Restrictions on competitive fishing activities due to the depletion of living marine resources and the monitoring of fish resources for the purpose of marine ecosystem research are supported by statistics on the protection of fish resources and ecosystem research, which are gathered through existing observer monitoring systems. However, in the case of deep-sea fishing vessels and special-purpose fishing vessels, some matters, such as collusive transactions with shipping companies and shipowners and threats toward the observer, are problematic, as observers are always active on board. Therefore, through the present study we would like to discuss the methodology and directions for research on the independent role of the observer and the methods for improving the reliability of data through systems that automate the monitoring of the acquisition of fish resources, which is expected to be a continuing problem. After an analysis of research trends for each issue related to the electronic monitoring system, future research directions are suggested on the basis of the findings, and for the research currently in progress, this paper presents the results from a prediction server and client and an image collector. In order to use these in the field in the future, as the detection method and reliability of the electronic monitoring system that can automate self-learning should be improved, we describe the image transmission technology, the image recognition technology for studying fish, and the methodology for calculating the yield.