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2020 Automated Streams Analysis for Public Safety Prize Challenge

This image depicts "ASAPS" in blue text and "Autmoated Streams Analysis for Public Safety Challenge" beneath

The Automated Streams Analysis for Public Safety (ASAPS) Prize Challenge is an open innovation program focused on the development of algorithms to detect and analyze a variety of emergency events from unstructured public safety data in real time. The increasing magnitude of live data from a variety of sources presents both a challenge and opportunity to public safety in making life-critical decisions regarding response and coordination to emergencies. The ASAPS Challenge is an AI challenge to detect, analyze, and alert public safety to emergencies from streaming data where every second counts. ASAPS fosters groundbreaking multidisciplinary research and innovation in real-time emergency data analytics using a first-of-its-kind data set of unstructured video, audio, textual communications, social media, and sensors. The challenge is segmented into a series of contests, detailed here: https://www.nist.gov/publications/automated-streams-analysis-public-saf… 


ASAPS Contest 1

ASAPS Contest 1 began in May 2020 and completed in September 2020. This contest was the first in the series and was designed to "kick-off" the ASAPS Challenge by assessing today's state-of-the-art and envisioning new ideas to better leverage multi-modal data streams and real-time data processing to support public safety's mission. This first contest concluded with six awards of $30,000 each to top contestants, totaling $180,000 for the most compelling ideas. Learn more about the winning contestants and their entries below

Topic Prize Awarded (Fall 2020) Submission Title Team Members
Topic 1: Information Extraction Across ASAPS Streams and Data Sources Across 1 or More Data Categories $30,000 Multimodal Fusion for Public Safety Analytics Dan Morozoff, Joe Ellis, Gianni, Peter Njenga (Vidrovr), Connor O'Day
Topic 2: Information Fusion Across Extracted Data and Generation of Live/Dynamic Information Representation Across 3 or More Data Categories $30,000 Scalable Data Fusion for Real-Time Event Detection Mehmet Aktukmak, Keval Doshi (University of South Florida), Yasin Yilmaz
Topic 2: Information Fusion Across Extracted Data and Generation of Live/Dynamic Information Representation Across 3 or More Data Categories $30,000 Balancing Space and Time with Asynchronous Models Jason Corso (University of Michigan), Chenliang Xu (University of Rochester), Yan Tom Yan (Texas State University)
Topic 3: Automated Emergency Event Analysis Across 3 or More Data Stream Categories, and Preferably Across All Data Categories $30,000 NEURATRACE: Detect, Trace, & Analyze Emergencies Madhukar Karmacharya, Kumar Apurv, Ananth BhimiReddy, Aamir Kahn, Archith Krishnan Rammohan, SaiManoharReddy Peddireddy (Indiana University/Indiana Purdue University), Sahitesh Reddypelly
Topic 4: Extraction to Analysis Systems Approach Across All Data Categories $30,000 Modular Design for Automated Event Analysis Dr. Roy Hayes Jr., Admiral Guy Curtis, Roy Hayes Sr., William Kimbark, Sreya Palnati, Tom Slattery (Systems Engineering Inc.)
Topic 4: Extraction to Analysis Systems Approach Across All Data Categories $30,000 Real-Time Multi-Source Event Analytics Alexander G. Hauptmann (CMU), Junwei Liang (CMU), Mubarak Shah (UCF), Yogesh Singh Rawat (UCF), Praveen Tirupattur (UCF), Shruti Vyas (UCF)

ASAPS Contest 2

ASAPS Contest 2 is in development and additional details are coming soon! To learn more about the data set created for this program and be the first to hear when details are available visit: https://www.asapschallenge.ai/


Learn more at https://www.asapschallenge.ai/

Created May 5, 2020, Updated July 12, 2021