JOURNAL ARTICLE

IOT Based Patient Fall Prediction And Detection System

Amol PatilMayuri GaikwadHarshali GaikwadSwati GavharHarshal Galwade

Year: 2020 Journal:   Zenodo (CERN European Organization for Nuclear Research) Vol: 5 (1)Pages: 29-32   Publisher: European Organization for Nuclear Research

Abstract

This Paper states that fall detection and fall prevention systems should require people to wear or to interact with devices. To monitor the system in 24/7 surveillance camera-based systems do not have a monitoring system as no object is attached here the sensors have to be active obstructiveness is varies from system to system as per the sensor used. Some systems need additional gadgets like a wrist band or a belt this has a data collection and robust with a more responsive system. It does not depend on wireless communication. Usually, it means bigger and more obstructive devices. We are tending to develop such a device that can alert and predict patient falls to prevent any injury due to falling.

Keywords:
Computer science Real-time computing Falling (accident) Wireless Embedded system Computer vision Artificial intelligence Telecommunications Medicine

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Topics

Context-Aware Activity Recognition Systems
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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