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Fall Detection System by Using Ambient Intelligence and Mobile Robots

Lucio Ciabattoni, G. Foresi, Andrea Monteriù, D. Proietti Pagnotta, Leonardo Tomaiuolo

Year
2018
Citations
12

Abstract

In this paper a robust Fall Detection Algorithm by using a deep learning approach and a low-cost mobile robot equipped with an RGB camera is presented. This method consists of four steps. The first step is the user detection, achieved by a real-time video stream and a Deep Learning approach. Once the user is detected, then its position is estimated in the second step. In the third step, if a fall is detected, a photo is acquired and a pre-registered audio message asks the user how he is. In the last step the photo and the audio captured are sent to a Telegram Bot (TB) in order to alert family members or caregivers. Tests have been performed in a real scenario.

Keywords

Computer scienceArtificial intelligenceMobile robotRGB color modelComputer visionRobotDeep learningReal-time computingMobile deviceOperating system

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