Every year, we celebrate World Space Week in October to honor scientists' contributions to space research and inspire the next generation of innovators. Honeywell has been a part of every NASA human space mission since the late 1950s, when our flight-control systems were installed on the X-15 Rocket Plane (shown above in a photo of Neil Armstrong after a research flight in November 1959).

The MAGIC1A is a rugged 3U VPX SWaP-C3 high-performance embedded computer combining an Intel Xeon E3-1505M v6 CPU and NVIDIA Quadro P2000 GPU, offering strong compute performance, broad I/O, rugged resilience, and flexible software support. • Xeon E3-1505M v6 quad-core CPU + Quadro P2000 GPU → ~2.3 TFLOPS • Ethernet, USB, serial, MIL-STD-1553, ARINC 429, DisplayPort/DVI, GPIO; up to 8 TB removable SSD with fast-purge • MIL-STD rated, baseplate or fan cooling; −40 °C to +65 °C range • Supports Linux/Windows/VxWorks & CUDA/OpenCL/DirectX/OpenGL; includes AXIS software toolkit

ELECTROMECHANICAL RELAYS FROM 2 TO 10 AMPS.

- Reduced weight and manufacturing cost by more than 30% compared to conventional metallic propellant tanks - Designed and qualified to according KARI requirements - Proof & burst pressure application - Cyclic pressure(MEOP, Max. Enveloped Operating Pressure) application, more than 40 cycles

The COX640AV embodies COX’s cutting-edge cooled MWIR imaging technology, delivering unparalleled performance for the most demanding applications. Its 640x512 resolution and 15μm pixel pitch InSb sensor achieve thermal sensitivity of less than 20mK, ensuring crystal-clear imaging for precise analysis. Capable of operating across a wide temperature range, the COX640AV supports multiple imaging modes and advanced processing functions including AGC, NUC, and customizable color palettes. This ensures adaptability to a variety of mission-critical environments such as defense, aerospace, scientific research, and industrial inspection. In addition to superior imaging quality, the COX640AV is designed for reliability and operational readiness. With rapid image stabilization after startup and robust construction, it performs consistently in harsh environments where stability is non-negotiable. Its combination of cooled MWIR precision, advanced processing features, and rugged design positions the COX640AV as a trusted solution for customers who require accuracy, speed, and durability. By integrating COX’s proprietary calibration expertise, it not only provides outstanding real-time imaging but also guarantees long-term reliability and service continuity.

DA 22-BLDC Brushless Actuator To guarantee maximum safety and reliability, its brushless motor and contactless, wear-free position sensing system makes the DA 22 BLDC immune to wear, vibrations and shock loads. It has especially been designed for usage in harsh environments and for safety-critical applications that require an actuator with high endurance. The conductive aluminum case and the shielded connection cable are reducing the susceptibility to any kind to EMI/RFI noise to the absolute minimum.

A cost-effective and reliable EO/IR solution designed for unmanned platforms, combining compact design with strong performance. The system integrates QVGA/VGA-class infrared sensors and 2–20 megapixel EO cameras, providing versatile options to meet different operational requirements. o Infrared (IR) Sensor: QVGA/VGA resolution, optimized for detection and recognition in short-to-mid range surveillance o Electro-Optical (EO) Module: 2MP–20MP visible light cameras with high-resolution imaging, adaptable to multiple mission profiles o Design Philosophy: Lightweight, compact, and robust for integration into unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), and ground robotics o Key Value: Balances price competitiveness, system reliability, and modular scalability for mass deployment

We developed and optimized an object detection and tracking solution tailored for edge environments using Intel Atom platforms with OpenVINO. The system combines MobileNetV3-SSDLite for detection and MobileNetV3-Small for tracking, enabling efficient real-time performance on resource-constrained devices. Through model optimization and inference acceleration, we achieved over 2x improvement in FPS and more than 50% enhancement in inference speed, all while maintaining detection and tracking accuracy. This demonstrates the solution’s suitability for lightweight, low-power edge AI applications