The journey to collaborative AI at the tactical edge (CATE)

Susan Toth; William Hughes

doi:10.1117/12.2586096

12 April 2021 The journey to collaborative AI at the tactical edge (CATE)

Susan Toth, William Hughes

Proceedings Volume 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III; 117460O (2021) https://doi.org/10.1117/12.2586096
Event: SPIE Defense + Commercial Sensing, 2021, Online Only

Abstract

Warfighters at the tactical edge do not have “Big Compute” capability and are bandwidth constrained. This significantly affects capability, workload and utility of Intelligence, Surveillance and Reconnaissance (ISR) at the edge. Artificial Intelligence (AI) has the potential to improve quality of information and reduce workload if we optimize AI/ML (Machine Learning) techniques for the constrained tactical environment. For several years, we focused on sensor and data interoperability. Leveraging contested urban environment experiments, and our work with Canada, we cracked the “data interoperability nut” across the systems provided by Canada, the United Kingdom, Australia, and New Zealand. The increased data interoperability made it clear that the link between sensor interoperability and data reasoning is a missing component of ISR at the edge. Data overload for the tactical operators was almost immediate and overwhelming. The success in interoperability highlighted failures in data fusion, filtering, and presentation. Increased data flow does not equal increased situational awareness. CATE is a collaborative effort to develop a prototype AI/ML architecture and framework that enables simple, rapid integration of collaborative, multi-agent AI technology into the Processing, Exploitation and Dissemination (PED) chain at the edge, sensor, and tactical PED level. CATE imagines a soldier on patrol in a “smart city”. In the background, collaborative AI agents scan city cameras, review patterns of life, providing an AI enabled over watch. The AI agents determine there is a threat and alert the soldier, who never had to look down at a screen and take his eyes off his immediate surroundings.

Conference Presentation

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Susan Toth and William Hughes "The journey to collaborative AI at the tactical edge (CATE)", Proc. SPIE 11746, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III, 117460O (12 April 2021); https://doi.org/10.1117/12.2586096

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