# Timely Monitoring of Dynamic Sources with Observations from Multiple Wireless Sensors

arXiv: https://arxiv.org/abs/2012.12179 · HTML: https://mlsanity.com/paper/2012.12179/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Dec 2020.

## Built on by (most cited first, 3 of 3)

- [Multimodal Remote Inference](https://mlsanity.com/paper/2508.07555/) (2025)
- [Timeliness-Oriented Scheduling and Resource Allocation in Multi-Region Collaborative Perception](https://mlsanity.com/paper/2601.04542/) (2026)
- [TALSC: Timeliness-Aware Large-Small VLM Collaboration for Infrastructure-Assisted Autonomous Driving](https://mlsanity.com/paper/2608.01998/) (2026)

## Abstract (arXiv)

Age of Information (AoI) has recently received much attention due to its relevance in IoT sensing and monitoring applications. In this paper, we consider the problem of minimizing the AoI in a system in which a set of sources are observed by multiple sensors in a many-to-many relationship, and the probability that a sensor observes a source depends on the state of the source. This model represents many practical scenarios, such as the ones in which multiple cameras or microphones are deployed to monitor objects moving in certain areas. We formulate the scheduling problem as a Markov Decision Process, and show how the age-optimal scheduling policy can be obtained. We further consider partially observable variants of the problem, and devise approximate policies for large state spaces. Our evaluations show that the approximate policies work well in the considered scenarios, and that the fact that sensors can observe multiple sources is beneficial, especially when there is high uncertainty of the source states.