Yliopiston etusivulle Suomeksi På svenska In English Helsingin yliopisto

Continuous and Energy-Efficient Transportation Behavior Monitoring

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dc.contributor Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta, Tietojenkäsittelytieteen laitos fi
dc.contributor.author Hemminki, Samuli fi
dc.date.accessioned 2012-11-19T13:00:48Z
dc.date.available 2012-11-19T13:00:48Z
dc.date.issued 2012-11-19
dc.identifier.uri http://hdl.handle.net/10138/37588
dc.description.abstract In this thesis we present and evaluate a novel approach for energy-efficient and continuous transportation behavior monitoring for smartphones. Our work builds on a novel adaptive hierarchical sensor management scheme (HASMET), which decomposes the classification task into smaller subtasks. In comparison to previous work, our approach improves the task of transportation behavior monitoring on three aspects. First, by employing only the minimal set of necessary sensors for each subtask, we are able to significantly reduce power consumption of the detection task. Second, using the hierarchical decomposition, we are able to tailor features and classifiers for each subtask, improving the accuracy and robustness of the detection task. Third, we are able to extend the detectable motorised modalities to cover most common public transportation vehicles. All of these attributes are highly desirable for real-time transportation behavior monitoring and serve as important steps toward implementing the first truly practical transportation behavior monitoring on mobile phones. In the course of the research, we have developed an Android application for sensor data collection and utilized it to collect over 200 hours of transportation data, along with 2.5 hours of energy consumption data of the sensors. We apply our method on the data to demonstrate that compared to current state-of-art, our method offers higher detection accuracy, provides more robust transportation behavior monitoring and achieves significant reduction in power consumption. For evaluating results with respect to the continuous nature of the transportation behavior monitoring, we use event and frame-based metrics presented by Ward et al. fi
dc.language.iso en fi
dc.title Continuous and Energy-Efficient Transportation Behavior Monitoring fi
dc.type.ontasot Pro gradu -työ fi
dc.subject.discipline Tietojenkäsittelytiede fi

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