Configuring The Internet of Things (IoT): A Review and Implications for Big Data Analytics

Williams, Susan P.; Hardy, Cynthia; Nitschke, Patrick

doi:10.24251/hicss.2019.706

Cited by 8 publications

(2 citation statements)

References 49 publications

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“…Because the amount of data grows at an unprecedented scale and depth with the proliferation of smart and sensor devices, big data analytics has emerged as a key initiative in the IIoT field [6][7][8]. Recently, artificial intelligence (AI) has become a key factor in big data analytics in industrial applications [9].…”

Section: Industrial Internet Of Things In Service Businessmentioning

confidence: 99%

How the Data Provided by IIoT Are Utilized in Enterprise Resource Planning: A Multiple-Case Study of Three Change Projects

Rajamäki¹,

Tuppela²

2020

New Trends in the Use of Artificial Intelligence for the Industry 4.0

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An extreme increase in data production has taken place over the past few decades with a large number of sensor and smart devices acquired from distributed data sources. Industrial Internet of Things (IIoT) enables seamless processing of information by integrating physical and digital world devices that can be used ubiquitously. This multiple-case study analyzes how the data generated by the IIoT benefit enterprise resource planning. In the analyzed cases, IIoT has been produced using and integrating various digital services and software in the enterprise. Data produced by IIoT might be raw data or pre-analyzed by the IIoT service provider according to the enterprise's needs. Services based on IIoT solutions ensure competitiveness within the enterprise since IIoT is flexible and easy to apply on future demands. IIoT generates increased amount of data and enterprises can utilize it to provide significant benefits to their operations. The cross-case conclusions emphasize that improving operational processes with data does not provide maximal benefit to the enterprise. Data-driven procedure and the entire change project (digital transformation) together with new procedures will provide most benefits to the enterprise.

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Section: Industrial Internet Of Things In Service Businessmentioning

confidence: 99%

How the Data Provided by IIoT Are Utilized in Enterprise Resource Planning: A Multiple-Case Study of Three Change Projects

Rajamäki¹,

Tuppela²

2020

New Trends in the Use of Artificial Intelligence for the Industry 4.0

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“…The machine is directed toward improving protection at the exterior office. 40 The suggested platform comprises a wearable human body network system (WBAN) to get user info along with a low-power wide-area system (LPWAN). 41 The wearable detectors while in the WBAN are used to assess the environmental requirements around the area, working with a risk-free node, to track the most critical signals, and with an overall health node.…”

Section: Literature Reviewmentioning

confidence: 99%

Internet of medical things for smart D3S to enable road safety

Ramzan

Awan

Aldabbas

et al. 2019

International Journal of Distributed Sensor Networks

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It has been seen that most of the accidents occur due to driver’s fatigue. Drowsiness is a state of mind before the driver falls asleep, which means the driver could not accomplish his actions, such as vehicular braking, controlling vehicular motion, properly. We have built an Internet of things–based medical application to analyze driver’s drowsiness. An architecture has been proposed and a simulation of that scenario in NS3 WSN simulation tool has been done. This simulation shows that the ratio of accidents can be majorly reduced. When drowsiness of drivers is captured, a message alert is delivered to all other drivers of the vehicles that are near to the sleeping driver; for this, different sensor nodes are used. Another unique feature of the sensor network used here is the collaborative effect of sensor nodes. So for measurement and analysis of applications on Google Play, a dataset of the medical applications category was scraped. The scraping was done with 550 applications of each category of medical applications. On each application on Google Play store, almost 70 attributes for each category were scraped. It is envisioned that, in future, wireless sensor networks will be an integral part of our lives, more so than the present-day personal computers.

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