IoT Miner: Intelligent Extraction of Event Logs from Sensor Data for Process Mining

• URL: http://arxiv.org/abs/2509.05769v1
• Date: Sat, 06 Sep 2025 16:50:33 GMT
• Title: IoT Miner: Intelligent Extraction of Event Logs from Sensor Data for Process Mining
• Authors: Edyta Brzychczy, Urszula Jessen, Krzysztof Kluza, Sridhar Sriram, Manuel Vargas Nettelnstroth,
• Abstract summary: IoT Miner is a framework for creating high-level event logs from raw industrial sensor data to support process mining.<n>By combining AI with domain-aware data processing, IoT Miner offers a scalable and interpretable method for generating event logs from IoT data.
• Score: 1.118478900782898
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper presents IoT Miner, a novel framework for automatically creating high-level event logs from raw industrial sensor data to support process mining. In many real-world settings, such as mining or manufacturing, standard event logs are unavailable, and sensor data lacks the structure and semantics needed for analysis. IoT Miner addresses this gap using a four-stage pipeline: data preprocessing, unsupervised clustering, large language model (LLM)-based labeling, and event log construction. A key innovation is the use of LLMs to generate meaningful activity labels from cluster statistics, guided by domain-specific prompts. We evaluate the approach on sensor data from a Load-Haul-Dump (LHD) mining machine and introduce a new metric, Similarity-Weighted Accuracy, to assess labeling quality. Results show that richer prompts lead to more accurate and consistent labels. By combining AI with domain-aware data processing, IoT Miner offers a scalable and interpretable method for generating event logs from IoT data, enabling process mining in settings where traditional logs are missing.

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