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FedSDM: Federated learning based smart decision making module for ECG data in IoT integrated Edge-Fog-Cloud computing environments paper by Independent / Community
⭐ 70.2
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Paper

FedSDM: Federated learning based smart decision making module for ECG data in IoT integrated Edge-Fog-Cloud computing environments

by Independent / Community 002019b0142b04acbc7afa17391949d518183f20
Free2AITools Nexus Index
70.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 87
P: Popularity 64
R: Recency 100
Q: Quality 65
Tech Context
Vital Performance —

Massive data collection in modern systems has paved the way for data-driven machine learning, a promising technique for creating reliable and robust statistical models. By combining the data into centralized storage to develop a reliable learning model, there are concerns with privacy, ownership, and strict rules. It is self-evident that the samples in the typical machine learning centralized server paradigm have vastly different probability distributions of data supplied by each user. As a r...

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Semantic Scholar 118 Citations
Paper Information Summary
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Registry ID 002019b0142b04acbc7afa17391949d518183f20
License ArXiv
Provider semantic_scholar
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Cite this paper

Academic & Research Attribution

BibTeX 
@misc{002019b0142b04acbc7afa17391949d518183f20,
  author = {Unknown},
  title = {FedSDM: Federated learning based smart decision making module for ECG data in IoT integrated Edge-Fog-Cloud computing environments Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/002019b0142b04acbc7afa17391949d518183f20}},
  note = {Accessed via Free2AITools.}
}
APA Style
Unknown. (2026). FedSDM: Federated learning based smart decision making module for ECG data in IoT integrated Edge-Fog-Cloud computing environments [Paper]. Free2AITools. https://api.semanticscholar.org/002019b0142b04acbc7afa17391949d518183f20

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βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 87
Popularity (P) 64
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for FedSDM: Federated learning based smart decision making module for ECG data in IoT integrated Edge-Fog-Cloud computing environments: Authority (A:87), Popularity (P:64), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

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πŸ“ Executive Summary

"Massive data collection in modern systems has paved the way for data-driven machine learning, a promising technique for creating reliable and robust statistical models. By combining the data into centralized storage to develop a reliable learning model, there are concerns with privacy, ownership, and strict rules. It is self-evident that the samples in the typical machine learning centralized server paradigm have vastly different probability distributions of data supplied by each user. As a r..."

❝ Cite Node 

@article{Unknown2026FedSDM:,
  title={FedSDM: Federated learning based smart decision making module for ECG data in IoT integrated Edge-Fog-Cloud computing environments},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

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πŸ“Š Research Signals

πŸ“ˆ118CitationsSemantic Scholar
πŸ›οΈ87AuthorityFNI pillar
⏱️100RecencyFNI pillar
βœ…65QualityFNI pillar
πŸ—‚οΈautomation workflowField

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πŸ†” Identity & Source

source
semantic_scholar
author
Unknown
license
ArXiv
tags
paper, research, academic

βš™οΈ Technical Specs

architecture
null
params billions
null
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null
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