Hybrid seismic and ultrasonic system for autonomous detection and classification of moving objects

Abstract

In this paper, a hybrid autonomous sensing system for the detection and classification of moving objects is presented. The proposed system is based on the integration of a seismic sensor using a geophone and an ultrasonic ranging module operating at 40 kHz, implemented on an STM32F103 microcontroller platform. The seismic channel is employed for early detection of ground vibrations caused by human movement, animals, or vehicles, while the ultrasonic channel is used to confirm the presence of an object in the monitored area and to estimate the distance to the target. The combination of heterogeneous sensors enables sensor fusion, which significantly reduces false alarms caused by environmental noise such as wind, rain, or ground disturbances. The structure of the analog front-end for the geophone signal conditioning, the principle of ultrasonic echo-based confirmation, and the overall system architecture are described. The proposed hybrid approach improves the reliability and robustness of autonomous field-deployed detection systems and can be applied in monitoring, security, and environmental observation applications.