Special Session on Spatiotemporal Big Data Analytics (SBDA2022)
35th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2022)
Overview
Governmental initiatives, such as Society 5.0 and Industry 4.0, aim to promote well-being of the human beings (or society as a whole). These initiatives cover a wide spectrum of real-world applications whose data naturally exist as a spatiotemporal database. Mining spatiotemporal databases can provide useful insights in many real-world applications such as eCommerce, internet of things, agriculture, healthcare, intelligent transportation systems, meteorology and astronomy. In the intelligent transportation systems, spatiotemporal big data analytics can help to detect, control and monitor the set of road segments in which congestion may regularly happen in a transportation network. In meteorology, spatiotemporal big data analytics can help to detect the geographical regions which are regularly prone to droughts. In the internet of things, spatiotemporal big data analytics can help to detect, control and monitor the nearby areas where people were regularly exposed to harmful levels of air pollution.
The 2nd Special session on Spatiotemporal Big Data Analytics is focusing on original research that aim to solve real-world problems using the concepts, tools, and techniques from statistics, data mining, machine learning and artificial intelligence. Papers in this special session are expected to range over a wide spectrum of topics from theoretical results to practical considerations, and from academic research to industrial adoption. Topics of interest include but are not limited to:
- Visionary papers on Society 5.0/Industry 4.0 applications
- Mining spatiotemporal databases
- Mining spatiotemporal data streams
- Mining uncertain spatiotemporal data
- Spatiotemporal multimedia analytics
- Machine learning/Deep learning of spatiotemporal data
- Analytics on Meteorological datasets
- Analytics on Astronomical big data
- Mining lifelog data
- Optimizing machine learning algorithms for spatiotemporal big data
- Energy efficient mining of spatiotemporal big data.
- User interfaces for spatiotemporal applications
- Multi-core and distributed mining algorithms for spatiotemporal big data analytics
- Decision support systems
- Developing intelligent transportation systems
- Case studies
Session Organizers:
- R. Uday Kiran, The University of Aizu, Japan, udayrage@u-aizu.ac.jp
- Sonali Agarwal, Indian Institute of Information Technology-Allahabad, India, sonali@iiita.ac.in
- Minh S. Dao, National Institute of Information and Communications Technology, Tokyo, Japan, dao@nict.go.jp
- Jerry Chun-Wei Lin, Western Norway University of Applied Sciences, Norway, jerrylin@ieee.org
Important Dates
• Paper Submission: January 31, 2022
• Notification of Acceptance: February 28, 2022
• Camera Ready Paper: April 1, 2022
• Conference Dates: July 26-29, 2022
Submission
Submission Site: https://cmt3.research.microsoft.com/IEAAIE2022/Submission/Index
IEA/AIE 2022 