Monday, 09 September 2019 08:09

Wuudis field data collection concept awarded in DatSci 2019

Wuudis service for forest damage monitoring - Data to decisions – awarded as finalist at The European DatSci and AI Awards 2019, organised in collaboration with the Big Data Value Association and Ireland's Centre for Applied AI (CeADAR) yesterday in Dublin, Ireland. This award was continuation of big data business success, as Wuudis Solutions won second prize in Big Data Value PPP Summit in Riga last June.

Wuudis was competing in category “Best use of Data Science in a Start-up /SME” demonstrating Wuudis concept for field data collection scaling to any kind of field data collection and interfacing with authority and 3rd party IT-systems via standard procedures.  Entries to this award must showcase how they have applied data science as part of a live implementation. The judging panel consisted of over 25 Data Science Leaders from across industry and academia to ensure transparency and fairness across the competition.

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The Wuudis concept was developed as a part of EU-funded DataBio and Ministry of Agriculture and Forestry of Finland funded key project for forest digitalization, and launched in November 2018 known as Laatumetsä app for Finnish Forest Centre for crowd sourced forest damage data collection and care works quality monitoring for subsidy payment to forest owners.

Seppo Huurinainen, CEO of Wuudis Solutions underlines: “Our Forests globally are in danger and Wuudis Solutions is in a mission to combat that through open and big-data and artificial intelligence solutions.”

The DatSci 2019 Awards demonstrates and celebrates the Power of Data Science and Artificial Intelligence in driving real business, educational and social outcomes.

Wuudis Solutions Oy

Wuudis Solutions Oy is a forerunning company in forest digitalisation. Wuudis services bring efficiency gains, cost savings and environmental benefits to all operators of forest and bio-based businesses.
We harness the power of big data through integrating Wuudis with multiple forest big data sources in standardized way, and implement intelligent algorithms to make forest management and monitoring simple, systematic, autonomous and cost-effective.
http://www.wuudis.com

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