Personalized travel mode detection with smartphone sensors

Xing Su, Yuan Yao, Qing He, Jie Lu, Hanghang Tong
2017 2017 IEEE International Conference on Big Data (Big Data)  
Travel Mode Identification with Smartphone Sensors by Xing Su Advisor: Hanghang Tong Personal trips in a modern urban society typically involve multiple travel modes. Recognizing a traveller's transportation mode is not only critical to personal context-awareness in related applications, but also essential to urban traffic operations, transportation planning, and facility design. While the state of the art in travel mode recognition mainly relies on large-scale infrastructure-based fixed
more » ... or on individuals' GPS devices, the emergence of the smartphone provides a promising alternative with its ever-growing computing, networking, and sensing powers. In this thesis, we propose new algorithms for travel mode identification using smartphone sensors. The prototype system is built upon the latest Android and iOS platforms with multimodality sensors. It takes smartphone sensor data as the input, and aims to identify six travel modes: walking, jogging, bicycling, driving a car, riding a bus, taking a subway. The methods and algorithms presented in our work are guided by two key design principles. First, careful consideration of smartphones' limited computing resources and batteries should be taken. Second, careful balancing of the following dimensions (i) user-adaptability, (ii) energy efficiency, and (iii) computation speed. First I would like to express my sincere gratitude to my advisor Prof. Hanghang Tong for the continuous support of my PhD study and related research, for his immense knowledge and experience in guiding the work. His guidance helped me in all the time of research and writing of this thesis. I am grateful for his patience, motivation and encouragement throughtout the PhD study. I am very thankful for all of the time he spent on writing, editing and revising papers and his help in putting with insightful advise, professional suggestions and comments. I would like to also give my sincere thanks to Professor Robert Haralick, for his generous help in spending time work on problems with me, patiently explain the methodology and related knowledge to me whenever I needed. I learnt a lot while working with him. Many thanks to my department Assistant Program Officer Ms. Dilvania Rodriguez and former APO Ms. Lina Garcia. They are kindhearted colleagues who were always there and offer help, support and advise for us. Their beautiful personality makes the computer science department like a big family. anonymous volunteers for taking time out of their busy schedules and traveled over places in the city to collect useful data.
doi:10.1109/bigdata.2017.8258065 dblp:conf/bigdataconf/SuYHLT17 fatcat:lfiv7ufbgba7vgq36tetije43q