Real-World Applications of Oracle Spatial AI

Oracle Spatial AI can be used to add value in several application areas.

• Spatial Data Analysis and Modeling

  Geospatial data scientists and application users can leverage Oracle Spatial AI to prepare and analyze data stored in Oracle Spatial and OCI object storage, train spatial machine learning models, and apply these models in a variety of applications. For example, users can use clustering, regionalization, and anomaly detection techniques to identify spatial patterns and anomalies. Users can also apply spatial regression and classification techniques to do predictive analysis.

• Enterprise Applications

  Enterprise applications include HCM, ERP, CRM, and industry solutions for utilities, defense, and public sectors. Most business data have a spatial component and therefore spatial analyzing and modeling capabilities adds significant value to those applications. For example, HR systems can leverage clustering to analyze grievances, safety violations, and disciplinary hot spots. Utility applications may train models to detect electric vehicle charging locations from their heavy load.

• OML Functionalities

  Oracle Spatial AI is delivered as part of OML. It fully leverages OML functionalities and complements OML by adding spatial modeling capabilities. Spatial AI, together with OML, enhances the user experience for data scientists and, in particular, geospatial users.