An understanding of the terms below is helpful when using ArcGIS Velocity.
A feed is a real-time stream of data coming into ArcGIS Velocity. Feeds typically connect to external sources of observational data such as Internet of Things (IoT) platforms, message brokers, or third-party APIs. Feeds parse incoming tabular, point, polyline, or polygon data and expose it for analysis and visualization. A feed is also a type of stream layer and can be added to a map to view new information as soon as it is received. For details, see Feed types and Collect real-time data.
A real-time analytic performs processing on data collected through a feed and analyzes each individual message as it is received. Real-time analytics are used for transforming data, geofencing, and incident detection. Real-time analytics conclude with one or more outputs such as storing data in a feature layer or sending an email alert. For details, see Perform real-time analysis.
Big data analytic
A big data analytic performs batch analysis on stored data such as data in a feature layer or in cloud big data stores such as Amazon S3 and Azure Blob. Big data analytics are typically used for summarizing observations, performing pattern analysis, and incident detection. Big data analytics conclude with one or more outputs such as storing data in a feature layer or sending an email alert. For details, see Perform big data analysis.
A data source is an input in a real-time or big data analytic that loads a set of stored information. This is often historical observations but can also be standard geographies or features that enrich observations with additional attributes. Data sources load information from ArcGIS feature or map image layers or external cloud stores and can parse tabular, point, polyline, or polygon data. For details, see Data sources and Ingest historical data.
Geofencing is a form of real-time spatial analysis in which features (often track points) are assessed using areas of interest (often polygon areas). Most commonly, point-based observations are analyzed to determine if they have entered or exited a virtual perimeter. Geofencing examples also include understanding if a storm is approaching or currently affecting an organization's facilities, if an infrastructure pipeline intersects a flood warning area, or if a fleet vehicle has deviated from its assigned route.
Geofencing can be performed in many ArcGIS Velocity real-time and big data analytic tools to identify certain spatial relationships that may occur between features in a target feed or data source and a set of join features (the geofences) in another feed or data source. The features used as geofences should be in a feed or data source connected to the join port of the tool. If the join features do not change, use a static data source for the best performance. For details, see Geofencing analysis.
Several real-time analytic tools allow you to perform dynamic geofencing to identify certain spatial relationships that may occur between features in a target feed and a set of features in a join feed (the geofences), both of which are updating in real time or near real time. The tool performing the geofencing uses the most recent observation of any given track ID as geofences. For details, see Geofencing analysis.
An output is the final step in a real-time or big data analytic that defines how analytic results are handled. Outputs can take a variety of actions such as storing features to a feature layer, sending features to a stream layer, sending an email alert, or actuating IoT device behavior through a cloud platform such as Azure IoT Hub. For details, see Outputs and Fundamentals of analytic outputs.
A stream layer is the layer in a stream service, which is a type of ArcGIS service that provides access to a live data stream. Each stream layer corresponds to a specific geometric type: point, polyline, or polygon. Stream layers visualize new features on the map as soon as they are received because they subscribe to a WebSocket over which the data is flowing. For details, see Stream Layer.
A Track ID is a field in an incoming event or dataset that relates observations to specific entities. For example, a truck might be identified by its license plate number or an aircraft by an assigned flight number. These identifiers can be used to track the events associated with a particular real-world entity or set of incidents. A Track ID is specified as part of a feed or data source schema. For details, see Configure input data.
Actuation refers to the action of causing a machine or device to operate and is often the desired outcome of an(IoT analysis process—for example triggering air conditioning systems automatically when heat waves are expected or unlocking a security gate when an authorized vehicle is in close proximity. In ArcGIS Velocity, outcomes from real-time or big data analytics can be used to actuate devices or systems in external systems through outputs such as HTTP or sending messages to an output broker that can route commands to devices such as Azure IoT Hub or Kafka. For details, see Fundamentals of analytic outputs.