# Quality of Experience Optimization in IoT Energy Services

arXiv: https://arxiv.org/abs/2208.13506 · HTML: https://mlsanity.com/paper/2208.13506/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Aug 2022.

## Built on by (most cited first, 5 of 5)

- [Monitoring Efficiency of IoT Wireless Charging](https://mlsanity.com/paper/2303.05629/) (2023)
- [IMAP: Individual huMAn mobility Patterns visualizing platform](https://mlsanity.com/paper/2209.03615/) (2022)
- [DIY-IPS: Towards an Off-the-Shelf Accurate Indoor Positioning System](https://mlsanity.com/paper/2209.03613/) (2022)
- [Energy Loss Prediction in IoT Energy Services](https://mlsanity.com/paper/2305.10238/) (2023)
- [CrowdWeb: A Visualization Tool for Mobility Patterns in Smart Cities](https://mlsanity.com/paper/2305.12935/) (2023)

## Abstract (arXiv)

We propose a novel Quality of Experience (QoE) metric as a key criterion to optimize the composition of energy services in a crowdsourced IoT environment. A novel importance-based composition algorithm is proposed to ensure the highest QoE for consumers. A set of experiments is conducted to evaluate the proposed approaches' effectiveness and efficiency.