Mining-based lifecare recommendation using peer-to-peer dataset and adaptive decision feedback

Due to the enhancing of life quality, increasing of chronic diseases, changing lifestyles, and an expanding life expectancy, rapid population aging requires a new business model that promotes happiness and emphasizes a healthy body and mind through the anytime, anywhere well-being lifestyle. Recently, lifecare systems using IoT devices are being released as products that are influential on the overall society, and their effectiveness is continuously proven. In addition, based on peer-to-peer (P2P) networking, diverse companies are conducting investments and research to develop devices as well as solutions that connect to these devices. Accordingly, in this study, a mining-based lifecare-recommendation method using a peer-to-peer dataset and adaptive decision feedback is proposed. In addition to collecting PHRs, the proposed method measures life-logs such as dietary life, life pattern, sleep pattern, life behavior, and job career; the P2P-dataset preprocessed index information; and biometric information using a wearable device. It uses the Open API to collect the health-weather and life-weather index data from public data, and it uses a smart-band-type wearable device known as a biosensor to measure the heart rate, daily activity, and body temperature. It monitors the current status and conditions through the classification of life data, and it mines big data and uses a decision tree to analyze the association rules and correlations, as well as to discover new knowledge patterns. In the peer-to-peer networking, a lifecare recommendation model that uses adaptive decision feedback has been developed for the peer-to-peer platform. This adaptive decision feedback reflects an individual's importance or sensory level. Accordingly, it proposes more individualized and flexible results and can be configured to support intellectual lifecare. A mining-based lifecare-recommendation mobile service can also be developed to enhance the quality of life, as it provides user-based health management and reduces the medical expenses; accordingly, it enhances the service satisfaction and quality in the lifecare field.