An American defense company addresses privacy concerns of the US citizens for geospatial imagery using Cloud-enabled Drone Privacy System
About the Client
Based in Virginia, US, our client is a defense company that provides engineering, technical, systems integration, and scientific services to various departments of United States, including the NSA, and other U.S. government civil agencies & few commercial markets. Its major focus areas are offering geospatial & intelligence analysis, air service solutions, supporting operations efforts, and cybersecurity services. Our client works across various locations in 30 countries and has a reported annual revenue of $10 billion in 2016.
The Cloud-enabled Drone privacy system supports resolution-degradation of IoT-originated, geospatial imagery. The system based on an Azure-installed privacy registration service has the potential to serve as a privacy guard for citizens. It can also reduce liability related to publishing imagery of property without an owner’s permission.
Unmanned Aerial Systems (aka Drones) are now being approved by the FAA for a number of commercial uses and the expectation is that use cases will continue to expand as the Government begins to consider longer-range operations that are enabled through Beyond Line of Sight (BLOS) operations. Drones flew over homes, businesses and other sensitive geographic areas to capture aerial imagery, which can be published or shown on media channels (e.g., YouTube, Facebook).
Our client uses these drone images to augment with geospatial metadata used in the processing of orthomosaics, 3D digital terrain models and other artifacts. Many of these metadata features are integrated with on-board applications. These applications bind flight controller and payload (e.g., camera) data into geo-tag metadata. The raw imagery captured by drones & metadata are then used for image processing to produce a variety of digital imagery products for engineering and entertainment purposes. These products will often have privacy-sensitive information of private properties and commercial organizations may find themselves liable for exposure of such data. As drones proliferate and are flown over homes, businesses and other sensitive geographic areas, the client was seeing a rise in citizen privacy concerns. Therefore, the company wanted a cloud-enabled system that can help them eliminate these concerns and provide strong support for resolution degradation of IoT-originated geospatial images.
Using today’s geotagging technology as a starting point, Microsoft Azure was leveraged to host privacy protection services for the US citizens. Our team architected a robust framework with Azure IoT Suite to ensure data accessibility, scalability, reliability & security. The team started with a 3D .TIFF image orthomosaic collection as a proof of concept.
Drone - Unmanned Aerial System uses IP enabled devices to transport images (.tiff files) and Meta data to Azure App Service and Azure IoT Hub respectively and stores images in Azure Blob storage.
Azure Drone filtering service matches database of restricted imagery collection areas against TIFF image metadata coordinates and gives output of specific image location to be degraded. The geotagged tiff files are further processed and returns with privacy regions filtered.
Web Interface that allows the imagery vendors to check & ensure that their products have been resolution-scrubbed as per the geospatial boundaries and limits provided.
Our IoT Consultants integrated the solution with the back end systems and processes that allows the citizens or others to enter coordinates (latitude/longitude points or single point and radius) that are completely off-limits for publishing, which are stored in Azure table storage. The solution has the potential to support other media types including streaming media (e.g., video) as well. This Cloud-enabled Drone Privacy System has the potential to serve as a privacy guard for citizens as well as reduce liability related to publishing imagery of property without an owner’s permission.
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