Automated Fall Detection for Elderly Care Leveraging IoT for Safety


Authors : Samskruthi C; Spoorthi B R; Sriram R Kashyap; Sudhanva Aathreya B M; Jagadeesh B N

Volume/Issue : Volume 9 - 2024, Issue 12 - December

Google Scholar : https://tinyurl.com/dbdtykev

Scribd : https://tinyurl.com/3u32jd6t

DOI : https://doi.org/10.5281/zenodo.14534385

Abstract : With the increasing elderly population, fall detection systems have become crucial in providing timely assistance to reduce fall-related injuries and fatalities. This project presents an IoT based fall detection system designed to monitor aged individuals in real-time, identifying sudden falls through wearable sensors and environmental data. By leveraging accelerometers, gyroscopes, and sense motions, the system detects abrupt changes in posture or unusual movements indicative of a fall. Upon detection, the system immediately sends notifications to caregivers or emergencycontacts, providing real-time alerts along with location information to facilitate quick intervention. This solution makes things safer and helps families and caregivers feel more at ease and caregivers, offering a reliable, efficient, and scalable approach to elderly care using IoT technology.

Keywords : Iot-Based Fall Detection, Elderly Safety, Wearable Sensors, Real-Time Monitoring, Accelerometer And Gyroscope, Emergency Alert System, Elder Care Technology, Posture Detection, Caregiver Notification, Health Monitoring

References :

  1. Diana Yacchiremaa,b,, Jara Suárez de Pugaa , Carlos Palaua , Manuel Esteve: Fall detection system for elderly people using IoT and Big Data
  2. Hatem A. Alharbi , Khulud K. Alharbi and Ch Anwar Hassan: Enhancing Elderly Fall Detection through IoT-Enabled Smart Flooring and AI for Independent Living Sustainability
  3. Prashant Wakhare, Hrishikesh Tavar, Priyanka Jagtap,Mayur Rane , Harshvardhan
  4. Alin Anil1, Athira S, Raifa Rafi, Asst. Professor Netha Merin Mathew: AN IoT- BASED WEARABLE FALL DETECTION SYSTEM;
  5. Pedditi satvika, parankusham vaishnavi, mamindla mounika, Dr K. Srujan Raju : A novel iot-based automatic fall detection cavity for elderly people using mems

With the increasing elderly population, fall detection systems have become crucial in providing timely assistance to reduce fall-related injuries and fatalities. This project presents an IoT based fall detection system designed to monitor aged individuals in real-time, identifying sudden falls through wearable sensors and environmental data. By leveraging accelerometers, gyroscopes, and sense motions, the system detects abrupt changes in posture or unusual movements indicative of a fall. Upon detection, the system immediately sends notifications to caregivers or emergencycontacts, providing real-time alerts along with location information to facilitate quick intervention. This solution makes things safer and helps families and caregivers feel more at ease and caregivers, offering a reliable, efficient, and scalable approach to elderly care using IoT technology.

Keywords : Iot-Based Fall Detection, Elderly Safety, Wearable Sensors, Real-Time Monitoring, Accelerometer And Gyroscope, Emergency Alert System, Elder Care Technology, Posture Detection, Caregiver Notification, Health Monitoring

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