As the ageing issue is coming, our team develops a bed-out alarm system with the goal of "preventing elderly falls". The system can be divided into software, cloud database and artificial intelligence. In addition, it can develope a prediction model by means of multiple sensor combined with machine learning theory. The system implements multi-bed monitoring with a mesh network architecture, and can get the system operating status by using APP.

Our team integrates multiple sensor information to achieve the detection of bed-out, and the KNN model algorithm is introduced into the system in the judgment of bed-out. The IoT communication module in the system can transmit information to the cloud database. With the artificial intelligence-hidden Markov model, behavioral analysis of the elderly can establish a care plan for individual seniors.

Compared with the current market,the system developed by our team uses multiple sensors to have the advantage of non-contact detection, which can greatly reduce the physical discomfort of the elderly.The use of artificial intelligence can improve the defect of the traditional algorithm with high false positive rate under different users.In addition to reducing the burden on caregivers, cloud database can also assist the medical team.