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Abstract — Recently, there has been an increasing interest on sensor data collection for environmental observations or weather forecasting. Data collection is a fundamental and important issue in wireless sensor networks. Wireless sensors network are becoming more popular in environmental monitoring, healthcare applications and etc. Since they are either worn or implanted into human body, these sensors must be very small in size and light in weight. Now a day, many studies exploit cluster head techniques to collect large scale data-base sensor data for environmental observations or weather forecasting for minimizing the energy consumption. Agent (cluster head) travels in sensing areas and collect data directly from each sensor. By using DPV (Delivering predicted Value) method, data can be collected and drop unused data thus we can say that we reduce communication traffic. However, in many methods, the mobile sink collects data from all sensors that the mobile sink can communicate with. In this project, we propose a communication traffic reduction method by agent approach for sensor data collection. In our proposed method, the agent broadcasts predicted sensor data to each sensor. Only sensors whose sensing data exceeds the admissible error margin from the predicted sensor data transmit their data. At the same time we also concentrate on the energy efficiency of the sensor. Therefore, the communication traffic can be reduced and at the time of implementation results demonstrated the effectiveness of our proposed method