The role of data management in the Industrial Internet of Things

Author(s):  
Lulwah AlSuwaidan

Robotic systems can already proactively monitor and adapt to changes in a production line. Nowadays, internet of things and robotic systems are key drivers of technological innovation trends.Majorcompanies are now making investments in machine learning-powered approaches to improve in principle all aspects of manufacturing. Connecteddevices, sensors, and similar advancements allow people and companies to do things they wouldn't even dream of in earlier eras.For realizing it time series feature extraction approach is selected.Industrial internet of things solutions are poised to transform many industry verticals including healthcare, retail, automotive, and transport. For many industries, the industrial internet of things has significantly improved reliability, production, and customer satisfaction. The internet of things and robotics arecoming together to create the internet of robotic things. Industrial internet of thingis a subset of industry4.0. Itcan encourage smartness at a bigger level in industrial robots.


2019 ◽  
Vol 23 (04) ◽  
pp. 1950036 ◽  
Author(s):  
JENS BUTSCHAN ◽  
SVEN HEIDENREICH ◽  
BENJAMIN WEBER ◽  
TOBIAS KRAEMER

Scientific research and innovation management practice have emphasised the important role of individual competencies in meeting the challenges of the digital transformation. However, it still lacks empirical studies that strive to determine how certain competencies of employees might affect the success of the digital transformation itself. In order to empirically determine the individual contribution of specific employee competencies to a successful digital transformation in terms of a high Industrial Internet of Things (IIoT) usage performance, a quantitative study among German component manufacturers of the capital goods industry was conducted. Drawing upon a sample of 284 employees, our results reveal that high developed cognitive and processual competencies of individuals promote the digital transformation processes of a firm. Surprisingly, social competencies have only a little influence. Furthermore, our findings also confirmed that a high IIoT usage performance is beneficial for a firm, significantly enhancing divisional success.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wenken Tan ◽  
Jianmin Hu

With the rapid development of the industrial Internet of Things and the comprehensive popularization of mobile intelligent devices, the construction of smart city and economic development of wireless network demand are increasingly high. SDN has the advantages of control separation, programmable interface, and centralized control logic. Therefore, integrating this technical concept into the smart city data management WLAN network not only can effectively solve the problems existing in the previous wireless network operation but also provide more functions according to different user needs. In this case, the traditional WLAN network is of low cost and is simple to operate, but it cannot guarantee network compatibility and performance. From a practical perspective, further network compatibility and security are a key part of industrial IoT applications. This paper designs the network architecture of smart city industrial IoT based on SDN, summarizes the access control requirements and research status of industrial IoT, and puts forward the access control requirements and objectives of industrial IoT based on SDN. The characteristics of the industrial Internet of Things are regularly associated with data resources. In the framework of SDN industrial Internet of Things, gateway protocol is simplified and topology discovery algorithm is designed. The access control policy is configured on the gateway. The access control rule can be dynamically adjusted in real time. An SDN-based intelligent city industrial Internet of Things access control function test platform was built, and the system was simulated. The proposed method is compared with other methods in terms of extension protocol and channel allocation algorithm. Experimental results verify the feasibility of the proposed scheme. Finally, on the basis of performance analysis, the practical significance of the design of a smart city wireless network hierarchical data management system based on SDN industrial Internet of Things architecture is expounded.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 43088-43099 ◽  
Author(s):  
Muhammad Babar ◽  
Fazlullah Khan ◽  
Waseem Iqbal ◽  
Abid Yahya ◽  
Fahim Arif ◽  
...  

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shafique Ur Rehman ◽  
Khurram Ashfaq ◽  
Stefano Bresciani ◽  
Elisa Giacosa ◽  
Jens Mueller

PurposeThe authors observe the influence of intellectual capital (IC) on innovation performance with the mediating role of interorganizational learning (IOL) in the Pakistani automotive industry. Besides, industrial Internet of things (IoT) technology is used as moderating variables between IOL and innovation performance.Design/methodology/approachStructural equation modeling (SEM) presents scholars with extra flexibility and enhanced research conclusions. SEM is described as a statistical methodology and the best tool used for hypothesis testing. The authors used partial least squares SEM for testing hypotheses. The simple random sampling technique followed to collect data from respondents, and 492 questionnaires were used for analysis.FindingsThe outcomes reveal that IC enhances innovation performance and IOL. Moreover, IOL increases innovation performance. IOL significantly mediates between IC and innovation performance. Industrial IoT technology improves innovation performance. Finally, industrial IoT technology strengthens the positive association between IOL and innovation performance.Practical implicationsThis study concentrates on the issue of how managers use IOL and industrial IoT technology to take higher advantage of IC that increases innovation performance.Originality/valueThis is the initial study that builds a theoretical framework to integrate IC, IOL, industrial IoT technology and innovation performance. Although prior researchers observe the association between IC and innovation performance, less concentration was paid to understand the role of interorganizational leadership and industrial IoT technology in leveraging organizational IC.


2019 ◽  
Vol 99 ◽  
pp. 247-259 ◽  
Author(s):  
Muhammad Habib ur Rehman ◽  
Ibrar Yaqoob ◽  
Khaled Salah ◽  
Muhammad Imran ◽  
Prem Prakash Jayaraman ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Xiaoqun Liao ◽  
Mohammad Faisal ◽  
Qing QingChang ◽  
Amjad Ali

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.


2020 ◽  
Author(s):  
Karthik Muthineni

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.


Author(s):  
С.Л. Добрынин ◽  
В.Л. Бурковский

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage


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