Smart Communities, Smart Responders (SCSR) – An AI for IoT Prize Competition

Texas A&M University

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

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 (SCSR) – An AI for IoT Prize Competition,” Texas A&M University 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. 

Meet the Team

Texas A&M University (TAMU) Internet 2 Technology Evaluation Center (ITEC), US Ignite, the Texas Engineering Extension Service (TEEX), and Texas A&M Institute for Data Science (TAMIDS) assembled a powerful team with decades of experience in each of their respective areas of expertise to engage in their “Smart Communities, Smart Responders (SCSR) – An AI for IoT” Prize Competition. Texas A&M University, 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.

Texas A&M University’s team is made of eight 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, Texas A&M University 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 Texas A&M University. 
• Jian Tao is an Assistant Professor in the Department of Visualization at the Texas A&M University. He is affiliated with the Texas A&M Institute of Data Science, the Department of Electrical & Computer Engineering, and the Department of Multidisciplinary Engineering Technology at Texas A&M University. 
• 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.
• Joan Quintana, Associate Director, ITEC, is a skilled project manager, communicator, and facilitator with more than 25 years of experience managing research‐based projects with local, state, and federal funding. She will use her broad expertise to effectively manage the proposed project, keeping partners engaged and informed, and overseeing project management, reporting, and communications.
• 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, Smart Cities Big Data Program Manager, US Ignite, works to create a unified framework for open data platforms to facilitate ease in data sharing.
• Palak Agarwal, Data Scientist, US Ignite, works on the smart city data projects and other data initiatives with government agencies and academic institutions.
• Jonathan Beam, Prizes and Challenges Program Manager, US Ignite, provides support to US Ignite’s growing list of smart communities and smart bases.
• Domenick Lasorsa, Prizes and Challenges Program Specialist, US Ignite, supports US Ignite's growing list of smart communities and smart bases with a focus on prizes and challenges.

Project Overview

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

Overall objectives of Texas A&M University’s SCSR – An AI for IoT 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 of participant’s data visualization and IoT technology solutions.

Participants of the SCSR - An AI for IoT Prize Competition will focus on operating and demonstrating the accuracy and scalability of an AI3 system. The competitors’ key deliverable is a functioning system that can demonstrate end‐to‐end functionality, with integrated operations by public safety professionals in a live exercise.

Potential Impacts of the Project

It will be critical that technology be interoperable with existing software and hardware solutions currently leveraged by first responders. The key innovations submitted through Texas A&M University’s SCSR - An AI for IoT Prize Competition will be related to the 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 Texas A&M University’s prize design approach, will establish: 

• Technical standards and best practices of real‐time data integration and visualization,
• Optimal AI/ML models to predict first responder actions across a wide range of scenarios, and
• User experience solutions required for first responders to act on simulation models, sensors, and mission‐driven predictions.