2015/07/19 by Gautam S. Thakur, Thakur, Gautam S., Budhendra Bhaduri +9
Computer Science · Social Sciences · #C.3 #Computers and Society (cs.CY) #Data Management and Algorithms #FOS: Computer and information sciences #Geographic Information Systems Studies #H.2.8 #Human Mobility and Location-Based Analysis #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1507.05245
openalex publication_date 2015/07/19 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/28
Geospatial intelligence has traditionally relied on the use of archived and unvarying data for planning and exploration purposes. In consequence, the tools and methods that are architected to provide insight and generate projections only rely on such datasets. Albeit, if this approach has proven effective in several cases, such as land use identification and route mapping, it has severely restricted the ability of researchers to inculcate current information in their work. This approach is inadequate in scenarios requiring real-time information to act and to adjust in ever changing dynamic environments, such as evacuation and rescue missions. In this work, we propose PlanetSense, a platform for geospatial intelligence that is built to harness the existing power of archived data and add to that, the dynamics of real-time streams, seamlessly integrated with sophisticated data mining algorithms and analytics tools for generating operational intelligence on the fly. The platform has four main components - i. GeoData Cloud - a data architecture for storing and managing disparate datasets; ii. Mechanism to harvest real-time streaming data; iii. Data analytics framework; iv. Presentation and visualization through web interface and RESTful services. Using two case studies, we underpin the necessity of our platform in modeling ambient population and building occupancy at scale.