Cultural Heritage on Internet of Things (IoT) systems: Trends and challenges

Piccialli, Francesco; Chianese, Angelo; Jung, Jason J.

doi:10.1002/cpe.4155

Cited by 8 publications

(2 citation statements)

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“…• Small to large scale: Since some of the studies on IoT (Piccialli, Chianese, & Jung, 2017;Rashidi, Cook, Holder, & Schmitter-Edgecombe, 2011) attempted to provide an integrated service, how to combine multiple systems for a particular region has also become a research trend of IoT in recent years. A typical example is the smart home application (Rashidi et al, 2011), which is aimed to gather and integrate data coming from different types of sensors and devices as well as external systems.…”

Section: From Data To Knowledgementioning

confidence: 99%

“…Since the information and communication technology has emerged information demands and analytics requirements, the data integration becomes an important issue in design and development of IoT systems. Especially for industrial applications, the integration process for data analysis is a hot topic in research, a study (Chen, ) illustrates this point and reviews the ideas and practices that facilitate the information integration process with ICT technologies. Small to large scale: Since some of the studies on IoT (Piccialli, Chianese, & Jung, ; Rashidi, Cook, Holder, & Schmitter‐Edgecombe, ) attempted to provide an integrated service, how to combine multiple systems for a particular region has also become a research trend of IoT in recent years. A typical example is the smart home application (Rashidi et al, ), which is aimed to gather and integrate data coming from different types of sensors and devices as well as external systems.…”

Section: Data Mining For Iotmentioning

confidence: 99%

See 1 more Smart Citation

Data analytics for internet of things: A review

Tsai

Chiang

et al. 2018

WIREs Data Min & Knowl

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The internet of things (IoT), which provides a way to connect every “thing” via the internet to further develop a convenient environment, has been around for more than a decade. The trend of the development of IoT nowadays is to focus not only on its devices and systems but also on data analysis. The main reason is that data from sensors or systems typically contain valuable information that is very useful for improving the system performance or providing a better service to the user if we come up with a good “data analysis” solution. This paper begins with a brief review of data mining technologies for IoT. Then, a reference data analytics architecture is given to show how data analysis technologies can be applied to an IoT system. Finally, applications, open issues, and possible research directions are addressed. This article is categorized under: Application Areas > Internet and Web‐Based Applications Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Technologies > Computational Intelligence Technologies > Machine Learning

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Section: From Data To Knowledgementioning

confidence: 99%