tensorflow-lite-micro-model-deployment

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adityakr-010 / TinyRUL-EdgeAI

Edge AI battery prognostics on ESP32 using TinyML, FreeRTOS, TensorFlow Lite Micro, and CNN-based Remaining Useful Life prediction.

machine-learning esp32 cnn pytorch freertos iot-application edge-computing battery-management-system predictive-maintenance tensorflow-lite battery-health embedded-ai edge-ai tensorflow-lite-micro battery-lifespan tensorflow-lite-micro-model-deployment

Updated Jun 1, 2026
C

SiliconWit / edge-ai-tinyml

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Not every application can tolerate the latency, bandwidth cost, or privacy exposure of cloud round-trips for every inference. Edge AI puts intelligence directly on the microcontroller.

tinyml-machine-learning-microcontrollers edge-impulse-data-collection-training tensorflow-lite-micro-model-deployment model-quantization-optimization-mcu keyword-spotting-voice-wake-word accelerometer-gesture-recognition anomaly-detection-predictive-maintenance camera-image-classification-esp32 edge-cloud-hybrid-architecture

Updated Jun 4, 2026
MDX

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