Aquatic debris monitoring using smartphone-based robotic sensors

Abstract

Abstract—Monitoring aquatic debris is of great interest to the ecosystems, marine life, human health, and water transport. This paper presents the design and implementation of SOAR – a vision-based surveillance robot system that integrates an off-the-shelf Android smartphone and a gliding robotic fish for debris monitoring. SOAR features real-time debris detection and coverage-based rotation scheduling algorithms. The image processing algorithms for debris detection are specifically de-signed to address the unique challenges in aquatic environments. The rotation scheduling algorithm provides effective coverage of sporadic debris arrivals despite camera’s limited angular view. Moreover, SOAR is able to dynamically offload computation-intensive processing tasks to the cloud for battery power con-servation. We have implemented a SOAR prototype and con-ducted extensive experimental evaluation. The results show that SOAR can accurately detect debris in the presence of various environment and system dynamics, and the rotation scheduling algorithm enables SOAR to capture debris arrivals with reduced energy consumption. Keywords—Robotic sensor; aquatic debris; smartphone; com-puter vision; object detection I.