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 :
- Diana Yacchiremaa,b,, Jara Suárez de Pugaa , Carlos Palaua , Manuel Esteve: Fall detection system for elderly people using IoT and Big Data
- 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
- Prashant Wakhare, Hrishikesh Tavar, Priyanka Jagtap,Mayur Rane , Harshvardhan
- Alin Anil1, Athira S, Raifa Rafi, Asst. Professor Netha Merin Mathew: AN IoT- BASED WEARABLE FALL DETECTION SYSTEM;
- 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