A complete workflow for building, training, and deploying a lightweight LSTM Autoencoder anomaly detector for temperature data on the ESP32 microcontroller—without TensorFlow or TFLite. This project uses PyTorch, ONNX, and C++ for efficient, real-time anomaly detection on edge devices.
iot hardware esp32 pytorch lstm lstm-model iot-application anomaly-detection pytorch-implementation lstm-autoencoder anomaly-detector onxx-cpu anomaly-detection-iot
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Updated
Jun 27, 2025 - Python