Sensor data is available in many formats, but sharing this data with other analysts isn’t easy, given that most sensor solutions utilize proprietary messaging that limits communication to their own specific GUIs and services. However, reengineering these existing solutions to normalize data into open standards for easy consumption is not only expensive but also time-consuming, particularly when sensor data is used for mission-critical purposes.
The Sensor Data Server (SDS) transforms data sources from one format to another, providing a solution for multidisciplinary communication of collected intelligence. Designed for scalability, resilience, and high performance, SDS readily connects data with other sensors or down-range systems via plug-ins, effectively normalizing disparate data for easy access and rapid deployment.
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SDS utilizes a Service-Oriented Architecture (SOA)-based approach to streamline transformation of raw, multiformat data into a flexible data set that is readily adaptive and sharable with extensible plug-in models. This allows application developers to program and choose plug-ins specific to the messaging required, permitting conversion of an unlimited amount of data types for use by other systems. SDS accesses standard plug-in libraries, making data conversion possible with a simple client request that connects one plug-in type to another. Also, application developers can easily create plug-ins for which there currently is no existing one in the standard library.
SDS is built on open-source technologies utilizing Java for platform-independence to allow for seamless integration with current systems. Removing cumbersome restrictions, SDS permits development by third parties to extend the built-in conversion capabilities of its standard libraries to allow for the processing of new sensor data formats and protocols. Such extensibility allows SDS to operate as a “central hub,” allowing disparate systems to communicate and distinct message formats to be transformed.
SDS is designed with realistic scalability in mind, making it adaptable for any mission use—from embedded devices and removable storage systems to the most powerful server technologies. Its core framework and existing plug-ins can be used, without modifications, for deployments of any size.
SDS employs the Adaptive Extensible Markup Language (XML) Logging Environment (AXLE), a powerful yet flexible data mining solution. AXLE subscribes to multidisciplinary data streams, to include sensor messages, to collect and synchronize these sources. Its easy-to-use, HTML5-based recording and playback console allows users to gain insight on real-time data via integration, search, edit, and playback features. By leveraging these tools, users can mine for data at the record level as well as the raw level.