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Publication Type : Conference Proceedings
Publisher : IEEE
Source : International Conference on Edge Computing and Applications, ICECAA 2022 - Proceedings, 2022, pp. 745–751
Url : https://ieeexplore.ieee.org/document/9936247
Campus : Bengaluru
School : School of Engineering
Department : Electrical and Electronics
Year : 2022
Abstract : Majority of people want to live freely at home. Some activities in our daily lives, such as falling, are prone to accidents. Falls can put people in dangerous situations, including death. This study presents a prototype of a fall detection system based on a FPGA interface with accelerometer and gyroscope. Accelerometer and gyroscope sensors are used to improve the accuracy of fall detection. This system is suitable for use both indoors and outdoors. If someone using this is in a deadly condition and need assistance, an automatic call will be sent to family members as an alert. In case of patients, alert will be sent to nearby hospitals and ambulance service. This study can also discriminate between people's physical conditions and their daily activities. The experiment has been tested carefully and can be applied to real applications for the elderly people. In order to monitor the data and do the necessary action in an automated manner the sensor data is sent to the cloud storage through IOT. Once threshold conditions based on the fall types are reached, the alerting action takes place with the help of React functions and the type of react function created in the cloud platform. The data transmitted by the sensor can be viewed by the doctors in order to frame an analysis to prevent the fall in near future by improving the factors where the people rely on to maintain the balanced position. Thus, in this paper the ultimate aim is to measure the tilt angle of the sensor to measure the human posture and detect whether the person has encountered a fall or not and sending the medical assistance by a SMS alert to a nearby hospital and ambulance control room.
Cite this Research Publication : S. Yadav, Sneha, S., Mukesh, R.S.,
“FPGA based Fall Detection for Elderly People.”
International Conference on Edge Computing and Applications, ICECAA 2022 - Proceedings, 2022, pp. 745–751