• Login
    View Item 
    •   SUSpace Home
    • Faculty of Science and Engineering
    • Department of Computer Science and Engineering
    • 2021 - 2025
    • View Item
    •   SUSpace Home
    • Faculty of Science and Engineering
    • Department of Computer Science and Engineering
    • 2021 - 2025
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    IoT-Based Smart Health Monitoring and Fall Alert System.

    Thumbnail
    View/Open
    CSE- 250240.pdf (1.199Mb)
    Date
    2025-09-10
    Author
    Sheikh, Md. Anisujjaman
    Samad, Md. Abu
    Akter, Most. Santa
    Shadiha, Umme
    Metadata
    Show full item record
    Abstract
    The rapid advancement of the Internet of Things (IoT) has significantly transformed healthcare by enabling remote patient monitoring and real-time health assessment. This paper presents the design and development of an IoT-based patient health monitoring and fall detection alert system using Blynk as the IoT platform. The system integrates multiple biomedical sensors, including the MAX30100 sensor for heart rate and blood oxygen saturation (SpO₂), an ECG sensor for cardiac activity monitoring, a 10k thermistor functioning as a body temperature sensor, and a blood sugar sensor for glucose level estimation. In addition, a vibration sensor is employed to detect accidental patient falls, which are critical events requiring immediate attention. All collected physiological data are processed by a microcontroller and transmitted to the Blynk application, where authorized caregivers and medical personnel can access real-time readings remotely. To enhance patient safety, the system includes a buzzer and LED module that provide instant audible and visual alerts in cases of abnormal health parameters or fall detection, ensuring timely response. The Blynk platform not only allows continuous remote monitoring but also stores historical data for medical analysis, thereby aiding in preventive healthcare and reducing hospital visits. The proposed systemis low-cost, portable, and efficient, making it suitable for home-based care of elderly individuals, chronically ill patients, and those in remote areas with limited access to healthcare facilities. Furthermore, the fall detection feature addresses one of the most pressing risks among elderly patients, where immediate intervention can prevent severe complications. Overall, this IoT-enabled health monitoring and fall detection alert system demonstrates a reliable, scalable, and user-friendly approach to improving patient care, offering both real-time health insights and emergency alerts that can significantly reduce medical risks and improve quality of life.
    URI
    http://suspace.su.edu.bd/handle/123456789/2240
    Collections
    • 2021 - 2025 [149]

    Copyright © 2022-2025 Library Home | Sonargaon University
    Contact Us | Send Feedback
     

     

    Browse

    All of SUSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Copyright © 2022-2025 Library Home | Sonargaon University
    Contact Us | Send Feedback