# A communication-efficient, online changepoint detection method for monitoring distributed sensor networks

arXiv: https://arxiv.org/abs/2403.18549 · HTML: https://mlsanity.com/paper/2403.18549/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Mar 2024.

## Built on by (most cited first, 2 of 2)

- [Information-Geometric First-Passage Monitoring of Distributional Stability in Stochastic Systems](https://mlsanity.com/paper/2604.24083/) (2026)
- [An Efficient Likelihood Ratio Test for Online Changepoint Detection in the Presence of Autocorrelation](https://mlsanity.com/paper/2607.16106/) (2026)

## Abstract (arXiv)

We consider the challenge of efficiently detecting changes within a network of sensors, where we also need to minimise communication between sensors and the cloud. We propose an online, communication-efficient method to detect such changes. The procedure works by performing likelihood ratio tests at each time point, and two thresholds are chosen to filter unimportant test statistics and make decisions based on the aggregated test statistics respectively. We provide asymptotic theory concerning consistency and the asymptotic distribution if there are no changes. Simulation results suggest that our method can achieve similar performance to the idealised setting, where we have no constraints on communication between sensors, but substantially reduce the transmission costs.