Find N FIsh
The people want to enjoy the healthy, savory bounty of the sea however this is not as simple as going to the market and buying whatever kind of fish you find, there are several variables that are needed to be considered and this drives away a lot of consumers away since they understandably don't wan
2025-06-28 16:27:15 - Adil Khan
Find N FIsh
Project Area of Specialization Artificial IntelligenceProject SummaryThe people want to enjoy the healthy, savory bounty of the sea however this is not as simple as going to the market and buying whatever kind of fish you find, there are several variables that are needed to be considered and this drives away a lot of consumers away since they understandably don't want to learn about all the properties of the fish and unfortunately, trusting the salesperson is not a good strategy as they are usually just interested in the customer buying the fish. Our project “Find n Fish” aims to tackle this issue by giving user the ability to identify the fish scanned through their phone camera using artificial intelligence and list out all the properties that the fish possess so the user can decide whether it is worth buying for their needs. Our project also has a community aspect to it where all the fish lovers can chime in and help one another by providing guides, recipes, answering questions and more.
Project ObjectivesThe primary objective of our project is to help customers who want to buy fish by identifying the characteristics of the fish scanned through the user’s camera using artificial intelligence. This is providing a list of properties that will help the user in deciding which fish to buy. The properties identified will be but are not limited to, type of fish (freshwater/saltwater), freshness indicator, fish species, estimated weight, number of bones, the best way to cook, market price, and more. Another goal of our project is to establish a community of fish lovers and enthusiasts who can help each other by providing recipes for a particular fish, answering queries, and having general discussions relating to seafood. This effort will help bring out the customer who are hesitant about purchasing and preparing fish themselves into exploring this wonderful, healthy, and tasty world of seafood
Project Implementation MethodIn the first phase of development, Data set collection and Research will be conducted to verify all the existing implementation and their limitations, building a roadmap of the application and capturing the images of different fish for the dataset using a camera. In the next phase, the UI and the structure of the application will be designed along with the foundation for the community features which will include the recipes section and forum posting. After that, the actual implementation of those features will begin. In the third phase, the fish identification and classification model will be trained using the datasets captured in the first phase. Next will be the training of the freshness algorithm and implementation of the models in the application. Finally, the application will be tested for bugs and fixed if needed, and the application will be published on the app store.
Benefits of the Project- Makes easier for a user to buy their fish of choice without any hassle or fraud.
- Users can only identify the fish but can see its internal structure and also check its freshness.
- Contains a community that will help users to connect and share their experiences and queries with each other.
- Not only a user can identify a fish but they can look for ways to cook it accordingly from the recipes exclusive section.
- Local users can easily find fish markets nearby
- UI Implementation - Design the whole application UI, with which the user will interact.
- Backend infrastructure - Building up the whole app backend structure. (Cloud providers and services, Databases, etc.)
- Freshness Algorithm Implementation - Researching and Implementing the freshness identification algorithm along with integration with the backend infrastructure.
- Classification Model Training / Implementation - Training the classification model and integrating it with backend
- App Integration - Integrating the developed backend services and models with the user interface.
- Bug Testing and Fixing - Test the whole app to identify any possible bugs and implement the required changes.
- Publishing App - Publishing the app on the play store.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 80000 | |||
| AWS Cloud Services | Miscellaneous | 3 | 2000 | 6000 |
| Playstore Fee | Miscellaneous | 1 | 4000 | 4000 |
| Digital Camera | Equipment | 1 | 70000 | 70000 |