The Sensor Data Mesh: Building an Open, AI-Ready Architecture for Modern ISR Platforms

Modern defense and security operations rely on rapidly expanding networks of distributed sensors operating across air, land, maritime, cyber, and space domains. These sensors generate vast volumes of heterogeneous data—including EO/IR imagery, radar tracks, and RF detections—often transmitted across bandwidth-constrained, unreliable, or contested communications networks. In many current architectures, sensor data must pass through centralized processing systems before it can be analyzed or shared, creating bottlenecks that delay decision-making and limit the operational value of the data collected. To address these challenges and remain competitive with emerging defense technology platforms, TACTIQL must evolve FULCRUM toward a Sensor Data Mesh architecture. A Sensor Data Mesh distributes processing, storage, and data synchronization across multiple nodes spanning tactical edge devices, operational hubs, and enterprise or cloud environments. Rather than relying on centralized systems, each node in the mesh can ingest sensor feeds, normalize and condition the data, store it locally, and synchronize it with other nodes when connectivity is available. This offline-first design reflects operational realities in which networks are contested, bandwidth is limited, and operators must still process and share critical information at the edge. Within the mesh, FULCRUM serves as the core processing and interoperability engine. It normalizes diverse sensor modalities—including EO/IR, radar, and RF—and translates them into interoperable operational message formats, enabling data generated anywhere in the mesh to be shared across systems, platforms, and organizations. Each instance acts as both a processing node and collaboration point, locally fusing sensor data while synchronizing insights across nodes when communications permit. Developing this capability is critical to delivering value. A Sensor Data Mesh overcomes fragmented systems, constrained networks, and rigid pipelines through resilient, distributed intelligence processing. For military operators, it delivers faster situational awareness, improved coalition collaboration, and AI-enabled analytics closer to the edge.

Faculty Supervisor:

Mehrdad Sabetzadeh

Student:

Partner:

TACTIQL Inc.

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Ottawa

Program: