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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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202 records · Page 12

Computer Vision on Edge Devices for the Short Term Prediction of Cloud Cover

Edge Computing and IoT are important pieces of today's technological landscape. Here, we build a low-cost IoT sensor for sky imaging and program it using AWS GreenGrass, one of the leading IoT platforms. We demonstrate remote reprogramming of this device to load software that predicts sun shading events through the linear advection method, which is a baseline algorithm that can be used to benchmark algorithmic improvements in future work. Some future directions for sky imaging research are enumerated.

14 SOLAR ENERGY↗

Surveilling Influenza Incidence With Centers for Disease Control and Prevention Web Traffic Data: Demonstration Using a Novel Dataset

Influenza epidemics result in a public health and economic burden worldwide. Traditional surveillance techniques, which rely on doctor visits, provide data with a delay of 1 to 2 weeks. A means of obtaining real-time data and forecasting future outbreaks is desirable to provide more timely responses to influenza epidemics. This study aimed to present the first implementation of a novel dataset by demonstrating its ability to supplement traditional disease surveillance at multiple spatial resolutions. We used internet traffic data from the Centers for Disease Control and Prevention (CDC) website to determine the potential usability of this data source. Additionally, we tested the traffic generated by 10 influenza-related pages in 8 states and 9 census divisions within the United States and compared it against clinical surveillance data.

60 APPLIED LIFE SCIENCES↗

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

remote sensing↗