The use of Artificial Intelligence in assistive systems is growing in application and efficiency. From self-driving cars, to medical and surgical robots and industrial tasked unsupervised co-robots; the use of AI and robotics to eliminate human error in high-stress environments and perform automated tasks is something that is advancing society’s status quo. Not only has the understanding of co-robotics exploded in the industrial world, but in research as well. The National Science Foundation (NSF) defines co-robots as the following: “...a robot whose main purpose is to work with people or other robots to accomplish a goal” (NSF, 1). The latest iteration of their National Robotics Initiative, NRI-2.0, focuses on efforts of creating co-robots optimized for ‘scalability, customizability, lowering barriers to entry, and societal impact’(NSF, 1). While many avenues have been explored for the implementation of co-robotics to create more efficient processes and sustainable lifestyles, this project’s focus was on societal impact co-robotics in the field of human safety and well-being. Introducing a co-robotics and computer vision AI solution for first responder assistance would help bring awareness and efficiency to public safety. The use of real-time identification techniques would create a greater range of awareness for first responders in high-stress situations. A combination of environmental features collected through sensors (camera and radar) could be used to identify people and objects within certain environments where visual impairments and obstructions are high (eg. burning buildings, smoke-filled rooms, ect.). Information about situational conditions (environmental readings, locations of other occupants, etc.) could be transmitted to first responders in emergency situations, maximizing situational awareness. This would not only aid first responders in the evaluation of emergency situations, but it would provide useful data for the first responder that would help materialize the most effective course of action for said situation.