Energy-Efficient Smart Wearable IoT Device for the Application of Collapse Motion Detection and Alert
Laxmikant Dewangan, Arpita Rani Vaishnava · IETE Journal of Research · 2020
As we know if anyone falls from a narrow height it is very critical especially for the people who are under 10 years or above 60 years of age. The age group under 10 years is very sensitive, if any child who falls can face injuries which will affect them in terms of mental and physical disability or fatal injuries can also be caused in some cases. Similar for the age group of above 60 is also crucial if they got any kind of injury due to falling and by the time if they didn’t get any medical treatment so it will cause a decisive loss for that person. In the present era we are living in the age of 4G and 3D technology which means in this era everyone is connected with each other by means of smart phone and internet, also the smart wearable devices, which will be connected with human beings and send a kind of information signal through the medium of internet which is commonly known as Internet of Things (IoT). According to this kind of technology we are able to rectify the injury causing by collapsing on the ground. In this paper, we proposed an energy-efficient smart wearable IoT device which is able to detect the motion of human body and based on that it will detect the collapsing motion and immediately take action by sending data to the cloud server via internet which will immediately send an SMS to the concerned person. Apart from that we also introduce one more feature which is panic alert, so if anyone who need any emergency support, this wearable device will send an SMS to the concerned person. Here we used ESP8266-01 for the communication channel, for the calculation of body motion we use ADXL335 and for the reduction of power we used ATTINY85 which will reduce the ample of energy and utilize the power intelligently which results in the long life of 220 mAh battery. Its battery back-up is approximately up to 3000 h which is extremely far better than all the previous existing approaches.