$150K Automated Stream Analysis for Public Safety Challenge - Part 1
Develop tools and capabilities to detect and analyze emergency events from live streaming multimodal public safety data
May 19, 2020
Literally every second counts in public safety response to emergency situations. Data-informed tools to alert public safety officials to emergencies, improve their situational awareness, and assist them in making fast and effective deployment decisions that save lives, property, and infrastructure are critically needed. Public safety operations have an ever-increasing amount of live streaming data available to them from public safety communications, sensors, social media, and other publicly available sources of information. Information contained within these data can help public safety make faster and more informed decisions in responding to emergencies. However, identifying and leveraging the nuggets of critically important information in the tremendous mass of ever-expanding data in time to make effective use of it in response decisions is both an opportunity and a challenge to public safety operations.
Currently, analyzing all of this data is tedious, time-consuming, and requires significant human resources. As these streaming data resources grow, public safety is reaching a point of diminishing returns in its ability to manually monitor and analyze these data streams during emergencies since such analyses require increased time and coordination as the number and nature of data resources expand. Since time is of the essence in responding to emergencies, there is an urgent need for advanced real-time analytic tools to support public safety in wading through this mountain of data in detecting, understanding, and responding to emergencies so that precious time isn’t lost in comprehending the data.
Creating the technologies to concurrently digest the many forms and streams of data flowing into public safety operations and support the development of comprehensive, effective, and efficient real-time public safety emergency situation analysis solutions is an unprecedented challenge. This challenge requires innovations that combine the state-of-the-art in artificial intelligence, real-time computing, and high-speed communications, multimodal information analysis and visualization, decision management, advanced information visualization, and user interfaces, and beyond. The ASAPS Challenge The National Institute of Standards and Technology (NIST) Public Safety Communications Research Division (PSCR) is launching the Automated Streams Analysis for Public Safety (ASAPS) Challenge to address this need by fostering ground-breaking multidisciplinary research and innovation in real-time emergency data analytics. The overall vision of this program is to provide public safety with advanced real-time emergency detection, situational awareness, and decision-making capabilities from many live unstructured data streams.
The overall goal of the ASAPS Challenge program is to stimulate R&D in critical technologies that will lead to future products providing public safety with advanced real-time emergency detection, situational awareness, and decision-making capabilities based on input from many live, unstructured data streams. The program is designed to stimulate research in critically important technologies such as AI-based streaming data analysis, evolving emergency event understanding, highly actionable analytic information visualizations, and highly intuitive analytics-driven response-support interfaces that maximize situation awareness while minimizing response time. Additionally, we seek to leverage cross-participant knowledge and expertise, inspire the spirit of competition, and garner potential wins at all levels – from low-level data stream analysis to information fusion to real-time information delivery and interaction.
The ASAPS challenge will play a critical role in improving public safety readiness by accelerating innovation and advancements in:
Agile multimodal analytics and fusion models for streaming data from video, audio, text, social media, and sensor data.
Reusable R&D and test and evaluation frameworks.
Open source analytics development tools and analytic solutions.
Highly actionable analytic information visualization, intuitive information interaction, and decision-support interfaces for emergency situation awareness and response.
Scalable, deployable event detection and analysis tools and methodologies.
Critical mass in R&D related to scalable real-time analytics for public safety.
Research for future analytics interoperability standards.
The ASAPS contests This ASAPS contest 1 is now open for submissions! This contest is the first in a series of four and is designed to jumpstart 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 in the public safety emergency response environment. This first contest anticipates awarding up to a total of $150,000 for the most compelling ideas.
The second contest, ASAPS Contest 2, is scheduled to launch in the summer of 2020. In this contest, which is open to everyone, contestants’ algorithms will be tested for their ability to perform live, automated emergency event analysis across many streams of data flowing from a variety of sources and modalities. Potential contestants of this first contest may view their participation as preparation for the second contest. What is public safety? Public safety is broadly defined as the welfare and protection of the general public. Public safety departments operating at different levels of government (municipal, county, state) ensure the protection of citizens. This protection is afforded through a wide portfolio of services, including law enforcement, fire, emergency medical services, and 911. NIST PSCR works collaboratively with the public safety community to identify technology requirements that are critical to advancing communications capabilities that will enable first responders to more effectively carry out their mission. Who can participate? All stakeholders are welcome to join our growing community of interest. Successful outcomes will require collaboration among contestants with skill sets from across many academic disciplines, sectors, organizations, and technical communities, including: Computer Vision, Human Language Technology, Automatic Speech Recognition, Information Filtering and Retrieval, Information Extraction, Sensor Data Processing, Geographic Information Systems, Knowledge Engineering and Management/Expert Systems, Artificial Intelligence, Machine Learning, Predictive Modeling, Data Science, High-Performance Computing, Distributed Processing, Cloud Computing, Information Visualization, Augmented/Virtual Reality, Operations Research, Public Safety Communications, and Operations.
Contestants may join as individuals or under their affiliation with R&D centers, laboratories, academia, large or small business, industry, and other organizations. There is no requirement for affiliation for contestants, but there are some exclusions detailed in the Terms and Conditions. Please ensure you are eligible to participate and comply with your affiliated organization’s rules of conduct, ethics, and other restrictions specific to your organization.
Contestants from a wide variety of backgrounds, experiences, and disciplines (not necessarily all captured above) are welcome to participate in the challenge. The Official Representative submitting (individual or team lead, in the case of a team submission) must be a U.S. citizen or permanent resident of the United States or its territories. International contestants can collaborate on a team with a team captain who meets the U.S. requirements. In the case of submissions from a business or other organization, it must be incorporated in and maintain a place of business in the United States or its territories. To register for the challenge, click - SOLVE THIS CHALLENGE
Other Current NIST Funding Opportunities - https://mail.google.com/mail/u/0/#inbox/WhctKJVqzzvjtqkCTtkQhvHvPSCCMZKXSrHpRPFnrrQBnKvQwhCQJRMswjffQzdMLXrpcfL