Internet of things and data mining: An application oriented survey

Sunhare, Priyank; Chowdhary, Rameez Raja; Chattopadhyay, Manju K.

doi:10.1016/j.jksuci.2020.07.002

Cited by 71 publications

(39 citation statements)

References 130 publications

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“…The conversion of data into practical knowledge is considered a part of the technology itself. Its intelligent environment is required for the efficient operation and management of resources and services (Sunhare et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Data mining as a cognitive tool: Capabilities and limits

Polyakov

Khanin

Shevchenko

et al. 2021

Knowledge and Performance Management

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Due to the large volumes of empirical digitized data, a critical challenge is to identify their hidden and unobvious patterns, enabling to gain new knowledge. To make efficient use of data mining (DM) methods, it is required to know its capabilities and limits of application as a cognitive tool. The paper aims to specify the capabilities and limits of DM methods within the methodology of scientific cognition. This will enhance the efficiency of these DM methods for experts in this field as well as for professionals in other fields who analyze empirical data. It was proposed to supplement the existing classification of cognitive levels by the level of empirical regularity (ER) or provisional hypothesis. If ER is generated using DM software algorithm, it can be called the man-machine hypothesis. Thereby, the place of DM in the classification of the levels of empirical cognition was determined. The paper drawn up the scheme illustrating the relationship between the cognitive levels, which supplements the well-known schemes of their classification, demonstrates maximum capabilities of DM methods, and also shows the possibility of a transition from practice to the scientific method through the generation of ER, and further from ER to hypotheses, and from hypotheses to the scientific method. In terms of the methodology of scientific cognition, the most critical fact was established – the limitation of any DM methods is the level of ER. As a result of applying any software developed based on DM methods, the level of cognition achieved represents the ER level.

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Section: Literature Reviewmentioning

confidence: 99%

Data mining as a cognitive tool: Capabilities and limits

Polyakov

Khanin

Shevchenko

et al. 2021

Knowledge and Performance Management

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“…New research examines and addresses tracking items, collection, and positioning of monitoring points in the smart power surveillance system. The machine feature debugging of data mining in an IoT environment develops an experimental forum [13]. In work, a monitoring service is discussed that provides information on the status and availability of the machine tool in real-time [16].…”

Section: B Review Of Iot In Other Fieldsmentioning

confidence: 99%

Internet of Things Based Cutting Tool Status Monitoring in a Computer Numerical Control Milling Machine

Natarajan¹,

Gokulachandran²

2021

Int. J. Adv. Sci. Eng. Inf. Technol.

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The Internet of Things (IoT) in the manufacturing industry shares machine data in real time. The majority of industrial data can be gathered and processed from machines and other remote IoT devices in a production system through data streaming. As sensors become smaller and more affordable, the Internet of things will attract more attention. It is possible to employ a wide range of sensors for monitoring, and with efficient open-source software, the status of the operation can be evaluated effectively. Our work aims at providing instructions for sending data (cutting tool status time) from Particle Photon devices connected to CNC milling machines to open-source software called ThingSpeak. This task is accomplished by integrating the Particle Photon device with the infrared sensor to the CNC milling machine. Three axis CNC vertical milling machine is used to manufacture the sample component. The status of the cutting tool, in this case the cutting time for each machining feature is monitored. Using infrared technology, the sensor detects whether the cutting tool is present. Particle photons measure machining time and communicate it to ThingSpeak. The ThingSpeak library will interpret the cloud information and displays it. With ThingSpeak software, we define the fields for various cutting tools and track every tool in real time. The time recorded using ThingSpeak software is found to be near to the time, which is monitored manually by the user. A major step in computer assisted process planning in manufacturing is monitoring the machining time for each cutting tool and it is successfully implemented in this research work.

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“…e approach integrates the Data Lake and Data Warehouse and then defines the tool for collection of heterogeneous data. Sunhare et al [5] presented a comprehensive and systematic review of the different data mining techniques employed in small-and large-scale IoT for formulating an intelligent environment. e system of cloud-based IoT big data mining is also discussed.…”

Section: Related Workmentioning

confidence: 99%

Evaluating the Role of Big Data in IIOT-Industrial Internet of Things for Executing Ranks Using the Analytic Network Process Approach

Liao

Faisal

QingChang

et al. 2020

Scientific Programming

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Due to the enhancements of Internet of Things (IoT) and sensors deployments, the production of big data in Industrial Internet of Things (IIoT) is increased. The accessing and processing of big data become a challenging issue due to the limited storage space, computational time, networking, and IoT devices end. IoT and big data are well thought-out to be the key concepts when describing new information architecture projects. The techniques, tools, and methods that help to provide better solutions for IoT and big data can have an important role to play in the architecture of business. Different approaches are being practiced in the literature for evaluating the role of big data in IIoT. These techniques are not handling the situations when complexity of dependency arises among parameters of the alternatives. The proposed research uses the approach of Analytic Network Process (ANP) for evaluating the role of big data in IIoT. The results show that the proposed research works well for evaluating the role of big data in IIoT.

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Internet of things and data mining: An application oriented survey

Cited by 71 publications

References 130 publications

Data mining as a cognitive tool: Capabilities and limits

Data mining as a cognitive tool: Capabilities and limits

Internet of Things Based Cutting Tool Status Monitoring in a Computer Numerical Control Milling Machine

Evaluating the Role of Big Data in IIOT-Industrial Internet of Things for Executing Ranks Using the Analytic Network Process Approach

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