Jal Anveshak: Prediction of fishing zones using fine-tuned LlaMa 2

TL;DR

Jal Anveshak is an AI-powered application that uses a fine-tuned Llama 2 model to predict fishing zones and assist Indian fishermen through multilingual, multimodal queries, aiming to enhance fishing yield and safety.

Contribution

The paper introduces Jal Anveshak, a novel application framework leveraging fine-tuned Llama 2 for predicting fishing zones and supporting fishermen with AI-driven, multilingual assistance.

Findings

Effective prediction of fishing zones demonstrated.

Multilingual and multimodal query resolution achieved.

Potential to improve fishing yields and safety.

Abstract

In recent years, the global and Indian government efforts in monitoring and collecting data related to the fisheries industry have witnessed significant advancements. Despite this wealth of data, there exists an untapped potential for leveraging artificial intelligence based technological systems to benefit Indian fishermen in coastal areas. To fill this void in the Indian technology ecosystem, the authors introduce Jal Anveshak. This is an application framework written in Dart and Flutter that uses a Llama 2 based Large Language Model fine-tuned on pre-processed and augmented government data related to fishing yield and availability. Its main purpose is to help Indian fishermen safely get the maximum yield of fish from coastal areas and to resolve their fishing related queries in multilingual and multimodal ways.