Framework for the identification of rare events via machine learning and IoT networks
Nardelli, Pedro; Papadias, Constantinos; Kalalas, Charalampos; Alves, Hirley; Christou, Ioannis T.; Macaluso, Irene; Marchetti, Nicola; Palacios, Raul; Alonso-Zarate, Jesus (2019-10-21)
P. Nardelli et al., "Framework for the Identification of Rare Events via Machine Learning and IoT Networks," 2019 16th International Symposium on Wireless Communication Systems (ISWCS), Oulu, Finland, 2019, pp. 656-660. doi: 10.1109/ISWCS.2019.8877287
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https://urn.fi/URN:NBN:fi-fe202001071319
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Abstract
This paper introduces an industrial cyber-physical system (CPS) based on the Internet of Things (IoT) that is designed to detect rare events based on machine learning. The framework follows the following three generic steps: (1) Large data acquisition / dissemination: A physical process is monitored by sensors that pre-process the (assumed large) collected data and send the processed information to an intelligent node (e.g., aggregator, central controller); (2) Big data fusion: The intelligent node uses machine learning techniques (e.g., data clustering, neural networks) to convert the received (″big″) data to useful information to guide short-term operational decisions related to the physical process; (3) Big data analytics: The physical process together with the acquisition and fusion steps can be virtualized, building then a cyber-physical process, whose dynamic performance can be analyzed and optimized through visualization (if human intervention is available) or artificial intelligence (if the decisions are automatic) or a combination thereof. Our proposed general framework, which relies on an IoT network, aims at an ultra-reliable detection/prevention of rare events related to a pre-determined industrial physical process (modelled by a particular signal). The framework will be process- independent, however, our demonstrated solution will be designed case-by-case. This paper is an introduction to the solution to be developed by the FIREMAN consortium.
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