The 3.7 kB Alarm: A Zero-Bloat Edge AI Smoke Detector in Pure C You are building a critical IoT safety device — a smart smoke and fire detector. It monitors 12 environmental variables in parallel: temperature, humidity, TVOC, eCO2, raw hydrogen, ethanol, barometric pressure, and five particulate matter metrics. You want a neural network to catch the non-linear chemical signatures of an imminent fire before the flames start. Then you look at the industry standard for Edge AI. TensorFlow Lite for Microcontrollers demands megabytes of Flash, custom memory allocators, a dynamic runtime, and a dependency chain long enough to make you reconsider the whole project. On a cheap, ultra-low-power microcontroller — an ESP32, an ATtiny — those frameworks eat the silicon and leave nothing for the WiFi stack or peripheral control. The hardware isn't the problem. 1. The Data No synthetic data here.…