Abstract: An edge computing system is deployed at a physical location and receives an input from one or more image/video sensing mechanisms. The edge computing system executes artificial intelligence image/video processing modules on the received image/video streams and generates metrics by performing spatial analysis on the images/video stream. The metrics are provided to a multi-tenant service computing system where additional artificial intelligence (AI) modules are executed on the metrics to execute perception analytics. Client applications can then be run on the output of the AI modules in the multi-tenant service computing system.

Abstract: An edge computing system is deployed at a physical location and receives an input from one or more image/video sensing mechanisms. The edge computing system executes artificial intelligence image/video processing modules on the received image/video streams and generates metrics by performing spatial analysis on the images/video stream. The metrics are provided to a multi-tenant service computing system where additional artificial intelligence (AI) modules are executed on the metrics to execute perception analytics. Client applications can then be run on the output of the AI modules in the multi-tenant service computing system.

Abstract: An edge computing system is deployed at a physical location and receives an input from one or more image/video sensing mechanisms. The edge computing system executes artificial intelligence image/video processing modules on the received image/video streams and generates metrics by performing spatial analysis on the images/video stream. The metrics are provided to a multi-tenant service computing system where additional artificial intelligence (AI) modules are executed on the metrics to execute perception analytics. Client applications can then be run on the output of the AI modules in the multi-tenant service computing system.

Abstract: An edge computing system is deployed at a physical location and receives an input from one or more image/video sensing mechanisms. The edge computing system executes artificial intelligence image/video processing modules on the received image/video streams and generates metrics by performing spatial analysis on the images/video stream. The metrics are provided to a multi-tenant service computing system where additional artificial intelligence (AI) modules are executed on the metrics to execute perception analytics. Client applications can then be run on the output of the AI modules in the multi-tenant service computing system.

Abstract: A computing device is configured to provide multi-window interaction with a source of hierarchical data. The computing devices includes a display, a processor configured to execute programmatic instructions, and a computer-readable storage media containing a sequence of instructions that, when executed by the processor, provide a thin-client application configured to interact with the source of hierarchical data. The thin-client application provides a first user interface relative to the source of hierarchical data and a second user interface relative to a selection of hierarchical data in the first user interface. The first and second user interfaces are rendered simultaneously in response to a user input requesting multi-window display.

Abstract: Search parameters are generated from search tokens that are entered within a transactional search context. A data provider is selected from a plurality of different data providers for executing a search, using the search tokens. Relevance calculators that calculate the relevance of matching search results, and sorting systems, that sort the search results, can also be selected from a plurality of different relevance calculators and sorting systems. The sorted search results are then displayed.