The Internet of Things—A survey of topics and trends
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The Industry 4.0 approach can be integrated into microalgal biorefinery for automation of cultivation and harvesting systems to decrease the cost of operation and also to monitor the microalgal growth and productivity in real-time.
“This approach can be integrated into microalgal biorefinery for automation of cultivation and harvesting systems to decrease the cost of operation and also to monitor the microalgal growth and productivity in real-time (Whitmore et al. 2014).”
From Production of microalgae with high lipid content and their potential as sources of nutraceuticals (2023) · cites this paper as Whitmore et al. 2014
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Making the Internet of Things a Reality: The WhereX Solution
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Information architecture for intelligent products in the internet of things
Främling, K., & Nyman, J. (2008) · Cited by 20 · see citing works
Towards unified tag data translation for the Internet of Things
Schmidt, L., Mitton, N., & Simplot‐Ryl, D. (2009) · International Conference on Wireless Communication, Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology · doi:10.1109/wirelessvitae.2009.5172469 · Cited by 18 · see citing works
A Triple Space-Based Semantic Distributed Middleware for Internet of Things
Gómez-Goiri, A., & López–de–Ipiña, D. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-16985-4_43 · Cited by 17 · see citing works
Connected objects and the Internet of things — A paradigm shift
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Research on the complexity in Internet of Things
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A Living Lab for Internet of Things Vending Machines
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An internet of things that do not exist
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Object Service Provision in Internet of Things
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Flagged first, then by citations
Cited by
Sorted by citations
Internet of things and supply chain management: A literature review
Ben-Daya, M., Hassini, E., & Bahroun, Z. (2019) · International Journal of Production Research · doi:10.1080/00207543.2017.1402140 · Cited by 1,501 · see citing works
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
Al-Garadi, M. A., Mohamed, A., Al-Ali, A. K., Du, X., Ali, I., & Guizani, M. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2988293 · Cited by 1,392 · see citing works
Internet of Things (IoT): A review of enabling technologies, challenges, and open research issues
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“1) Key Distribution: Key distribution is a challenging requirement for many applications in the IoT [68], and naturally extends to the IIoT.”
BackgroundFabris, M., Abbriano, R. M., Pernice, M., Sutherland, D. L., Commault, A. S., Hall, C. C., Labeeuw, L., McCauley, J. I., Kuzhiuparambil, U., Ray, P., et al. (2020) · Frontiers in Plant Science · doi:10.3389/fpls.2020.00279 · Cited by 382 · see citing works
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Full spectrum sharing in cognitive radio networks toward 5G: a survey
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A framework of digital technologies for the circular economy: digital functions and mechanisms
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Production of microalgae with high lipid content and their potential as sources of nutraceuticals
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“This approach can be integrated into microalgal biorefinery for automation of cultivation and harvesting systems to decrease the cost of operation and also to monitor the microalgal growth and productivity in real-time (Whitmore et al. 2014).”
BackgroundA study of Artificial Intelligence impacts on Human Resource Digitalization in Industry 4.0
Murugesan, U., Subramanian, P., Srivastava, S., & Dwivedi, A. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100249 · Cited by 217 · see citing works
Threat-Based Security Analysis for the Internet of Things
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Machine Learning-Enabled Internet of Things (IoT): Data, Applications, and Industry Perspective
Bzai, J., Alam, F., Dhafer, A., Bojović, M., Altowaijri, S. M., Niazi, I. K., & Mehmood, R. (2022) · Electronics · doi:10.3390/electronics11172676 · Cited by 110 · see citing works
Developing human resource data risk management in the age of big data
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Data quality and the Internet of Things
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The evolution of distributed computing systems: from fundamental to new frontiers
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- Authors
- Whitmore, A., Agarwal, A., & Da Xu, L.
- Affiliations
- University of South Florida (US)
- Corresponding author
- Agarwal, Anurag
- ORCID
- Whitmore, Andrew
- Venue
- Information Systems Frontiers
- Published
- 2014-03-12
- Volume
- 17
- Issue
- 2
- Pages
- 261-274
- ISSN
- 1387-3326 (ISSN-L)
- 1572-9419
- OpenAlex
- W2037759417
- Cited by
- 1,568
- References
- 131
- Citations by year
- 2026: 39 · 2025: 83 · 2024: 85 · 2023: 107 · 2022: 144 · 2021: 156 · 2020: 223 · 2019: 219 · 2018: 205 · 2017: 171 · 2016: 101 · 2015: 27 · 2014: 8
- FWCI
- 117.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Information Systems Frontiers (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT Networks and Protocols
- Keywords
- Internet of Things, IoT adoption challenges, ubiquitous computing, context awareness, ambient intelligence, IoT devices
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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