| Abstract |
The rollout of 5G infrastructure, the proliferation of devices in the Internet of Things, and the integration of innovative technologies into buildings, transportation, and public safety systems have brought many benefits to communities throughout the country. However, this has also created a large amount of data, making it difficult for public safety leaders and first responders to use it. To address one aspect of this issue, the Smart Communities, Smart Responders: An Artificial Intelligence for Internet of Things Prize Competition was established. The main goal of this initiative is to accelerate the development of real-time data analysis and visualization, facilitated by the integration of sensors, allowing access to a variety of IoT data streams in user-friendly formats. This will give first responders the ability to tackle complex problems by combining and integrating sensor data, thus improving situational analysis and response times. Texas A&M University, Texas A&M Engineering Extension Service, and US-Ignite invited the public to participate in the competition, which is funded by the National Institute of Standards and Technology Public Safety Communications Research Division. Contestants are challenged to ingest unfamiliar data, assess them based on metadata or contextual cues using machine learning methods, and classify them for use on a situational awareness platform. The competition was organized in three phases over the course of 12 months. The selected contestants from the previous phases were given the opportunity to develop their solutions, preparing and participating in a live testing event hosted at Disaster City® managed by Texas A&M Engineering Extension Service. © 2024 IEEE. |
