Artificial Intelligence for 3D Big Spatial Data Processing
Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 10578
Interests: 3D indoor modelling; 3D GIS; integration of BIM and GIS; 3D spatial analysis; DBMS; emergency response
Special Issues, Collections and Topics in MDPI journals
Interests: geo-enabled computing framework based on gis; location-based services; spatiotemporal databases; big data analysis; cyber-physical cloud computing
Interests: point cloud data management, processing, and analysis; spatial data processing, big data management, processing, and mining; real-time data processing (stream data processing); transaction processing; data warehousing and data mining; online analytical processing (OLAP); parallel and distributed data processing; statistical modeling; uncertain data processing
The Second International Workshop on Artificial Intelligence for 3D Big Spatial Data Processing (AI3D 2019, https://sites.google.com/view/ai3d2019/home), co-located with IEEE ISM 2019, will be from 9 to 11 December 2019 in San Diego, California, USA. The AI3D 2019 is intended to provide a common forum for researchers, scientists, engineers, and practitioners throughout the world to present their latest research findings, developments, and applications in the area of Artificial Intelligence for 3D big spatial data processing.
Recent advances in laser technology have resulted in the generation of a massive amount of 3D spatial data. The 3D spatial data offer a useful source of information for natural resource management, urban planning, autonomous driving, etc. Artificial intelligence (AI) has the potential to take the 3D spatial data processing into hyper-growth. Recently, 3D indoor mapping systems, terrestrial mobile mapping systems (MMS), and airborne LiDAR systems have become able to collect terabytes of data (including images and point clouds) in a single scan or on a single trip. Existing approaches and tools, however, lack the efficient management, processing, and analysis of 3D spatial data. The solution to this problem lies in the use of Artificial Intelligence and deep learning to redefine the workflow. This workshop focuses on the use of Artificial Intelligence and deep learning to improve the processing, management, and analysis of 3D Big Spatial data. The workshop aims at providing a platform to the group of researchers working in this direction to share their work, exchange ideas, and solve research problems.
To enable the researchers to publish the extended versions of their work in a journal in a timely manner, we have planned a Special Issue for the AI3D 2019 workshop. The Special Issue will contain a selection of papers submitted, accepted, and presented at AI3D 2019. We warmly invite researchers to submit their contributions to this Special Issue. A list of topics of interest includes but is not limited to:
- AI and the 3D scanning technologies and devices;
- Use of AI in 3D view registration and surface modeling;
- Intelligent LiDAR data processing, management and analysis;
- Point cloud data processing and analysis;
- 3D modeling and depth image processing;
- Spatiotemporal data processing and analysis;
- Geospatial data processing and analysis;
- Distributed, parallel, and peer-to-peer approaches to index, search and process 3D big spatial data;
- AI-based object detection from point cloud and images;
- Supervised/unsupervised object annotation in 3D data;
- Point cloud data indexing and querying;
- 3D big spatial data architectures;
- 3D big spatial data visualization and analytics;
- 3D big spatial data cleaning, compression, and integration;
- Geographic information retrieval;
- Indoor and outdoor mapping;
- 3D mapping;
- Urban planning;
- Spatial data applications;
- User interfaces and visualization.
Prof. Dr. Sisi Zlatanova
Dr. Kyoung-Sook Kim
Dr. Salman Ahmed Shaikh
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