Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 506

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Distributed Event-Triggered Estimation Over Sensor Networks: A Survey

Open access
Ge, Xiaohua, Han, Qing-Long, Zhang, Xian-Ming, Ding, Lei, Yang, Fuwen·2020·IEEE Transactions on Cybernetics

Abstract

An event-triggered mechanism is of great efficiency in reducing unnecessary sensor samplings/transmissions and, thus, resource consumption such as sensor power and network bandwidth, which makes distributed event-triggered estimation a promising resource-aware solution for sensor network-based monitoring systems. This paper provides a survey of recent advances in distributed event-triggered estimation for dynamical systems operating over resource-constrained sensor networks. Local estimates of an unavailable state signal are calculated in a distributed and collaborative fashion based on only invoked sensor data. First, several fundamental issues associated with the design of distributed estimators are discussed in detail, such as estimator structures, communication constraints, and design methods. Second, an emphasis is laid on recent developments of distributed event-triggered estimation that has received considerable attention in the past few years. Then, the principle of an event-triggered mechanism is outlined and recent results in this subject are sorted out in accordance with different event-triggering conditions. Third, applications of distributed event-triggered estimation in practical sensor network-based monitoring systems including distributed grid-connected generation systems and target tracking systems are provided. Finally, several challenging issues worthy of further research are envisioned.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1109/tcyb.2019.2917179

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 506

Metadata

Authors
Ge, X., Han, Q.-L., Zhang, X.-M., Ding, L., & Yang, F.
Venue
IEEE Transactions on Cybernetics
Published
2020-03
Volume
50
Issue
3
Pages
1306-1320
ISSN
  • 2168-2267 (ISSN-L)
  • 2168-2275
OpenAlex
W2951782192
Cited by
506
References
1
FWCI
40.66
Type
journal article
Language
en
Open access
green

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 ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Distributed Event-Triggered Estimation Over Sensor Networks: A Survey. https://app.cochat.ai/papers/10.1109/tcyb.2019.2917179
The paper
Ge, X., Han, Q.-L., Zhang, X.-M., Ding, L., & Yang, F. (2020). Distributed Event-Triggered Estimation Over Sensor Networks: A Survey. IEEE Transactions on Cybernetics. https://doi.org/10.1109/tcyb.2019.2917179

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.