## Paper 4: Optimal Sensor Placement with Minimal Predicted Posterior Variance
**Authors:** Mendler, A., Marsili, N., Kessler, S., Grosse, C.
**Year:** 2024
**Venue:** *Unknown*
**DOI:** [10.58286/29612](https://doi.org/10.58286/29612)

### Research Question
How to optimize the physical placement of sensors to minimize prediction errors (posterior variance) in monitoring systems.

### Methodology
- **Design:** Mathematical Modeling / Engineering Optimization.
- **Approach:** Bayesian inference or similar statistical prediction methods [VERIFY].

### Key Findings
*Inferred:* Development of an algorithm that reduces the number of sensors needed while maintaining data quality.

### Relevance to Your Research
**Score:** ⭐⭐ (2/5)
**Why:** Highly technical. Only relevant if your supply chain research involves specific IoT sensor deployment strategies for the "agri-food" monitoring mentioned in Paper 1.

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