We present ECO, the first system enabling efficient multimodal AI deployment on commercial Neural Processing Units (NPUs) through context-aware sensor and compute optimizations. ECO introduces runtime-tunable, NPU-architecture-aware knobs—approximate interpolation, quantization, and model scaling—that adapt to system conditions such as energy availability and sensor reliability. Deployed on an Intel Core Ultra Series 2 NPU with RGB and LiDAR inputs for a semantic segmentation application, ECO achieves up to 4.9× performance and 11.3× energy-efficiency improvement over CPU. Compared to systems lacking runtime context adaptability, ECO preserves higher segmentation quality (48.1 mean IoU in %, referred to as IoU hereafter) vs. 37.9 IoU under energy constraints and restores accuracy from 30.6 IoU to 40.0 IoU in sensor failure scenarios. The demo video and the ECO codebase are available at https://github.com/arghadippurdue/ECO%5FDemo.

This article introduces SecuPilot, a Security Coprocessor-integrated platform designed to enhance the resilience and operational security of autonomous Unmanned Aerial Vehicles (UAVs) in increasingly adversarial environments. Recognizing the critical role UAVs play in diverse applications, SecuPilot builds upon established architectures by incorporating a dedicated security module that performs a series of comprehensive preflight checks to establish a robust root of trust. Once airborne, the platform continuously monitors the UAV’s operational state during runtime to infer and maintain its security, ensuring that any anomalies are promptly identified and addressed without disrupting mission-critical functions. We develop a custom Hardware-in-the-Loop (HITL) simulation framework replicating realistic operational scenarios and adversarial conditions to validate the system’s performance and effectiveness. This rigorous evaluation demonstrates that SecuPilot can successfully mitigate potential threats while preserving the essential performance characteristics of the UAV. The results underscore the viability of a scalable, hardware-centric approach to UAV security, paving the way for safer autonomous systems capable of operating in complex, threat-prone environments.