SensXR: Accelerating Decision Cycles with Low-SWaP Wearable Edge-AI Sensor Fusion & PPE-Compatible HMI for Multi-Threat Detection

SensXR addresses a critical Department of Defense (DoD) capability gap in warfighter protection from chemical, biological, radiological, and nuclear (CBRN) threats. Most fielded detectors are limited to identifying single threats, forcing operators to carry multiple bulky devices, which increases the size, weight, and power (SWaP) burden, slows decision-making cycles, and reduces situational awareness. These challenges conflict with the DoD’s Human-Machine Interface (HMI) and Trusted AI & Autonomy Critical Technology Areas (CTAs), which emphasize the need for integrated, lightweight sensing systems capable of providing trusted, edge-based intelligence.SensXR proposes a wearable, low-SWaP platform integrating chemical and radiological sensor fusion, TinyML-powered edge inference, and a human-machine interface (HMI) optimized for use with standard PPE (e.g., SCBA and M50 masks). The system provides automated hazard classification with confidence scores, real-time shared data-mapping and alerts over encrypted LoRa mesh, and intuitive AR visual cues via a flip-down display. This design minimizes cognitive load, accelerates perception-to-action cycles, and ensures mission continuity even in contested electromagnetic environments.Phase I demonstrated successive prototypes, evolving from helmet-mounted units with COTS smartglasses to a compact belt-worn module with custom PCBs and an integrated sensor array. Trials at events like CBOA 24 and RDAX 24 validated system feasibility, highlighting improvements in form factor, power efficiency, and network resilience. Field tests confirmed reliable edge inference, high-confidence alerts, and user-preferred HMI features under realistic operational conditions.Phase II will further mature SensXR through structured warfighter workshops and field trials at Ellsworth AFB, incorporating user feedback to refine enclosure ergonomics, validate LoRa mesh communications, and implement federated learning pipelines to adapt inference models against adversarial inputs. The program’s objectives include achieving measurable decision-cycle compression, improving situational awareness, and enhancing the safety and effectiveness of CBRN response operations.With a multidisciplinary team experienced in sensor fusion, embedded AI, radiological science, electronics engineering, and field operations, SensXR is poised to deliver a scalable, mission-ready solution. The effort supports a clear path to commercialization and DoD adoption while offering dual-use potential in non-Defense markets.