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Falls are the most common cause of injuries for older adults. IoT systems have been developed for monitoring, detecting, and reporting falls of patients in the home environment. However, studies have reported that most falls occur in the bathroom, where older adults do not use wearable devices. A solution with sensors installed on the bathroom environment could contribute to increasing the degree of fall detection. The purpose of this paper is to show how simulation models can be used to evaluate, at design time, two architectural alternatives for IoT-based home monitoring systems. The first alternative is a conventional IoT system based on wearable devices, while the second architectural design improves the former model by including sensors on the bathroom environment. Datasets for fall detection were used during the simulations. Preliminary results show that fall detection increases of up to 8.2% by comparing an architecture that uses only accelerometers to one that additionally uses a doppler radar installed on the bathroom floor.

Simulação de Arquiteturas de Sistemas de Monitoramento de Quedas de Pacientes Domiciliares