Urban Sensing based on Mobile Phone Data: Approaches, Applications and
Challenges
- URL: http://arxiv.org/abs/2008.12992v1
- Date: Sat, 29 Aug 2020 15:14:03 GMT
- Title: Urban Sensing based on Mobile Phone Data: Approaches, Applications and
Challenges
- Authors: Mohammadhossein Ghahramani, MengChu Zhou, and Gang Wang
- Abstract summary: Much concern in mobile data analysis is related to human beings and their behaviours.
This work aims to review the methods and techniques that have been implemented to discover knowledge from mobile phone data.
- Score: 67.71975391801257
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Data volume grows explosively with the proliferation of powerful smartphones
and innovative mobile applications. The ability to accurately and extensively
monitor and analyze these data is necessary. Much concern in mobile data
analysis is related to human beings and their behaviours. Due to the potential
value that lies behind these massive data, there have been different proposed
approaches for understanding corresponding patterns. To that end, monitoring
people's interactions, whether counting them at fixed locations or tracking
them by generating origin-destination matrices is crucial. The former can be
used to determine the utilization of assets like roads and city attractions.
The latter is valuable when planning transport infrastructure. Such insights
allow a government to predict the adoption of new roads, new public transport
routes, modification of existing infrastructure, and detection of congestion
zones, resulting in more efficient designs and improvement. Smartphone data
exploration can help research in various fields, e.g., urban planning,
transportation, health care, and business marketing. It can also help
organizations in decision making, policy implementation, monitoring and
evaluation at all levels. This work aims to review the methods and techniques
that have been implemented to discover knowledge from mobile phone data. We
classify these existing methods and present a taxonomy of the related work by
discussing their pros and cons.
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