Long-Term Animal Observation by Wireless Sensor Networks with Sound Recognition

摘要

Due to wireless sensor networks can transmit data wirelessly and can be disposed easily, they are used in the wild to monitor the change of environment. However, the lifetime of sensor is limited by the battery, especially when the monitored data type is audio, the lifetime is very short due to a huge amount of data transmission. By intuition, sensor mote analyzes the sensed data and decides not to deliver them to server that can reduce the expense of energy. Nevertheless, the ability of sensor mote is not powerful enough to work on complicated methods. Therefore, it is an urgent issue to design a method to keep analyzing speed and accuracy under the restricted memory and processor. This research proposed an embedded audio processing module in the sensor mote to extract and analyze audio features in advance. Then, through the estimation of likelihood of observed animal sound by the frequencies distribution, only the interesting audio data are sent back to server. The prototype of WSN system is built and examined in the wild to observe frogs. According to the results of experiments, the energy consumed by sensors through our method can be reduced effectively to prolong the observing time of animal detecting sensors.