GIS4IoRT

Summary of the project The convergence of robotic technologies and sensor networks has generated vast amounts of data with potential applications in several domains like agriculture and urban planning. However, the lack of interoperability between this data and Geographic Information System (GIS) tools poses a challenge. The objective of GIS4IORT project is the development of a “plug and play” and cloud-based middleware to bridge this gap, enabling seamless integration and visualization of multidimensional datasets within GIS environments. A GIS client (QGIS plugin) will also be developed as a user-friendly interface to browse available data and perform spatio-temporal queries within the middleware. GIS4IORT Key components include middleware architecture, cloud-based infrastructure, real-time interrogation of robots, AI-based approaches to ensure data reliability and completeness, spatio-temporal query support in the cloud, GIS integration, and adherence to standards. The middleware will support diverse data types such as Lidar, imagery, and sensor data and will be validated by an agriculture case study. Expected outcomes include advancements in GIS capabilities for several decision-making contexts involving robots and sensor data. Relevance to the topic addressed in the call The project addresses the following topics mentioned in the Chist-era call: “Novel software, hardware and/or architectures to improve performance and scalability of GIS system”: the cloud-based middleware (WP2) will take performance issues inherent to big data into account “General-purpose and automatic tools with outlier detection and data consolidation from multiple sources for GIS applications”: data reliability and completeness of robotic data will be managed through AI and probabilistic approaches (WP1). “Use of GIS-backed geostatistical AI analysis solutions in monitoring risk management and additional applications within urban and rural landscapes”: our validation case study (WP 4) is about agriculture but our development is generic and should be applicable to other domains like urban planning “Development of novel data management systems and/or the reapplication or integration of existing knowledge management systems”: the middleware will be compliant with relevant GIS standards proposed by OGC and ISO (WP 3) “New and novel application of computing techniques for real-time and edge-computing related to spatiotemporal data processing”: the middleware will be able to perform spatio-temporal queries in the cloud and allow real-time interrogation of robot data (WP 1).