IoT fall detection system for the elderly using Intel Galileo development boards generation I

In today society there has been an increase in the number of elderly people that can fend for themselves. However, there are certain risks related to age such as falls, blood pressure or heart problems among others, that can result in serious consequences to the person. The objective of this study is the development of a system oriented IoT, which can be acquired by the low income population, allowing any member of the family to do a remote following up. One of the most serious problems is the falls. For this reason we started developing a module that can detect falls by using accelerometers and gyroscopes in this first stage, as a part of the daily elderly control integral system using the “Intel Galileo Gen I” development board. Selection criteria of the sensors used for this purpose together with corrections reading and data processing are described, because working with a sensor MPU6050 with Intel Galileo Gen I differs respect to other platforms. An analysis on different fall detection algorithms is done; false positives are discarded applying notifications alarms thus acquiring trustworthy data for their processing.