Essay Example on Abstract An Emergency Fall Notifier is a wearable IOT device








Abstract An Emergency Fall Notifier is a wearable IOT device that helps to detect fall of a person Fall detection is a major challenge especially for the elderly as the decline of their physical fitness Many elderly individuals can suffer accidental falls due to weakness or dizziness Since old people are fragile these accidents may possibly have serious consequences if aid is not given in time Statistics show that the majority of serious consequences are not the direct result of falling but rather are due to a delay in assistance and treatment Post fall consequences can be greatly reduced if caretakers can be alerted in time The proposed system consists of an integrated sensor with tri axial accelerometer and tri axial gyroscope for sensing linear acceleration and angular velocity a GPS sensor for detecting location a micro controller a wifi module and a battery The sensor provides accelerations of elderly body movements to micro controller which identifies a fall collect location coordinates of person with the help of GPS and triggers the wifi module that sends notification to the caretakers along with location The wifi module is in the sleep mode until there is a fall which makes the project more energy efficient We use parameter threshold in our proposed fall detection as a method to detect falls which is an accurate method Keywords IOT Internet of Things Fall Detection Sensor Acceleration Threshold I I NTRODUCTION

An emerging task of the health care system is to provide assisted living to elderly persons and patients suffering from chronic diseases Many neuromuscular disorders have an in creased chance of losing balance which may lead to minor accidents loss of consciousness and heart failure A severe fall may cause serious injuries leading to further complications and even death if immediate and appropriate action is not taken A fall as an event which results in a person coming to rest unintentionally on the ground Since these events involve mo tion and change in position observing certain characteristics of these may provide us with the necessary information to detect falls Many types of sensors can be used to observe motion and position of the elderly and determine if a fall has occurred or not Sudden falls have many consequences among which fracture is the most common injury There is also a certain possibility to get coma brain trauma and paralysis In most of the situations fall is the main source of injury because of the high impact But sometimes the late medical help may worsen the situation That means the faster the help arrives the less risk the elderly will face Now Internet of Things is a reality and it helps devices to configure themselves without the intervention of human beings Progress of various technologies brings more possibil ities to help us protect the elderly 

A continuous monitoring of the movement and posture of such individuals would be helpful in alerting the concerned person Components that consume low power make it possible to build an efficient and wearable monitoring device MEMS micro electro mechanical systems have simplified the design and deployment of sensor systems LBS Location based ser vices makes it more convenient to locate the elderly in health monitoring Beside these mobile computing makes remote health monitoring easier They do not suffer from interference problems and do not impose restrictions on movement space Many strategies have utilized the changes in acceleration magnitude to determine falls Focusing on large acceleration results in many false positive outcomes while other activities such as sitting and running are not considered as a fall The purpose of this research is to develop a wearable device to detect a human body fall in accordance with the elderly conditions So the device needs to be light weight use a battery power supply and have low energy consump tion Head waist trunk and thigh are good locations for sensor placement while wrist is not For most persons placing sensors on the head can be uncomfortable

The proposed system uses tri axial accelerometer and tri axial gyroscope sensor When fall event occurs the accelerometer provides valuable information of body inertial change due to the impact Simultaneously the gyroscope provides the unique information of bodys rotational velocity during a fall event A fall event produces both large change of acceleration and angular ve locity These changes are not observed during normal daily activities Thus several thresholds of acceleration and angular velocity could be set to distinguish between fall event and ADL Activities of Daily Living A microcontroller is used for signal acquisition processing control and data transfer The device has nonvolatile memory for recording the sensed data and wireless connectivity A fall detection algorithm applying multiple decomposition and threshold on the acceleration data is implemented on the microcontroller for real time processing The device uses an efficient algorithm with less number of resources and power consumption which means that it is a proper design for fall detection

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