Remote control of mechanical rat traps based on vibration and audio sensors

Abstract: The main aim with this master’s thesis was to study the possibilities of detecting an event (rat trap going off) by analyzing audio streams from a MEMS (micro-electromechanical systems) microphone or movement patterns from a MEMS accelerometer. To achieve this goal, a small, power efficient and cost efficient embedded system was built with the help of a development board, a MEMS accelerometer, a MEMS microphone and a metal box where the equipment and the rat traps were placed and positioned. Data was collected and recorded from both sensors in form of a training set and a test set. The training set was analyzed and algorithms were implemented and optimized in MATLAB for three different cases (Case 1. Microphone, Case 2. Accelerometer and Case 3. Microphone + Accelerometer). The algorithms were based on two steps. In the first step events were detected based on amplitude threshold values. The detected events were then stored as signal segments of a fix interval to ensure that the complete event was captured. In the second step different features were computed to find some characterization of the signal segments to separate correct detections from false detections but also to identify the position of the activated rat trap or whether the rat trap was empty or not. Finally, the results show that it is possible to detect events where a rat trap has been activated in a quiet environment and the accelerometer had the best performance based on amplitude detection.