Challenges for Data Mining in Distributed Sensor Networks

Cantoni, Virginio; Lombardi, Luca; Lombardi, Paolo

doi:10.1109/icpr.2006.359

Cited by 39 publications

(16 citation statements)

References 22 publications

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“…One attempt to provide different data mining models for IoT solutions using either decentralised or centralised approaches was provided by Bin et al (2010). Cantoni et al (2006) analysed the challenges in distributed sensor networks and concluded that pattern recognition, data mining and data fusion are key issues in elaborating reactive decisions. Moreover, they stated that complex pattern recognition and data mining can be effectively performed when relying on a mainly centralised approach in which the computational power is not constrained (Cantoni et al, 2006).…”

Section: Figure 1 Model Of Knowledge Gatheringmentioning

confidence: 99%

Survey of business excellence by knowledge gathering for industrial internet-of-things applications

Tervonen

Hautamäki

Heikkilä

et al. 2018

IJMED

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The Internet-of-Things (IoT) can change not only products but also companies' whole business model. The goal of this article is to inform companies about the creation of business intelligence via utilisation of the industrial IoT. This review article assumes that combining business excellence, service design and knowledge gathering via data engineering into cognitive infocommunication (CogInfoCom) opens new possibilities to develop business ideas. These new possibilities are examined through a literature review on deployments of industrial IoT solutions. The survey responds to two research questions: What methods of knowledge gathering and business excellence are used in industrial IoT-based product, service and process innovations? How can knowledge gathering, business Jouni K. Tervonen et al. excellence and CogInfoCom methods be utilised to create added value in industrial IoT solutions? This survey reveals the richness and delicacy of these exploitation opportunities.

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Section: Figure 1 Model Of Knowledge Gatheringmentioning

confidence: 99%

Survey of business excellence by knowledge gathering for industrial internet-of-things applications

Tervonen

Hautamäki

Heikkilä

et al. 2018

IJMED

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“…In wireless sensor networks, communication is easily the most energy consuming operation. It is reported in that communication is over one thousand times more expensive in terms of energy than performing a trivial aggregation operation. Ni et al .…”

Section: Energy Efficiencymentioning

confidence: 99%

Adding semantics to internet of things

Riekki

Nurminen

et al. 2014

Concurrency and Computation

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SummaryThe development of Internet of Things (IoT) applications can be facilitated by encoding the meaning of the data in the messages sent by IoT nodes, but the constrained resources of these nodes challenge the common Semantic Web solutions for doing this. In this article, we examine enabling technologies for adding semantics to the IoT. Especially, we analyze data formats, which enable IoT applications consume semantic IoT data in a straightforward and general fashion, and evaluate resource usage of different alternatives with a sensor system. Our experiment illustrates encoding and decoding of different data formats and shows how big a difference a data format can make in energy consumption. Copyright © 2014 John Wiley & Sons, Ltd.

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“…Data management in the case of WSNs would involve the task of acquiring data from sensors, storage of the collected data and efficient transmission of data to the end users [7]. It should be energy efficient, scalable and robust to failures as well.…”

Section: Introductionmentioning

confidence: 99%

Framework for a Self-managed Wireless Sensor Cloud for Critical Event Management

Nair

Morrow

Parr

2012

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Wireless sensor networks (WSNs) can be widely used for managing various scenarios existing in social, industrial and numerous environmental management systems. They have been widely used in environmental monitoring and management applications and have also found application in disaster management scenarios. One of the greatest problems faced by the scientific community in organizing data collection through sensor networks in areas of disaster is the disorder and destruction brought about in the communication systems prevailing in such situations. In this paper, a scientific study of the various scenarios that could occur post-disaster and the various housekeeping functions each sensor node would adopt as part of the self management requirement is provided. We also present a sensor task management framework that could be implemented to provide a low energy consuming, reliable network for WSNs deployed for critical infrastructure management.Keywords: self-managed wireless sensor cloud, critical event management. Related WorkWireless sensor networks used for monitoring applications can be prone to various events like nodes dying, topology reconfiguration, loss of connection to the base station etc. Depending on various events that could occur during a WSN deployment, elements that could be said to contribute to the design of a WSN are protocols, data fusion / aggregation techniques, topology management and methods of deployment. Protocols that are used in WSNs can be categorized as network / routing, transport and MAC protocols. There have been several network protocols designed to address the issue of connectivity establishment. According to the authors of [1], LEACH

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Challenges for Data Mining in Distributed Sensor Networks

Cited by 39 publications

References 22 publications

Survey of business excellence by knowledge gathering for industrial internet-of-things applications

Survey of business excellence by knowledge gathering for industrial internet-of-things applications

Adding semantics to internet of things

Framework for a Self-managed Wireless Sensor Cloud for Critical Event Management

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