EutrophicationLevels Prediction Algorithm (E.L.P.A.)

Weare a group of five students, four studying Electrical and ComputerEngineering, and one studying Chemistry. In this Space Apps Challengewe decided to study the problem of eutrophication and algal blooms,an important phenomenon that impacts oceans, lakes and rivers allaround the world. The release of nutrients such as nitric andphosphoric ions in the water, causes the extreme growth of algae,which consumes all the oxygen found under water. Thus, livingorganisms such as fish die, toxical substances are released, and thewater is not safe for drinking or swimming. Our approach to theproblem is to predict the growth of algae, so that better measurescan be taken. The main idea is to develop a neural network that willbe fed with data from satellite imagery, obtained from satellitessuch as ESA's Sentinel 2 and 3. These data include water and airtemperature,and the colour of water. Other data can be obtained from samplingwater, and measuring chlorophyll levels, pH, concentration ofsubstances such as ammonia etc. We obtained these from the Centraland Northern California Ocean Observing System (CNCOON). Ourneural network wasmade with Matlab and processedthis information, and after being trained produceda prediction of how algae population will evolve in the San FransiscoBay in theyear 2020.Of course, given enough data, we could apply the same principles toany area of the world. Our project also includes the construction ofa machine at the surface of a river, lake or sea, that will collectdata by sampling the water. This will run on solar energy, capturedby panels on top of it.

Ouridea is still at an early stage, namely a Technology Readiness Level(TRL) of 3. But given enough time and data, we could further evolveit, and turn it into a product that could be utilized by governmentsand environnmentalist organizations.

Teammembers:
1.Emmanouilidis George

2.Liliopoulos Ioannis

3.Metallidou Nefeli

4.Sianti Eleni

5.Tsismanidis George