Emerging Techniques of AI for Mobility Analysis and Mining
A special issue of Future Internet (ISSN 1999-5903).
Deadline for manuscript submissions: closed (20 June 2019) | Viewed by 4239
Special Issue Editors
2. Scuola Normale Superiore, 56126 Pisa, Italy
Interests: mobility data science; computational social science; human-centered AI; human–AI coevolution
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The availability of massive digital traces of human movements, such as call detail records (CDR) from mobile phones, GPS traces from phones and vehicles, and check-ins from social media platforms, offers the opportunity to investigate the quantitative patterns characterizing human mobility at different spatiotemporal resolutions. This broad social microscope has attracted scientists from diverse disciplines, from physics and network science to data mining, fueling advances from public health to transportation engineering and urban planning.
Artificial intelligence (AI), especially deep learning techniques, is increasingly used in the context of human mobility analysis with the purpose of (i) designing more accurate algorithms for predicting the future whereabouts of individuals, (ii) extracting complex patterns capturing the mobility habits of individuals, (iii) performing semantic enrichment of mobility information, and (iv) generating synthetic trajectories which are realistic in reproducing the mobility patterns of individuals.
This Special Issue will collect contributions on the recent advances and emerging techniques in using AI for human mobility analysis, mining, and modeling. This issue welcomes submissions of high-quality articles containing original research results and survey articles of exceptional merit.
Potential topics include, but are not limited to:
- Next location and trajectory prediction
- Modeling and simulation of human mobility and generation of synthetic trajectories
- Application of Machine Learning and Deep Learning to human mobility
- Mobility data mining
- AI techniques to estimate commute and migration flows
- Prediction of traffic congestion and road usage
- Activity Recognition and modeling
Dr. Salvatore Rinzivillo
Dr. Luca Pappalardo
Dr. Vinicius Cezar Monteiro de Lira
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- human mobility
- artificial intelligence
- mobility data mining
- location prediction
- mathematical modeling
- traffic forecasting
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