Artificial intelligence for automatized monitoring of water quality and vegetation biodiversity (AIWaterBio)


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Levää Helsingin Hieltarannassa 2018
Fig. 1 Algae bloom in near the Hietaranta beach in Helsinki was causuing harm for swimming and fishing. Alage was recognized with over 90 percent reliability. © Jari Silander.

Research questions

  • Can crowd data be used to classify algal bloom levels to improve national algal bloom forecasts and reduce monitoring effort of experts?
  • What valuable features can be extracted from the data?


The project supports the MONITOR 2020 program, which develops the effectiveness and cost-effectiveness of monitoring by improving methodology, processes, networking, quality and data usage.

Additionial information

Senior researcher Jari Silander, puh: +358 295 251 638,

Published 2020-08-10 at 16:54, updated 2020-08-13 at 14:24

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