Firmware
Building a production-ready camera system with 45 MB/s sustained throughput Direct Memory Access (DMA) promises zero-CPU data transfers, but poor buffer design can turn that promise into corrupted frames, system crashes, and unpredictable behavior. This post shares hard-won lessons from building Hoomanely's camera module—a dual-sensor system
Software
Cross-platform apps move fast—until native features start leaking into product code. BLE streaming, notifications, file access, analytics: all must behave consistently across iOS and Android without tangling UI logic with platform quirks or slowing tests to a crawl. Our current setup uses direct native bridges from a view-model into
Hardware
At Hoomanely, USB isn’t just a connector—it’s a critical part of the power architecture. Almost every product we build uses USB for one or more purposes: * Powering the device * Configuring firmware * Transferring logs or data But USB is more than a port. It defines an electrical relationship
Firmware
During prototyping of our hardware products - Hoomanely EverBowl and EverHub - we leveraged the Raspberry Pi Compute Module 4 (CM4) as the embedded compute platform for early-stage development. The CM4 served as our prototyping vehicle before transitioning to Hoomanely's custom purpose-built System on Module (SOM) for production.
Firmware
Storage wear & tear — practical engineering guide from Ever-bowl’s memory pipeline This post explains how the Ever-bowl platform uses PSRAM as a buffer and a flash-aware firmware stack to extend flash lifetime. It includes concrete implementation pitfalls and solutions, datasheet-backed guidance, and a practical checklist for engineers building similar
Firmware
Introduction Have you ever wondered how your pet's GPS tracker knows whether they're running, resting, or digging in the backyard? Or why sometimes the tracker seems to lose accuracy after a few weeks of use? The secret lies in a sophisticated component called an Inertial Measurement
Firmware
The Problem That Started Everything At Hoomanely, we set out to build connected pet products that could genuinely understand pet behavior and health through multiple sensors working together. Trackers needed to monitor activity, detect vocalizations, track location, and communicate over long distances. Smart bowls needed to measure food consumption with
Hardware
When you're holding a PCB prototype, it's easy to focus on the exciting parts—the microcontroller, the sensors, the wireless module. But here's what I've learned at Hoomanely: the humble connector is often the difference between a product that lasts 5 years
AI
Intro Devices in the field continuously send motion, temperature, and power data. In connected pet‑tech products like those at Hoomanely, spotting unusual patterns right on the device can prevent bigger issues - like a dog’s collar overheating or a tracker battery draining too quickly. Local anomaly detection lets
Tech, Insights and ideas.
A step-by-step guide to seamless deep linking on iOS and Android Introduction Have you ever clicked a link in an email, ad, or WhatsApp message that opened an app directly on a specific screen — like a post, quiz, or checkout page? That seamless experience is powered by deep linking. Universal
I've seen this story play out across the industry more times than I can count. A team builds a working prototype — everything looks perfect in demos, investors love it, morale is high, and excitement pushes everyone toward production. Then certification testing happens. Most prototypes fail on day one
How AI models are shrinking without losing their minds. Many of our real-time models - from detecting dog motion to analyzing eating patterns - run directly on embedded systems. At Hoomanely, we combine lightweight CNNs (like MobileNet) with quantization and pruning to achieve low-latency inference without sacrificing reliability. The ability
In digital platforms where content relevance drives engagement, location-based geofencing plays a key role in connecting users with contextually meaningful information. It helps ensure that users see posts that are local, timely, and personally relevant—whether it is a nearby dog park meet-up, a local pet store promotion, or a
When I first powered up our multi-radio tracker prototype—equipped with Wi-Fi, Bluetooth, LoRa, and GPS—I watched the battery plunge from full to flat in under 6 hours. That painful moment sparked a six-month deep dive into embedded power optimisation. What follows is not theory—it's a
A Guide to CAN Controllers, Transceivers, and Bus Configuration Introduction When our team at Hoomanely began developing iot devices for building a pet environment platform, we faced a critical challenge: transmitting high-resolution sensor data between multiple ECUs with microsecond-level timing precision were We needed CAN FD. But here's
Last year at Hoomanely Inc., we were developing an IoT sensor that needed to communicate across our campus. On paper, LoRa promised 10km range. Our prototype? Barely reached the parking lot. The antenna looked fine. The code was solid. The radio chip was premium quality. So what went wrong? Turns
When Disconnects Become the Norm Bluetooth Low Energy links don't fail in the lab—they fail in the real world. Phones roam between rooms, radios get noisy, apps are backgrounded, and peripherals reboot at the worst possible moment. After shipping connected devices at scale, I've learned
Introduction We’re building technology that helps us understand pets better - not just through visuals, but through sound. Dogs communicate through subtle cues: the rhythm of a chew, a quiet gulp, or a bark that changes tone when they’re anxious. At Hoomanely, our smart bowls and monitoring systems
Building Secure, Scalable Sign-In with Google & Apple for Apps Introduction Every great app starts with a simple promise: “Log in, and your world syncs instantly.” Behind that seamless experience is a complex system of user authentication, token management, and identity federation. With AWS Cognito + Amplify gives you a powerful,
Automate Flutter deployments with Fastlane: reduce release time 70%, eliminate version errors, and achieve reproducible releases across your team.
Introduction In specialized fields, smarter systems are the goal. While scaling large language models (LLMs) is popular, real improvements often come from optimizing the backend. Retrieval-Augmented Generation (RAG) pipelines, particularly chunking, are crucial for performance. At Hoomanely, we faced issues with irrelevant responses due to poor chunking. Instead of using
