• Meghana B.N
• B.N. Shankar Gowda

Falls that leads to fatal injuries have become a great challenge that cannot be neglected for elderly people. Hence, mechanisms to detect and avoid falls are necessary to improvise common living of aged people. An ambient-assisted Living applications will be developed in the near future having user positioning as ground technology: elderly tele-care, energy consumption, security and which are strongly based on indoor positioning information. Though many fall detection solutions were presented, few included wrist-wearable devices, mainly due to typical processing and classification challenges to achieve satisfactory accuracy. Considering the wrist as the most comfortable, discrete and acceptable place for an elderly wearable device, this work presents the development and evaluation of a wrist -worn fall detection solution, RFID based indoor positioning system and an android supported text to speech reminders. The fall alert sent to the care takers will be SMS which consists of location where the fall occurred. The sensors like accelerometer, gyroscope, and magnetometer are used to obtain, signals (acceleration, velocity, and displacement) which were combined and then the threshold-based and machine learning methods were applied in order to define the best approach for fall detection and monitoring. Machine learning gave a satisfactory accuracy when compared to threshold-based method.

Fall Detection, Alzheimer’s disease, Wearable device, RFID, Indoor Positioning System, Machine Leaning.

"INDOOR POSITIONING AND MACHINE LEARNING BASED FALL DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.299-305, May-2019, Available :http://www.jetir.org/papers/JETIRCD06053.pdf

"INDOOR POSITIONING AND MACHINE LEARNING BASED FALL DETECTION SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp299-305, May-2019, Available at : http://www.jetir.org/papers/JETIRCD06053.pdf