Challenge

First responders, including firefighters, ER personnel, and police officers, require a comprehensive understanding of the situation when dealing with complex and dynamic events. This detailed situational awareness is crucial for effective decision-making and coordination during emergencies. One of the significant challenges they face is the localization of people, events, and objects within buildings, as traditional GPS technology is typically unavailable or unreliable in indoor environments. As a result, accurately identifying and tracking these critical elements becomes significantly more difficult. To overcome these challenges, commanding officers often rely heavily on voice communications from their team members to gather real-time information

RnD Objectives

In this project, we utilize multimodal generative AI to enhance the localization and tracking of people, events, and objects based on the multiparty voice communications of first responders. This advanced AI technology integrates data from various sources, such as voice inputs from firefighters, ER personnel, and police officers, to create a comprehensive and real-time situational awareness. By analyzing and synthesizing these diverse inputs, our system aims to provide accurate location information and track critical elements within complex environments, thereby improving the efficiency and effectiveness of emergency response operations 

People