Firmware
When you're building a sensor module that must capture high-resolution images, store them reliably across power cycles, and ship them over a constrained CAN FD bus — all at the same time — you run into a fundamental problem. No single memory tier does all three jobs well. External PSRAM
From Raw Bayer to JPEG on STM32H5 in ~200ms When a Camera Sensor Captures an Image When a camera sensor captures an image, it does not directly produce a photograph. Instead, it generates a grid of raw intensity values arranged behind a color filter mosaic. On a desktop system, converting
Product
Introduction Time-of-Flight (ToF) sensors promise simple, accurate distance measurement—drop them into a design, read distance, and trigger behavior. But in real products, especially enclosed ones, proximity sensing quickly becomes a mechanical + optical system problem, not just an electrical one. While working with the VL53L1X ToF sensor at Hoomanely, what
Hardware
Bring-up is where hardware stops being theoretical. You power the board for the first time, and suddenly everything that looked clean in schematics becomes a question: * Is this rail actually up? * Is it stable or just momentarily present? * Did the regulator enable correctly? * Is the downstream load pulling it down?
Hardware
Most embedded systems are designed around what should be present. Sensors, modules, peripherals — all assumed to be connected, powered, and behaving correctly. But real systems don’t live in ideal conditions. * A connector may not be fully seated * A sensor board may be missing in a modular setup * A cable
Hardware
High-speed signals do not fail loudly. They fail quietly. A system boots, data starts flowing, and everything appears normal — until you begin seeing intermittent frame drops, occasional communication retries, unexplained latency, or sensors behaving inconsistently under load. The root cause is often not firmware. It is the path those signals
AI
Machine learning systems increasingly rely on data generated by devices operating in the real world - cameras capturing environments, sensors streaming telemetry, microphones collecting audio, and applications logging user interactions. These signals provide invaluable training data because they reflect the true conditions under which models must perform. However, the moment
Hardware
Debug access is one of the most useful parts of a board during development. It is how firmware gets flashed, how logs are captured, how dead boards get recovered, and how engineers figure out what the system is actually doing. But in a real product, debug access is never just
Hardware
In embedded sensor systems, the difference between a stable product and a fragile one often comes down to something that users never see: The order in which sensors wake up. It may sound like a small detail. But in multi-sensor platforms — where image sensors, proximity sensors, microcontrollers, and communication interfaces
Software
Retrieval-Augmented Generation has become the default architecture for practical AI systems because it separates reasoning from knowledge freshness. Models no longer need to contain every fact at training time; instead, they can retrieve relevant information from search indices, document stores, internal knowledge bases, and user-generated corpora at runtime. That architectural