The use of stereo cameras and artificial intelligence data to support capture fisheries landing data monitoring

Abstract

Reliable data and data collection are important key factors in realizing sustainable fisheries management. Landing data collected by the fishing port authority through has issues with coverage and accuracy. The fast development of image processing and artificial intelligence (AI) analysis opens the possibilities of automatic catch monitoring and data collection in the fishing port. This paper aims to develop a catch data collection program in fishing ports based on stereo camera video monitoring which AI processes. The first version of the devices, FishQi-L (Fish Quantitative Intelligence in Landing site), was developed. FishQi-L consisted of a set stereo camera and a pre-programed JETSON Nano image/video processor. The stereo camera allows image size quantification, size estimation, and spatial mapping capabilities. FishQi-L was able to detect the character and dimensions of objects, the trial object in Pekalongan was “Basket” with mean average precision (mAP) of the detection was 84% and 0.4387 losses. To increase the accuracy and reliability of the systems, we need to increase the number of data and data training iterations.