PSCR publicizes all upcoming prize challenges to its website. Official announcements for all open opportunities are made available on Challenge.gov.
- PSCR Prize Challenge Participant (2018)
The CHARIoT Challenge, hosted by PSCR and its challenge partners, invites innovators to build augmented reality (AR) interfaces or Internet of Things (IoT) data emulators by participating in a multi-phase contest. The Challenge is running two multi-phase contests, simultaneously: Build Augmented Reality Interfaces for First Responder and Emulate Smart City Data for Disaster Scenarios. Learn more.
This four-stage Challenge promotes unmanned aircraft systems (UAS) technology that may someday assist first responders in their search and rescue operations. Competitors will have an opportunity to demo their UAS prototype at a live culmination event in front of industry experts and public safety agencies in April 2021, and to compete for up to $552K in prizes. Learn more.
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 served from a live streaming data processing framework. The framework will leverage an extensive and unique staged dataset designed to stimulate a day in the life of a busy city as viewed through the lens of many parallel, multimodal, unstructured data streams. Learn more.
Launching this summer, PSCR seeks solvers to create image datasets that depict camera capture problems such as grime on the lens or sun flare, that cause issues for computer vision applications. These training datasets will be offered for future image quality research and development to better diagnose and predict camera problems and improve public safety analytics.
Are you a computer vision or no-reference metric researcher? Interested in learning more about the opportunity to contribute to image quality researcher? Contact PSCR at firstname.lastname@example.org to learn how you can get involved in the Computer Vision Challenge and compete to win up to $240,000 in prizes. Learn more.
The 2020 NIST PSCR Differential Privacy Temporal Map Data Challenge follows on the success of 2018 Differential Privacy Synthetic Data Challenge, extending the reach and utility of differential privacy algorithms.
Participants will compete in a sequence of marathon matches to apply differentially private algorithms to datasets that contain time and location data, where one individual in the data may contribute a short sequence of events. The goal is to create a privacy-preserving dashboard map that shows changes across different map segments over time.
Temporal map data is of particular interest to the public safety community in applications such as optimizing response time and personnel placement, natural disaster response, epidemic tracking, demographic data and civic planning. Yet, the ability to track a person's location over a period of time presents particularly serious privacy concerns. See this news article - for an overview of this topic.
The Differential Privacy Temporal Map Challenge will invite solvers to develop algorithms that preserve data utility while guaranteeing individual privacy is protected.
For more information on Differential Privacy, the challenge and its target public safety applications, check out the on-demand session "Crisis Collaborations: Challenges for Safe Data Sharing with Differential Privacy" from PSCR 2020: The Digital Experience.
PSCR is exploring ways to utilize already-deployed mobile technologies to provide a portable, on-the-scene fingerprint capture solution that would save public safety personnel resources and potentially save lives. The path to capable mobile fingerprinting could be made more accessible by addressing gaps in technology that have hindered development. To accomplish this, PSCR is launching the Mobile Fingerprint Capture for First Responders Challenge in Winter/Spring 2021. Winning solutions will focus on innovations across a variety of mobile device operating systems that advance the state of fingerprint capture technologies.