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Editorial: Industrial Internet of Things (I2oT) - Springer MONET SI

Authors

Abstract

Industrial Internet of Things (I2oT) consists of a variety of objects (e.g., sensors, RFID tags, actuators, mobile devices, appliances, industrial equipment), which could communicate and cooperate with each other to perform information sensing and automatically control, fulfilling various industrial applications (e.g., intelligent manufacturing, product quality inspection, equipment diagnostics, intelligent logistics). The essence of the I2oT is to provide companies with the opportunity to enhance their computing paraphernalia for use in industry, which in turn will render them more proficient and more profitable. By virtue of transforming embedded computers into intelligent systems, companies can improve the throughput of their processes and workforces, boost their productivity and hence enter new horizons. Numerous world-leading companies have discovered the great potential to benefit from I2oT. The realization of I2oT involves establishing smart connected infrastructures and remotely interconnecting the industrial applications with users by utilizing technologies such as distributed computing, ubiquitous computing and Cloud. However, there are still quite a number of critical issues (e.g., sensor deployment, big data and analysis, information management, information services, query processing, network security, software system) which could strongly influence the successful realization of I2oT.

Subject

Industrial IoT

TechReport Number

N/A

DOI


Cited by

Year 2020 : 2 citations

 J. Khan et al., "SMSH: Secure Surveillance Mechanism on Smart Healthcare IoT System With Probabilistic Image Encryption," in IEEE Access, vol. 8, pp. 15747-15767, 2020. DOI: 10.1109/ACCESS.2020.2966656

 Abdul Rehman, Anand Paul, Muhammad Azfar Yaqub, and Muhammad Mazhar Ullah Rathore. 2020. Trustworthy intelligent industrial monitoring architecture for early event detection by exploiting social IoT. In Proceedings of the 35th Annual ACM Symposium on Applied Computing (SAC ’20). Association for Computing Machinery, New York, NY, USA, 2163–2169. DOI:https://doi.org/10.1145/3341105.3373996

Year 2019 : 1 citations

 Ke Wang, Migration strategy of cloud collaborative computing for delay-sensitive industrial IoT applications in the context of intelligent manufacturing, Computer Communications, Volume 150, 2020, Pages 413-420, ISSN 0140-3664, DOI: 10.1016/j.comcom.2019.12.014.

Year 2018 : 2 citations

 Shama N. Islam, M.A. Mahmud, A.M.T. Oo, Impact of optimal false data injection attacks on local energy trading in a residential microgrid, ICT Express, Available online 21 February 2018, ISSN 2405-9595, https://doi.org/10.1016/j.icte.2018.01.015.

 Pilloni, V. How Data Will Transform Industrial Processes: Crowdsensing, Crowdsourcing and Big Data as Pillars of Industry 4.0. Future Internet 2018, 10, 24. doi: 10.3390/fi10030024.