Real-Time Monitoring of Track and Field Teaching Based on Internet of Things and Sensors

Abstract Track and field is a sport made up of several events in IoT. Field teaching events, such as a jump in the execution, and Throw will include track and field teaching. Although most of the event is an individual, some, such as the track relay, accompanied the team. Team event distribution points, and the total points earned by players with a high finish of each event for their team. Track and field teaching is assumed that all these different roles for sports players. For the coach, but it should not be maximum victory gain is completed, training and competition methods of influence in the personal development of aggressive teaching classification level analysis are very difficult in the previous system. To introduced Logistic Tracking Performance (LTP) based IoT, player development, the players' safety, and supporters' participation play a role today. Coach analyses the possibility of shaping the game's strategy. The analysis will customize the experience that sensor to collect the data through a plurality of IoT. An important role in the information monitoring and control system of IoT sensors, the world attaches great importance to use their real time monitoring track and field teaching, new materials and new product development. The proposed algorithm Logistic Tracking Performance (LTP) is used to classify the sports player performance level using IoT and sensors. Track and field teaching enhances the teaching process using the IoT and how coaches and sports players will help understand the effective relationship between them. The LTP algorithm analysis the track and field teaching performance level and classification level.