Problem Statements

Recreational fishing is one of the best sustainable fishing methods which provides enormous social and economic benefit to any country. According to the Australian Bureau of Statistics, it is estimated over 5 million Australian take part in recreational fishing in Australia as a leisure activity. Experienced fishermen, as well as amateurs, will benefit when they go fishing at the right time and the right place. This is because they will bring more fishes home with happy smiles. But the key challenge is many fishermen will go fishing at wrong times and wrong places and often go home without any catch. Fishermen will waste a lot of time and will reduce the interest in the recreational fishing activity. The reason for that is because they do not have real-time information and intelligence with respect to the fishing variables. Though there are many fishing variables, weather information, seasonal patterns, solunar information, chlorophyll data, sea surface temperature (SST), wind direction, sonar and catch information can be considered as the key variables for better prediction. The proposed system will classify those data in a decision tree, execute the artificial intelligence algorithm using Natural Language Processing (NLP) using an approach called extraction based text summarization and predict the most effective time and location for fishing, which will be verified by on ground feedback from fishermen.


The initial idea originated from Sasen. He is the son of our team member Maharaba. He loves fishing and always happy when he catches some fishes. But often disappointed when he comes home with empty handed without any fish. He was always asking his father, "how do we know when the fishes are in Jetty?" So idea sprung. We thought deeply about his problem which is common to everybody and came up with a solution called FishBuddy.

Today we are pitching the FishBuddy mobile application. It is an intelligent application which can gift quality time for your next fishing endeavor. Because it can predict when and where to go fishing and verify using user feedback, to maximize the catch. We are using the data of third-party Sonar information providers, Weather Bureau, IMOS & US Navy observatory data for solunar information. Sonar providers will share information with this platform for a small fee which is covered by revenue from subscription fees and marketing income. Therefore the device management responsibility solely lies with the Sonar providers.

What it does

The system will process through the fishing variables given above and suggests when and where to go fishing. It classifies those data in a decision tree, execute the artificial intelligence algorithm using Natural Language Processing (NLP) using an approach called extraction based text summarization and predicts the most effective time and location for fishing. Further, it analyses SST data from the latest satellite images retrieved from BOM. Chlorophyll data published by IMOS are also considered. So this system can predict the locations and time not only for jetty fishermen but also for recreational fishermen who go on boats. This system will gift quality time among children in the families, amateurs or even experienced fishermen during their fishing endeavor. This system even helps to swap or give away their catches to initiate lasting interactions and friendships. We know that a lot of communities with different cultures will have different taste buds. Some will not prefer mackerels to consume but whereas for others it could be a delicacy. FishBuddy gives a marvelous opportunity to create friendships by promoting activity-based social networks. Another benefit of FishBuddy indirect benefit of the app is that it promotes sharing help to develop the psycho-social development in children, encouraging good ethics such as generosity by giving away their catch to someone who likes and improving their communication skills. Fishing also is proven to help children develop their gross and fine motor skills, concentration, judgment and reaction. There's even a voice-to-text feature in the app, which allows hands-free operation of the app when hands are wet or dirty.

How we built it

We build our initial idea on papers and then mocked up using a rapid wire-framing tool called Balsamiq. Then we started to do the usability tests with our team members, with my kids and finally came up with a user-friendly version for native development. During this weekend we use Android Studio to build our native Android application and a web application to process the artificial intelligence algorithm.

Challenges we ran into

We initially wanted to introduce a community-driven fish market in this application. But due to the complexity and time constraints, we finally decided not to include that feature in this version. All team members agreed to it and focused only on the main theme of our app that is "gifting quality time".

Accomplishments that we're proud of

We are very much happy since this application can bring happiness and improve fine qualities such as generosity. Because “There is more happiness in giving than there is in receiving.”

What we learned

We learned to focus and how to get rid of unwanted complexities and clutter from an application when adding features. We understood the importance of usability testing. Meeting client's requirements and make them happy is still the golden rule we all learned.

What's next for FishBuddy


FishBuddy2 will be called as TARU. It will be focused on deep sea commercial fishermen.

TARU can predict best fishing locations for commercial deep sea fishermen based on weather, solunar (Solar and Lunar) data, satellite images, and sea temperature. An intelligent web service will inform the locations based on SST (Sea Surface Temperature), sea current, and color of the water (Based on the Chlorophyll data). TARU is ideal for commercial fishermen to plan their voyage and find the temperature breaks and swell breaks using the latest satellite imaging technologies and meteorological data sets. Fishermen those who registered to this valuable service will get their notifications real-time. So that they can plot their course effectively. This will help to decrease the overall fuel consumption in commercial fishing endeavors.

Mostly fishes like to stay in their comfortable sea temperature zones. They usually swim across the temperature breaks to find their comfy zones. These breaks, therefore, will make very good areas for small fishes as well as big game fishes. Apart from that using clear satellite images as well as Chlorophyll data-sets published by IMOS, we can define the areas where Chlorophyll are. These green patches are also proved to be very attractive areas for small fishes as well as big game fishes.

Not only the sea surface temperature but the direction of the wind also very important factor when fishing. According to most experienced fishermen, fishes usually bite when the wind is westerly and southerly along the warm current in the temperature breaks. It means there is a very high chance of taking bites by the fishes like tuna, marlin or mahi-mahi when the winds are coming from the west, south-west, south. But very less chance when the wind is directed from North.

This software will process the SST breaks (Warm Streams), wind direction, wind speed and many other fishing factors used in offshore fishing.

Find more about TARU prototype on

The other solution we can try to address in future is a community-driven fish markets around jetties and wharf. People who want to buy fresh and affordable seafood can benefit from this system. Not only it benefits to the fishermen but to the local communities who want to buy fresh and affordable seafood from nearby Jetties.

Apart from that, it creates a platform for fishermen to sell their catches. Seafood enthusiasts in the neighborhood will flock around in the nearby wharf to buy their delicacies or they can wait to be delivered to their doorstep. As we mentioned earlier communities with different cultures will have different taste buds. The future system will allow the fishermen to build interactions with members in the other communities and subcultures by selling their catch at an affordable rate or by giving away them free of charge. Governments also will earn more revenue by selling their fishing licenses for the fish dealers.

Business Case

We have a very straightforward business case. There are over 5 million recreational fishermen and we are looking to capture 5% of the market during the 1st year which will bring us the estimated revenue of $15,000,000 from $5 per user per month. We are estimating around $400,000 for product development, installation, and marketing during the first year. Every business has its own risks. For FishBuddy we identified that the sudden appearance of seals in the water could chase the fishes away suddenly. In such rare situations, the predictions could go wrong. To overcome that, FishBuddy members can send alerts to each other through the app on such unfavorable events.

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