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Smart Communities, Smart Responders: An AI for IoT (AI3) Prize Competition

Texas A&M University logo

Texas A&M University

In February 2022, Texas A&M University (TAMU) was awarded nearly $1,200,000 for the Public Safety Innovation Accelerator Program: An Artificial Intelligence for Internet of Things Prize Competition (PSIAP - AI3).

TAMU Internet 2 Technology Evaluation Center (ITEC), the Texas Engineering Extension Service (TEEX), the Texas A&M Institute for Data Science (TAMIDS), and US Ignite joined together to form a powerful team, each bringing decades of experience in their respective areas of expertise to leverage for the “Smart Communities, Smart Responders: An AI for IoT (AI3)” Prize Competition. TAMU, TEEX, and US Ignite have worked across the globe with over 150 partner cities, companies, universities, and nonprofits to create next‐generation applications that provide transformative public benefit. The rapid deployment of 5G infrastructure, Internet-of-Things (IoT) devices, smart buildings, transportation, and public safety data streams benefit communities across the country. However, these technologies created a flood of data, making it difficult for public safety leaders and individual first responders to make use of this data. These building and city data streams are difficult to segment, process, integrate, and act on, particularly for real‐time data analysis. Through their “Smart Communities, Smart Responders: An AI for IoT (AI3) Prize Competition,” Team TAMU seeks to accelerate the development of real‐time data visualization and rapid integration of IoT sensors for first responders, giving these stakeholders access to various streams of IoT data delivered in usable formats that can help solve complex challenges, thus improving America’s public safety capability.

Total of $360,000 in cash prizes!

Challenge participants will create an artificial intelligence (AI) system to help first responders—like firefighters, police, and EMTs—leverage data from IoT devices, smart buildings, and other surrounding sources. Review the challenge rules document and the informational webinar on the challenge website linked below.

Meet the team

Team TAMU is made of nine key personnel with diverse backgrounds including competition design, networking, data science, public safety communications, and emergency response to design and execute the challenge.

  • Walt Magnussen, Director of Communications, TAMU Internet2 Technology Evaluation Center (ITEC), has been in the communications industry for 45 years. As an expert in communications, he directed the data network, voice network, cellular network, and land mobile radio network at TAMU.
  • Michael Fox, Senior Associate Director, ITEC, is an accomplished technical executive with 30+ years of experience directing the design, development, and management of pre‐ and post‐sales customer‐facing functions, and designing, deploying, and supporting some of the largest networks in the country.
  • Jian Tao is an Assistant Professor from the Section of Visual Computing & Computational Media in the School of Performance, Visualization & Fine Arts at TAMU. He is also the Director of the Digital Twin Lab and the Assistant Director for Project Development at TAMIDS. His research interests include digital twin, numerical modeling, machine learning, data analytics, distributed computing, visualization, and workflow management.
  • Anjuli “A.J.” Renold, Associate Director, ITEC, is an accomplished and skilled project manager, communicator, and facilitator with more than 15 years of experience as a director charged with the development, implementation, management and evaluation of data driven methodologies to solve complex humanitarian issues. Ms. Renold’s experience and expertise lies in the implementation of new technology, policy development, change management and the dissemination of innovation through government and private sector entities for national organizations.
  • Nick Maynard, CEO and Co-founder, US Ignite, is responsible for designing and executing US Ignite’s two Department of Defense smart base test beds on city resiliency and autonomous vehicles.
  • Praveen Ashok, Senior Technical Program Manager, US Ignite, works to create a unified framework for open data platforms to facilitate ease in data sharing.
  • Jonathan Beam, Community Innovation Manager, US Ignite, provides support to US Ignite’s growing list of smart communities and smart bases.
  • Lizzette Arias, Communications Manager, US Ignite, helps US Ignite program teams develop and carry out external communication plans.
  • Mojdeh Mahdavi, Program Manager, US Ignite, supports identification, design, and implementation of digital and data-driven solutions to improve the safety and quality of life for communities.

Project overview

To obtain enough IoT data to drive an AI learning system in the right format with appropriate privacy policies and permissions, team TAMU will collect IoT data from real-world, real-time sensors for practical use with an AI engine. Specifically, TAMU ITEC will work with TEEX to place sensors at key locations in Disaster City, Texas’ world‐renowned urban search and rescue training campus that hosts training for more than 20,000 first responders annually. Sensors installed on props and stations across the training facility will provide a data set that is true to real world situations. Additionally, team TAMU will conduct an exercise at TEEX to inform ITEC’s design and deployment of an IoT architecture to collect the sensor data.

Rocks labeled "Disaster City" in front of a staged train wreck.

Overall objectives of the AI3 Prize Competition include:

  • Plan, design, and disseminate a targeted challenge marketing and participant outreach campaign to ensure adequate challenge participation.
  • Partner with a community to understand their experiences and simulate an environment based on their suggestion.
  • Procure a facility for the planning and execution of a final, live event showcasing participant’s data visualization and IoT technology solutions.

Participants of the AI3 Prize Competition will focus on operating and demonstrating the accuracy and scalability of an AI system to enhance a first responder’s situational awareness. The competitors’ key deliverable is a functioning system that can recognize existing sensor data elements and incorporating previously unknown data elements based on contextual analysis. The aggregated output data will be utilized to improve individual situational awareness for first responders as a communal resource capable of supporting multiple user interfaces and user experiences.

Potential impacts of the project

It is critical that technology be interoperable with existing software and hardware solutions currently leveraged by first responders. The key innovations submitted through TAMU’s AI3 Prize Competition will be related to new data science models leveraging available sensors to support real‐time data visualization. The output of these models needs to be distilled and delivered so first responders can quickly act on the information in the future. The key impacts envisioned in TAMU’s prize design approach will establish: 

  1. Technical standards and best practices of real‐time data integration and visualization,
  2. Optimize AI/machine learning models to predict first responder actions across a wide range of scenarios, and
  3. User experience solutions required for first responders to act on simulation models, sensors, and mission‐driven predictions.
Created March 15, 2022, Updated July 25, 2023