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Community Blog Clorofish: Fishing Area Recommendation System

Clorofish: Fishing Area Recommendation System

This project is from the team Monsoon, which was awarded with the Second Prize in the Global AI Innovation Challenge 2021 - Intelligent Weather Forecast for Better life.

This project is from the team Monsoon, which was awarded with the Second Prize in the Global AI Innovation Challenge 2021 - Intelligent Weather Forecast for Better life.

Project Introduction

Clorofish is a fishing area recommendation system based on chlorophyll-A concentration and meteorological parameters. We also provide information on sailing risks for fishermen.

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Solution and Project Value

Indonesia is an archipelagic country, 74.26% of its territory is the ocean. This makes more than 2 million Indonesians work as fishermen. With this vast sea area, it certainly has very abundant marine resources. However, according to the Ministry of Maritime Affairs and Fisheries in 2020, fisheries production in Indonesia has only reached 7.5 million tons; this is quite far from the estimated potential for fisheries production which should be 12.53 million tons. Furthermore, Indonesian territories with high LQ (Location Quotient) value for the fishing industry unfortunately have low production volume instead.

We came up with an idea to help fishermen to maximize fish catches and minimize operating costs by recommending good fishing spots and providing sailing risk matrix map. This is done by combining meteorology, oceanography, and artificial intelligence technology. The fishing spots recommendation is based on the meteorological parameters and chlorophyll-A concentration, which is one of the indicators for phytoplankton abundance. Phytoplankton are essential sources of food for fishes. To predict chlorophyll-A based on meteorological parameters, we use Deep Neural Network. As for predicting the sea wave height and wind speed in certain region for the next day, we use Recurrent Neural Network. It will then be classified by Deep Neural Network as a sailing risk for certain region.

In this Clorofish prototype, we created an information system based on telegram bot. Our service is built using Django framework, Telegram Bot API, and using postgreSQL as database.

Alibaba Cloud Products Used

We used ECS to run our back-end system so that it can be enjoyed by all Telegram users wherever they are for 24 hours.

To support the system, we used the ApsaraDB database service to get more secure data security.

In this future application development, it’s possible that we will explore using other Alibaba Cloud services such as PAI, MaxCompute, Big Data systems, security, or other services to support our system services.

About the Developer

Hello, we are the Monsoon Team, consisting of three Indonesian youth coming from three different background studies: Instrumentation, Meteorology, and Computer Science. We work on this Clorofish project by combining our background study into interdisciplinary application.

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