Abstract
In this study, with Estonia as an example,we established an approach based on Hidden Markov Model to extract large-scale commuting patterns at different geographical levels using a massive amount of mobile phone cellular network data, which is referred to as Call detail record (CDR). The proposed model is designed for reconstructing and transforming the trajectories extracted from the CDR data. This step allowed us to perform origin-destination matrix extraction among different geographical levels, which helped in depicting the commuting patterns. Besides, we introduced different techniques for analyzing the commuting at the urban level. Our results unveiled that there is great potential behind mobile data of the cellular networks after transforming it into meaningful mobility patterns. That can easily be used for understanding urban dynamics, large-scale daily commuting and mobility. The aggressive development and growth of ubiquitous mobile sensing have generated valuable data that can be used with our approach for providing answers and solutions to the growing problems of transportation, urbanization and sustainability.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
