Develop Cloud Computing Capability at Streamgages using Amazon Web Services GreenGrass IoT Framework for Camera Image Velocity Gaging

Science Center Objects

We developed an Internet of Things (IoT) prototype and associated cloud infrastructure for camera-based data collection and initial processing of river streamflow using the cloud (fig. 1). This pilot successfully created a hardware and cloud infrastructure to collect and upload video from a camera gage at San Pedro Creek in San Antonio, Texas. Using a ThingLogix Foundry instance in the Amazon W...

We developed an Internet of Things (IoT) prototype and associated cloud infrastructure for camera-based data collection and initial processing of river streamflow using the cloud (fig. 1). This pilot successfully created a hardware and cloud infrastructure to collect and upload video from a camera gage at San Pedro Creek in San Antonio, Texas. Using a ThingLogix Foundry instance in the Amazon Webservices Cloud, we have created a cloud framework that can auto-provision new camera-based gaging equipment, as well as process incoming videos into image frames for the computation of streamflow. Additionally, we began testing of serving timeseries data from a camera gage (water level and CPU temperature) using real-time telemetry. These data are displayed in a web dashboard. This preliminary work has been expanded, and we are now working to incorporate several camera-enabled gages in the Water Mission Area Next Generation Water Observing Systems (NGWOS) Delaware River Basin.



Image caption: Schematic showing the prototype cloud infrastructure consisting of a camera and Raspberry Pi computer observing river conditions, direct telemetry to AWS IoT and ThingLogix Foundry, cloud storage and object management, cloud processing steps using Lambda functions, and data serving through a web dashboard. A ground photo of the installed equipment, and two example camera feed images are shown.



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