IoT-Based Smart Edge for Global Health: Remote Monitoring With Severity Detection and Alerts Transmission

被引:93
|
作者
Pathinarupothi, Rahul Krishnan [1 ]
Durga, P. [1 ]
Rangan, Ekanath Srihari [2 ]
机构
[1] Amrita Vishwa Vidyapeetham, Amrita Sch Engn, Amrita Ctr Wireless Networks & Applicat, Amritapuri Campus, Kollam 690525, India
[2] Amrita Vishwa Vidyapeetham, Sch Med, Cochin Campus, Kochi 682041, Kerala, India
关键词
Internet of Things (IoT); machine learning; m-Health; smart health; wearable sensors; SYSTEM; SENSOR;
D O I
10.1109/JIOT.2018.2870068
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Global health which denotes equitable access to healthcare, particularly in remote-rural-developing regions, is characterized by unique challenges of affordability, accessibility, and availability for which one of the most promising technological interventions that is emerging is the Internet of Things (IoT)-based remote health monitoring. We present an IoT-based smart edge system for remote health monitoring, in which wearable vital sensors transmit data into two novel software engines, namely rapid active summarization for effective prognosis (RASPRO) and criticality measure index (CMI) alerts, both of which we have implemented in the IoT smart edge. RASPRO transforms voluminous sensor data into clinically meaningful summaries called personalized health motifs (PHMs). The CMI alerts engine computes an aggregate criticality score. Our IoT smart edge employs a risk-stratified protocol consisting of rapid guaranteed push of alerts and PHMs directly to the physicians, and best effort pull of detailed data-on-demand through the cloud. We have carried out both clinical validation and performance evaluation of our smart edge system. The clinical validation on 183 patients demonstrated that the IoT smart edge is highly effective in remote monitoring, advance warning and detection of cardiac conditions, as quantified by three measures, precision (0.87), recall (0.83), and F1-score (0.85). Furthermore, performance evaluation showed significant reductions in the bandwidth (98%) and energy (90%), thereby making it suitable for emerging narrow-band IoT networks. In the deployment of our system in the cardiology institute of our University hospital, we observed that our IoT smart edge helped to increase the availability of physicians by 59%. Hence, our IoT smart edge system is a significant step toward addressing the requirements for global health.
引用
收藏
页码:2449 / 2462
页数:14
相关论文
共 50 条
  • [41] Intrusion Detection in IoT-Based Smart Grid Using Hybrid Decision Tree
    Taghavinejad, Seyedeh Mahsan
    Taghavinej, Mehran
    Shahmiri, Lida
    Zavvar, Mohammad
    Zavvar, Mohammad Hossein
    2020 6TH INTERNATIONAL CONFERENCE ON WEB RESEARCH (ICWR), 2020, : 152 - 156
  • [42] A smart ontology-based IoT framework for remote patient monitoring
    Sharma, Nonita
    Mangla, Monika
    Mohanty, Sachi Nandan
    Gupta, Deepak
    Tiwari, Prayag
    Shorfuzzaman, Mohammad
    Rawashdeh, Majdi
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2021, 68
  • [43] SolicitudeSavvy: An IoT-based Edge Intelligent Framework for Monitoring Anxiety in Real-time
    Sundaravadivel, Prabha
    Wilmoth, Parker
    Fitzgerald, Ashton
    PROCEEDINGS OF THE 2021 TWENTY SECOND INTERNATIONAL SYMPOSIUM ON QUALITY ELECTRONIC DESIGN (ISQED 2021), 2021, : 576 - 580
  • [44] Real-Time Weather Monitoring and IoT-Based Palmtop Device for Smart Agriculture
    Tharani Thathsara Rajapaksha
    Amila Alexander
    Leshan Fernando
    Anh Than
    Huy Le Nguyen
    SN Computer Science, 2022, 3 (1)
  • [45] IoT-Based Smart Home Healthcare Monitoring System Using Machine Learning Algorithms
    Jamalpur, Bhavana
    Saseendran, Arun K.
    Vani, V. Divya
    Raj, Vijilius Helena
    Veeramalai, G.
    GinniNijhawan
    2024 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATION AND APPLIED INFORMATICS, ACCAI 2024, 2024,
  • [46] IoT-Based Smart Biofloc Monitoring System for Fish Farming Using Machine Learning
    Abid, Muhammad Adeel
    Amjad, Madiha
    Munir, Kashif
    Siddique, Hafeez Ur Rehman
    Jurcut, Anca Delia
    IEEE ACCESS, 2024, 12 : 86333 - 86345
  • [47] IoT-based monitoring and control of substations and smart grids with renewables and electric vehicles integration
    Ullah, Zia
    Rehman, Anis Ur
    Wang, Shaorong
    Hasanien, Hany M.
    Luo, Peng
    Elkadeem, Mohamed R.
    Abido, Mohammad A.
    ENERGY, 2023, 282
  • [48] An IoT-Based E-Health Monitoring System Using ECG Signal
    Neyja, Maryem
    Mumtaz, Shahid
    Huq, Kazi Mohammed Saidul
    Busari, Sherif Adeshina
    Rodriguez, Jonathan
    Zhou, Zhenyu
    GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE, 2017,
  • [49] Implementation of a Prototype IoT-Based System for Monitoring the Health, Behavior and Stress of Cows
    Evstatiev, Boris I.
    Valov, Nikolay P.
    Kadirova, Seher Y.
    Nenov, Teodor R.
    2022 IEEE 9TH ELECTRONICS SYSTEM-INTEGRATION TECHNOLOGY CONFERENCE, ESTC, 2022, : 77 - 81
  • [50] PISIoT: A Machine Learning and IoT-Based Smart Health Platform for Overweight and Obesity Control
    Machorro-Cano, Isaac
    Alor-Hernandez, Giner
    Andres Paredes-Valverde, Mario
    Ramos-Deonati, Uriel
    Luis Sanchez-Cervantes, Jose
    Rodriguez-Mazahua, Lisbeth
    APPLIED SCIENCES-BASEL, 2019, 9 (15):