump system using convolutional neural network for energy saving
    Eom, Yong Hwan
    Yoo, Jin Woo
    Hong, Sung Bin
    Kim, Min Soo
    [J]. ENERGY, 2019, 187
  • [7] Jadhav HM., Machine Learning Algorithms for Signal and Image Processing, V2022, P219
  • [8] Jarwar MA., 2021, IEEE Int Things J, V10, P2864
  • [9] Machine Learning Algorithms and Fault Detection for Improved Belief Function Based Decision Fusion in Wireless Sensor Networks
    Javaid, Atia
    Javaid, Nadeem
    Wadud, Zahid
    Saba, Tanzila
    Sheta, Osama E.
    Saleem, Muhammad Qaiser
    Alzahrani, Mohammad Eid
    [J]. SENSORS, 2019, 19 (06):
  • [10] Kashid MM., 2022, Proceedings of the international conference on cognitive and intelligent computing. ICCIC, V1, P43