# Maximizing Consumer Satisfaction of IoT Energy Services

arXiv: https://arxiv.org/abs/2209.03619 · HTML: https://mlsanity.com/paper/2209.03619/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Sep 2022.

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

- [Monitoring Efficiency of IoT Wireless Charging](https://mlsanity.com/paper/2303.05629/) (2023)
- [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)-aware framework to crowdsource IoT energy services efficiently. The proposed framework leverages the provisioning of energy services as an auxiliary to increase consumers' satisfaction. A novel QoE model is developed as a metric to assess the consumers' satisfaction with the provisioning of energy services. Two novel composition algorithms, namely, Partial-Based (PB) and Demand-Based (DB) approaches, are proposed to ensure the highest QoE for consumers. Both approaches leverage the providers' flexibility and shareable nature of energy services to efficiently allocate services and optimize the QoE. A set of extensive experiments is conducted to evaluate the proposed approaches' efficiency and effectiveness.