Predictive Maintenance for LoRa: A Hybrid Telemetry Framework

AID Edge Inc. presents a hybrid telemetry framework for predictive maintenance in LoRa networks, combining rule-based detection methods with machine learning.

The framework uses SNR and RSSI-based features together with models including LSTM and logistic regression, designed to help identify early signs of degradation before they affect network reliability.

This page presents the recovered abstract for this publication. The full paper is available as a PDF: Predictive Maintenance for LoRa — A Hybrid Telemetry Framework.