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Tag - ESP32

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High-Density LED Control with ESP32 RMT and WLED

Driving large WS2812 or SK6812 installations with ESP32 and WLED is not just an MCU performance problem. The real constraints are LEDs per output, RMT interrupt or DMA behavior, 800 kHz serial timing, power injection, Wi-Fi load, and multi-controller sync. This article gives a practical architecture guide.
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Debugging Long-Uptime ESPHome Devices on ESP32

ESPHome devices that fail after days or weeks usually suffer from accumulated system effects: heap pressure, fragmentation, Wi-Fi instability, blocking components, sensor timing, and weak diagnostics. This guide gives a practical ESP32 long-uptime debugging path.
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Building a Multi-I2C Sensor Gateway with ESP32 and ESPHome

A reliable ESP32 and ESPHome multi-I2C sensor gateway is not just about scanning sensor addresses. It needs bus isolation, warm-up windows, deep sleep trade-offs, power design, diagnostic entities, and clear Home Assistant modeling.
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ESP32 Energy Metering with HLW8032, BL0942, and ESPHome

ESP32 energy metering with HLW8032, BL0942, and ESPHome is not just about reading voltage, current, power, and energy. This article explains how to design the UART boundary, sampling cadence, Wi-Fi behavior, calibration, diagnostics, and Home Assistant entities as one stable data path.
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Best ESP32 Firmware Frameworks in 2026: How to Choose Between ESP-IDF, Arduino, ESPHome, and Zephyr

The best ESP32 firmware framework in 2026 depends less on hype and more on product lifetime, driver control, Home Assistant alignment, and platform portability. This article explains when ESP-IDF, Arduino, ESPHome, and Zephyr each make sense.
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ESP32 Firmware Development Guide for IoT Devices

Real ESP32 firmware development is not just about connecting a device to Wi-Fi. It is about structuring BSP, drivers, protocols, config, OTA, logs, and maintenance into a system that can survive production. This guide outlines a more scalable firmware architecture for IoT devices.
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Why Edge AI Fails More Often on Observability Than on Model Accuracy

Edge AI deployments rarely fail first on model accuracy. They fail when teams cannot see input health, inference health, version context, or diagnostic evidence. This article explains why observability should be designed as a core Edge AI capability from ESP32-class devices to Linux edge boxes.
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Edge AI Device OTA: How to Do Staged Rollouts and Rollbacks

The hard part of Edge AI OTA is not pushing a new package. It is designing staged rollout, rollback, and remote recovery for devices whose firmware, model, and configuration evolve together. This article explains how to do it from ESP32 to RK3566.
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