AI-Powered SkyCam Estimates Air Quality
A new system, developed by an unknown creator named 'lucascreator', uses computer vision and AI to estimate air quality. The device relies on an Unihiker K10 microcontroller module featuring the ESP32-S3 chip and a lightweight convolutional neural network (CNN) trained on 12,000 sky images.
The system works by capturing sky images with a camera connected to the ESP32. These images are then analysed by the CNN model, which predicts the Air Quality Index (AQI) based on visual patterns. This method has shown remarkable accuracy in some cases, serving as an additional data point to traditional measurement methods.
However, it's important to note that while this approach may have some value, it's not a replacement for proper air quality measurement devices. The compact model may not always provide supreme accuracy, and implementing video data processing on an ESP32 has its limitations.
The 'lucascreator' system offers an innovative approach to air quality estimation using computer vision and AI. Despite its potential, it's crucial to understand its limitations and use it as a supplementary tool. Further research and development are needed to enhance its accuracy and practicality.
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