Inferring Transportation Mode and Human Activity from Mobile Sensing in Daily Life-Reference-Cited by-同舟云学术

Inferring Transportation Mode and Human Activity from Mobile Sensing in Daily Life

Published:2018-11-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
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Author:

Liono Jonathan¹,Abdallah Zahraa S.²,Qin A. K.³,Salim Flora D.¹

Affiliation:

1. Computer Science and Information Technology, School of Science, RMIT University, Melbourne, Victoria, Australia

2. School of Computing and Digital Technology, Birmingham City University, Birmingham, United Kingdom and Information Technology, Monash University, Australia

3. Department of Computer Science and Software Engineering, School of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, Australia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3286978.3287006

Reference40 articles.

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2. RUP: Large Room Utilisation Prediction with carbon dioxide sensor

3. Irvan Bastian Arief-Ang Margaret Hamilton and Flora Dilys Salim. 2018. A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO2 Sensor Data. ACM Transactions on Sensor Networks (2018). 10.1145/3217214 Irvan Bastian Arief-Ang Margaret Hamilton and Flora Dilys Salim. 2018. A Scalable Room Occupancy Prediction with Transferable Time Series Decomposition of CO2 Sensor Data. ACM Transactions on Sensor Networks (2018). 10.1145/3217214

4. DA-HOC

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