Port Aqua Market demand analysis and recommendation system

Project Code :TCMAPY1118

Objective

The project aims to create a deep learning system to classify fish species from images accurately, improving access to detailed species information, and offering state-wise fish recommendations to encourage sustainable fishing and consumption. By merging technology with environmental sustainability, it supports ecosystem conservation, enhances market efficiency, and educates consumers. Ultimately, this initiative benefits all stakeholders in the fisheries sector by promoting sustainable practices, preserving biodiversity, and aligning consumption patterns with regional availability and preferences.

Abstract

This project introduces an integrated system for fish species classification utilizing advanced deep learning techniques, followed by detailed information display and state-wise fish recommendation. Leveraging sophisticated image recognition technology, the system accurately identifies fish species from uploaded images, offering users comprehensive information about each classified fish, including habitat details, nutritional value, and commercial significance. Moreover, the system provides tailored fish recommendations based on geographical data, ensuring users receive pertinent suggestions aligned with regional availability and preferences. This approach not only enhances consumer knowledge and decision-making but also fosters sustainable fishing practices by promoting species diversity and local consumption patterns. By merging technological innovation with environmental consciousness, the project contributes to ecosystem preservation, market efficiency, and consumer education, benefiting stakeholders across the fisheries sector.

Keywords: Fish Species Classification, Deep Learning, State-wise Recommendations, Geographical Data Analysis

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