User Analysis Mechanisms based Mobile Fitness System

Abstract

INTRODUCTIONIn the modern society, obesity has been increasing due to a number of reasons, like improper food intakes and lack of exercise. Lack of muscle mass induces various diseases. As a result, the importance of strength training is increasing day by day. However, strength training should be conducted mostly through a weight training room, and there was no way to determine quantity of exercise. To solve this problem, various fitness systems have been developed [1][2][3]. Existing fitness systems sense the motion of the user and inform the consumed calorie value based on the sensor of a mobile device. However, the data provided to existing systems are not high accuracy. Also it notifes only the bumed calories value, and information on recommendations for strength training is insufficient. In another method the system can analyze the user's body information, and provide the data to indicate how the exercise and use the fitness equipment. In this way it is difficult for the system to provide a generic data analysis, because only the information of individual users. There are also other problems with the information that is available and the user needs to actually [4][5][6][7].In this paper, we develop a system that can be used indoor and outdoor, to manage fitness due to lack of strength exercise. Mechanisms of the system analysis the users information and provide the processed data. It also provides three different recommendation data, based on different algorithm in order to solve the shortcomings of the existing systems of not providing fitness data required by the user.Recommendation algorithm is made based on the user's BMI index, BMR value and exercise level, etc. through which the user is able to receive the correct data than other fitness system. In addition, group of users with similar levels of BMI index as the user, notifies info and exercise machines with users belonging to the same group as the users. Because of this it is possible to proceed with the strength training based on various informations. Also we have used the inductive reasoning method, which allows reflecting the choice of the user to provide the data.