About |
Maintenance is a critical issue in the industrial context for the prevention of high costs or injuries. Various industries are moving more and more toward digitalization and collecting “big data” to enable or improve the accuracy of their prediction. At the same time, the emerging technologies of Industry 4.0 empowered data production and exchange which lead to new concepts and methodologies exploitation of large datasets for maintenance. The intensive research effort in data-driven Predictive Maintenance (PdM) has been producing encouraging outcomes. Therefore, the main objective of this workshop is to raise awareness of research trends and promote interdisciplinary discussion in this field. Data-driven predictive maintenance deals with big streaming data that include concept drift due to both changing external conditions, but also normal wear of the equipment. It requires combining multiple data sources, and the resulting datasets are often highly imbalanced. The knowledge about the systems is detailed but in many scenarios, there is a large diversity in both model configurations, as well as their usage, additionally complicated by low data quality and high uncertainty in the labels. In particular, many recent advancements in supervised and unsupervised machine learning, representation learning, anomaly detection, visual analytics and similar areas can be showcased in this domain. Therefore the overlap in research between machine learning and predictive maintenance continues to increase in recent years. Maintenance is a crucial topic for industrial machines, medical equipment, energy systems, passengers transport vehicles and home appliances among others. Cost reduction, machine reliability, operation, safety and time reduction have been the main concerns of companies and organizations. Meanwhile, Industry 4.0 brought new opportunities of meaningful data collection and storage. Promising data-driven methodologies shrive for predictive maintenance becoming a strong alternative. |
Call for Papers |
Topics of interest for the workshop include, but are not limited to:
Real world applications such as:
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Summary |
IOTStreams 2020 : ECML/PKDD 2020 Workshop on IoT Stream for Data Driven Predictive Maintenance will take place in Ghent, Belgium. It’s a 1 day event starting on Sep 14, 2020 (Monday) and will be winded up on Sep 14, 2020 (Monday). IOTStreams 2020 falls under the following areas: MACHINE LEARNING, DATA, PREDICTIVE MAINTENANCE, INTERNET OF THINGS, etc. Submissions for this Workshop can be made by Jun 09, 2020. Authors can expect the result of submission by Jul 20, 2020. Upon acceptance, authors should submit the final version of the manuscript on or before Jul 27, 2020 to the official website of the Workshop. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the IOTStreams 2020
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Credits and Sources |
[1] IOTStreams 2020 : ECML/PKDD 2020 Workshop on IoT Stream for Data Driven Predictive Maintenance |