Introduction Modern IoT and edge AI applications demand embedded systems that can process vast amounts of sensor data in real-time while maintaining reliability and power efficiency. Whether you're building smart home devices, industrial monitoring systems, or precision health monitoring platforms, the foundation lies in sophisticated memory management and
Hardware
1. Reframing the Topic: Charging Is Not Plumbing Charging circuits are often treated as settled territory. Choose a controller, follow the reference schematic, confirm thermal margins, and move on. In many organisations, charging is considered infrastructure—important, but fundamentally understood, and rarely revisited once it appears to work. That assumption
AI
Building high-quality audio datasets is a uniquely painful challenge. Unlike images, where you can glance at a grid of thumbnails and instantly spot a "bad" sample, audio requires time. You have to listen. Linear time is the enemy; you cannot "fast forward" through a dataset validation
Firmware
The Challenge: Edge AI Demands Unprecedented Data Throughput In the world of IoT and edge AI, sensor fusion systems generate massive amounts of data that must be processed, stored, and transmitted in real-time. Our challenge was clear: build an embedded storage pipeline capable of handling continuous multi-sensor data streams—thermal
Hardware
Why USB, PCIe, and the Decision to Punt Are Product-Level Choices, Not PCB Details 1. Introduction: Reframing the Topic High-speed interface routing on platforms like the Compute Module 4 is often framed as a technical hurdle to be cleared late in design—something to be validated, tuned, and signed off
AI
"We need at least a million labeled images to train this model." If you've ever heard this from a data scientist and felt your heart sink, you're not alone. The reality of building production ML systems is that you rarely have the luxury of
Hardware
Introduction: The Surface Is the Product In consumer hardware, surfaces are often treated as cosmetic decisions—colour, gloss, texture. In reality, surface engineering is one of the most critical determinants of product longevity, safety, and trust. For products that live in close proximity to pets, surfaces are not passive shells;
Firmware
Modern edge AI systems face an increasingly complex challenge: how to efficiently transmit massive amounts of high-resolution sensor data in real-time while operating under severe resource constraints. When your embedded system captures 500KB+ images every few seconds and needs to transmit them over limited bandwidth connections, traditional approaches quickly hit
Firmware
In embedded systems, we often celebrate the idea of doing more with less. Smaller MCUs, tighter power budgets, fewer components efficiency as a virtue. But once you start building real device fleets at the edge, that philosophy quickly meets its limits. At Hoomanely, our devices don’t just sample a
AI
The best engineering solutions aren't always the most complex ones. Sometimes, the smartest approach is knowing when to keep it simple—and when to add just enough redundancy to make it bulletproof. At Hoomanely, we build preventive pet healthcare technology that helps pet parents stay ahead of health