The Advantages of Health Recommending System with Wearable Devices

Abstract

The health recommendation system is one of the critical application scenarios of machine learning technology. With the advantages of wearable and mobile devices to collect rich user health monitoring data, machine learning algorithms can accurately advise users’ health status and corresponding living habits. However, some technical and regulatory challenges still need to be solved at this stage. Specifically, to ensure real-time recommendation results, the health recommendation system needs to adopt the method of training computational learning algorithms on wearable devices. However, due to wearable devices’ limited computing resources and storage space, it is often difficult to obtain satisfactory results by changing the strategy. In addition, the issue of data privacy deserves attention because wearable devices collect a lot of user privacy information, but the data manager is often not the user himself. Finally, Bluetooth protocol usually connects wearable devices, making them vulnerable to intentional attacks. This paper investigates the above problems and expounds on the solutions to related problems.