SW-121688 - USA (Washington, DC) - Dynamic Sensor-Tasking and Routing System - Deadline January 6,2027

(1) Vendor needs to provide dynamic sensor–tasking and routing system to the government authority located in Washington, DC.– Develop an explainable, adaptive machine learning architecture using Super Intelligence (SI) that dynamically schedules, sequences, and gates geophysical sensor modalities based on real–time environmental physics, learned sensor operational envelopes, and predictive target response models.– System will enable autonomous platforms to perform in–stride characterization and clearance of subsurface hazards, including potential devices or components, in high–tempo, contested tactical environments.– Adaptive, machine–learning–driven sensor–tasking and routing decision engine capable of scheduling sensor deployment and routing platform payloads in real time using probabilistic, data–driven optimization methods.– Intelligent edge capability that continuously monitors changing site conditions and dynamically queues, activates, or inhibits physical sensor payloads on an autonomous platform.– Automating this sensor–queuing and routing logic at the edge through explainable and efficient AI, the system will overcome the subsurface bottlenecks of current field suites, eliminate tactical network saturation, minimize time on target, and ensure reliable detection and defeat of subsurface devices.– Standoff aerial and surface visual mapping systems.– Adaptive AI/ML for sequential decision–making and path planning.– Autonomous warehouse robotics, dynamic network routing, and space domain awareness, machine learning is highly mature for solving complex, real–time sensor scheduling and path–planning challenges.