AI + IoT Engineering Insights
Practical guidance for teams building connected products: from embedded firmware and edge gateways to IoT platforms, industrial integration, and applied AI.
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New technical comparisons, implementation notes, and field-oriented engineering guidance.
Connecting an Existing MCU Product to Tuya: DP, UART, Prototype, and OTA Gates
A device that used to work with local buttons now appears in an app after a connectivity module is added. That is progress, not acceptance.
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How to Benchmark an Edge LLM: TTFT, TPOT, Memory, Thermals, and Power
An edge LLM benchmark needs separate TTFT, TPOT, memory, thermal, and whole-system power results under a fixed model and workload.
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How to Select Edge Hardware for LLM Inference: Memory, Bandwidth, Accelerators, and Power
A supplier's “8 GB RAM, 6 TOPS NPU” line does not establish that a field device can answer questions about a long service manual offline.
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ESP32-P4 vs ESP32-S3: Choosing for Displays, Cameras, and Wireless Products
Use display and camera interfaces, RAW/ISP or H.264 needs, wireless architecture, and matched-workload tests to decide which ESP32 platform to prototype first.
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What Edge AI Models Can ESP32-P4 Run? From ESP-DL Support to Real-Time Vision Validation
An ESP-DL model listing may say “ESP32-P4 supported,” but that does not answer the question a camera product has to answer.
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ESP32 PCB or External Antenna in a Metal Enclosure: What to Check Before Selecting the Module
An ESP32 prototype connects reliably on an open bench but drops its Wi-Fi link once the metal cabinet door closes.
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From ESP32-P4 Function EV Board to a Custom PCB: What Must Be Revalidated
A screen, camera and network demo may all work on the ESP32-P4 Function EV Board. That is useful evidence for the particular board.
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ESP32-S3 WROOM vs MINI: Choose PSRAM, Footprint, and Antenna for Your Product
An ESP32-S3 development board running a display, voice, or camera demo does not establish which module belongs on the product PCB.
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Choosing an Edge LLM Runtime: Start with Devices and Model Artifacts
Compare llama.cpp, RKLLM, ExecuTorch, and MLC LLM by target device, model artifact, acceleration backend, and release responsibility—not an unverified speed ranking.
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