Abstract
A number of web-based systems provide environmental information to support our ecological lifestyle. However, there exists a need for more accurate and automated online systems facilitating personalised ecological awareness. This paper presents a travel type detection system for an automatic mobile carbon emission calculator. The system is able to detect automatically trips made by mobile users and provide them an easy and quick way for estimating the travel related CO2 emissions. The system is based on energy and computationally effective multisource fusion in a mobile device. The paper introduces the system with design rationale, explains smartphone implementation and provides comprehensive evaluation from both accuracy and energy efficiency points of view. The system attained the overall travel type detection accuracy of 77% and the daily average current consumption of 33mA. The results show great promise for the developed methodology to facilitate 24/7 carbon emission estimation of a traveller.
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Könönen, V. et al. (2011). Anatomy of Automatic Mobile Carbon Footprint Calculator. In: Riekki, J., Ylianttila, M., Guo, M. (eds) Advances in Grid and Pervasive Computing. GPC 2011. Lecture Notes in Computer Science, vol 6646. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20754-9_10
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DOI: https://doi.org/10.1007/978-3-642-20754-9_10
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