Sonar for Commercial Fishing

Abstract

Commercial fishing has been made more effective with the use of devices based on Sound Navigation and Ranging (SONAR) technology, across the years. FishFinder is one such device, the first of its kind. It is a very trivial device and is used as the basis for all devices that are available in the market today. This device has a lot of drawbacks; it detect objects that have densities different from water, making it hard to identify whether the waves have hit a pool of fish or not. There is no mechanism to identify the type of fish as well, hence purely depending upon the experience of the fisherman. To overcome these drawbacks, certain modifications that could be incorporated into this device is proposed in this paper. The proposed modifications include a Stabilization mechanism, a Real-time tracking mechanism, and a Machine Learning (ML) model that identifies the type of fish with reference to its unique swim bladder size. These modifications, along with future work ideas, could enhance the effectiveness of the FishFinder device, thereby creating pathways to new advancements in the field.