The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Stream Processing of Healthcare Sensor Data: Studying User Traces to Identify Challenges from a Big Data Perspective
Open accessAbstract
The Internet of Things (IoT) generates massive streams of data which call for ever more efficient real time processing. Designing and implementing a big data service for the real time processing of such data requires an extensive knowledge of both input load and data distribution in order to provide a service which can cope with the workload. In this context, we study in this paper the challenges inherent to the real time processing of massive data flows from the IoT. We provide a detailed analysis of traces gathered from a well-known healthcare sport-oriented application in order to illustrate our conclusions from a big data perspective.
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Chen, M., Mao, S., & Liu, Y. (2014) · Mobile Networks and Applications · doi:10.1007/s11036-013-0489-0 · Cited by 2,913
Cited by
Fog Computing: Helping the Internet of Things Realize Its Potential
Dastjerdi, A. V., & Buyya, R. (2016) · Computer · doi:10.1109/mc.2016.245 · Cited by 1,047
Fog Computing: principles, architectures, and applications
Dastjerdi, A. V., Gupta, H., Calheiros, R. N., Ghosh, S. K., & Buyya, R. (2016) · Internet of Things · doi:10.1016/b978-0-12-805395-9.00004-6 · Cited by 573
Shifting machine learning for healthcare from development to deployment and from models to data
Zhang, A., Xing, L., Zou, J., & Wu, J. C. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00898-y · Cited by 420
Metalearning: A survey of trends and technologies
Lemke, C., Budka, M., & Gabrys, B. (2015) · Artificial Intelligence Review · doi:10.1007/s10462-013-9406-y · Cited by 365
Bilal, K., Khalid, O., Erbad, A., & Khan, S. U. (2018) · Computer Networks · doi:10.1016/j.comnet.2017.10.002 · Cited by 334
Metadata
- Authors
- Cortés, R., Bonnaire, X., Marin, O., & Sens, P.
- Venue
- Procedia Computer Science
- Publisher
- Elsevier BV
- Published
- 2015
- Volume
- 52
- Pages
- 1004-1009
- ISSN
- 1877-0509 (ISSN-L)
- OpenAlex
- W579984701
- Cited by
- 357
- References
- 1
- FWCI
- 29.96
- Type
- conference paper
- Language
- en
- Open access
- diamond
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- Cortés, R., Bonnaire, X., Marin, O., & Sens, P. (2015). Stream Processing of Healthcare Sensor Data: Studying User Traces to Identify Challenges from a Big Data Perspective. Procedia Computer Science. https://doi.org/10.1016/j.procs.2015.05.093
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
