Existing health promotion systems (HPSs) have some shortcomings, such as lacking in the ability to plan exercise prescriptions (EPs) for individuals automatically, difficulty in acquiring in a timely manner the physiologic signals of users who are doing exercise, and having no efficient mechanisms for notifying medical personnel of users’ emergent conditions. Aimed at addressing these shortcomings, in this study, we leverage the technologies of wireless sensor network (WSN), mobile communication, and cloud computing to develop a cloud-based HPS. The HPS contains a health promotion cloud service platform that can construct users’ physical fitness models and then generate appropriate EPs for the users to perform various exercises. On the user side, in this study, we design an exercise-sensing device that can timely acquire the physiologic signals and global positioning system (GPS) positioning information of users who are doing exercise through the WSN. Several sensors, such as a GPS sensor, are designed into the exercise-sensing device. The exercise-sensing device can then send those data to the cloud service platform through mobile phone communication to allow the users to master their exercise records. In this study, we also design a cloud alarm mechanism that can efficiently notify medical personnel and family members of the user's emergent states through mobile phone push service. In addition, on the basis of fuzzy inference, we develop an EP adaptation mechanism that can accept the feedback information from the user and can then automatically adjust the user's EP to an appropriate strength level. The results of this study can be a useful reference for constructing new-generation HPSs.