Efficient Data Analysis in Everyday Crises
Dr. Ranga Raju Vatsavi, Associate Professor of Computer Science at NC State, has been awarded $60,000 by the Center for Accelerated Real Time Analytics (CARTA) to support his research proposal entitled “Near Real-Time Analytics on Embedded Edge Computing Devices, CARTA Core Project”.
The award will run from July 1, 2019 to June 30, 2020.
Abstract – In many real-world applications, data loses its value if it’s not analyzed in near real time. Examples include natural disasters, crop disease identification and bioterrorism, traffic monitoring, monitoring human activities and public places. Edge computing refers to pushing computing power to the edge of the network or bringing it closer to the sensors. We envision that the embedded supercomputers (e.g., Jetson TX1 and TX2; 1 Teraflop; ~10 Watts) allow computing at the edge (e.g., UAVs). This framework would then allow near real-time analytics on streaming data, which is critical for first responders to national security agencies alike, and compress/reduce data before transmitted to the cloud or data centers. In this project, we propose to develop novel machine learning algorithms on the embedded supercomputers while the data is still in device memory and demonstrate the technology in two real-world applications: crop monitoring and traffic monitoring. Proposed technical work involves following three key stages. (i) Generate a statistical model from historical data (e.g., spectral signatures of different crops) by using statistically principled mixture model (e.g., Gaussian Mixture Model (GMM)), (ii) As the data is being acquired compare new (streaming) data with the GMM model to identify any anomalous patterns (e.g., weeds), (iii) generate event signal about the anomaly before the data is being compressed and transferred out from devise memory.
For more information on Dr. Vatsavai, click here.
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