Browsing by Author "Siwat Suksri"

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    NVIDIA Jetson Nano and Python-based Economical Human Fall Detection and Analysis System
    (Institute of Electrical and Electronics Engineers Inc., 2023) Chudanat Sudthongkhong; Siwat Suksri; Chanate Ratanaubol; Sookyuen Tepthong; Jira Jitsupa; Putawan Suksai; C. Sudthongkhong; King Mongkut's University of Technology Thonburi (KMUTT), School of Architecture and Design, Department of Medical and Science Media, Bangkok, Thailand; email: medicalmedia01@gmail.com
    Every year, around one-third of elderly individuals experience falls at home, especially in high-risk areas like bathrooms and stairs. Uneven floor surfaces exacerbate these dangers, impeding elderly mobility and significantly increasing fall risks, with recurrent falls being common. Recognizing this pressing concern, our project introduces a 'Human Fall Detection and Estimation System' to mitigate harm. This system deploys a specialized camera with gesture recognition software to monitor for falls by detecting posture deviations. When a fall occurs, the system records the location and uses advanced Image Processing for precise Pose Estimation. Deep Learning analyzes Pose Estimation data to gauge fall severity and simultaneously alerts caregivers via the network for swift assistance. Incidents are logged in a database for root cause analysis, facilitating more effective elderly care systems. our system plays a crucial role in preventing and addressing elderly falls, swiftly detecting and assessing incidents, and alerting caregivers [1], enhancing elderly safety and well-being. © 2023 IEEE.