Journal article
Activity Recognition for a Smartphone and Web-based Human Mobility Sensing System
Singapore-MIT Alliance1
Department of Management Engineering, Technical University of Denmark2
Transport DTU, Department of Management Engineering, Technical University of Denmark3
Transport Modelling, Department of Management Engineering, Technical University of Denmark4
Massachusetts Institute of Technology5
Activity-based models in transport modeling and prediction are built from a large number of observed trips and their purposes. However, data acquired through traditional interview-based travel surveys is often inaccurate and insufficient. Recently, a human mobility sensing system, called Future Mobility Survey (FMS), was developed and used to collect travel data from more than 1,000 participants.
FMS combines a smartphone and interactive web interface in order to better infer users activities and patterns. This paper presents a model that infers an activity at a certain location. We propose to generate a set of predictive features based on spatial, temporal, transitional, and environmental contexts with an appropriate quantization.
In order to improve the generalization performance of the proposed model, we employ a robust approach with ensemble learning. Empirical results using FMS data demonstrate that the proposed method contributes significantly to providing accurate activity estimates for the user in our travel-sensing application.
Language: | English |
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Publisher: | IEEE |
Year: | 2018 |
Pages: | 5-23 |
ISSN: | 19411294 and 15411672 |
Types: | Journal article |
DOI: | 10.1109/MIS.2018.043741317 |
ORCIDs: | Pereira, Francisco Camara |
Activity recognition FMS data Frequency modulation Global Positioning System Internet Quantization (signal) Statistics activity recognition activity-based models data handling future mobility survey interactive data collection interactive web interface learning (artificial intelligence) mobile computing predictive features smart phones smartphone traditional interview-based travel surveys transport modeling transportation travel data travel industry travel-sensing application urban mobility user interfaces web-based human mobility sensing system