Audio-based Motion Detection

Abstract: Motion detection is an essential technology and it has numerous use-cases, such as security tracking, automated door opening systems, and IP cameras. Commonly, passive infrared sensors or radio frequency sensors are used for motion detection. However, this thesis focuses on performing motion detection using existing hardware at audio frequencies. Specifically, it aims to implement a motion detection algorithm using existing speakers and microphones on each of two intercom devices designed by Axis Communications, AXIS I8016-LVE Network Video Intercom (Device 1) and AXIS A8207-VE Mk II Network Video Door Station (Device 2). The goal of implementing such an algorithm is to save power and cost by reusing existing hardware. In this thesis, data was collected and studied for both stationary and moving objects to understand the systems’ behaviour. The range detection capability for different signal parameters was compared and analysed using a stationary object, at different positions within the range of the systems. This was done to find the optimum signal parameters for the motion detection algorithm. Once these were determined, data was collected and analysed for a moving object. Based on this data, an optimisation and tracking algorithm was designed to obtain better results from the systems. The results show that for Device 1, the algorithm can detect any movement of a person within the range of the system. However, for Device 2, the algorithm can differentiate between different movements, allowing the detection of a person who is approaching the device, rather than just someone who is just passing by. The latter enables power saving for the device since its camera will only turn on when someone approaches the device with the intention of using it.