Causing Pain: The traditional edge intelligence computing model doesn’t work for edge Military wearable and IOBT devices. Transmission of large amounts of sensor data over potentially unreliable communications channels puts Battlefield soldiers at risk. Problem Statement: How DOD can manage the military battlefield assets to include integrate signals from a diverse and dynamic set of sensors, including static ground sensors and soldiers worn sensors to provide predictive and operational analytics? SAIC’s Virtual Tactical Assistance provides the DOD the IOT infrastructure to manage military battlefield assets to include integrating signals and communications protocols from a diverse and dynamic set of sensors, including stat ground sensors and soldier worn sensors to provide Distributed compute resources and predictive and operational analytics. Combatant personnel require the ability to use data from many systems and communicate peer to peer without access to significant IT infrastructure. The technology seeks to enhance asset management, supply and maintenance operations, rapid target acquisition, and the sharing of targeting/ballistic solutions. Sensors and other weapon mountable accessories/enablers are designed to capture logistic, targeting, and telemetry data from individual weapon systems and share it across the squad, platoon, and higher echelons via a decentralized network. Confluent/Kafka provides processing of IOBT data streams, such as device and sensor data, which provides insights into asset state by monitoring use, providing indicators, tracking patterns and optimizing asset use for proactive and predictive analytics. More importantly, Confluent kafka provides each TVA to function as a data hub and a peer in a “data mesh”, which can share messages, location updates, and other data with other TVA devices in an ad-hoc manner independent of any wider network.