It is now widely accepted that human behaviour accounts for a large portion of total global emissions, and thus influences climate change to a large extent. Changing human behaviour when it comes to mode of transportation is one component which could make a difference in the long term. In order to achieve behavioural change, we investigate the use of a persuasive multiplayer game. Transportation mode recognition is used within the game to provide bonuses and penalties to users based on their daily choices regarding transportation. To easily identify modes of transportation, an approach to transport recognition based on accelerometer and gyroscope data is analysed and extended. Preliminary results from the machine learning tests show that the classification true-positive rate for recognizing 10 different classes can reach up to 95% when using a history set (66% without). Preliminary results from testers of the game indicate that using games may be successful in causing positive change in user behaviour. / <p>Del av Erasmus Mundus PERCCOM. Redovisning skedde på anordnad summer school av partner-universitet där hela konsortiet närvarade.</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-65348 |
| Date | January 2017 |
| Creators | Hedemalm, Emil |
| Publisher | Luleå tekniska universitet, Institutionen för system- och rymdteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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