Environment Optimization Scheme Based on Edge Computing Using PSO for Efficient Thermal Comfort Control in Resident Space

Rongxu Xu,Dohyeun Kim,Wenquan Jin

doi:10.3390/act10090241

Abstract

With the fast development of infrastructure and communication technology, the Internet of Things (IoT) has become a promising field. Ongoing research is looking at the smart home environment as the most promising sector that adopts IoT and cloud computing to improve resident live experiences. The IoT and cloud-dependent smart home services related to recent researches have security, bandwidth issues, and a lack of concerning thermal comfort of residents. In this paper, we propose an environment optimization scheme based on edge computing using Particle Swarm Optimization (PSO) for efficient thermal comfort control in resident space to overcome the aforementioned limitations of researches on smart homes. The comfort level of a resident in a smart home is evaluated by Predicted Mean Vote (PMV) that represents the thermal response of occupants. The PSO algorithm combined with PMV to improve the accuracy of the optimization results for efficient thermal comfort control in a smart home environment. We integrate IoT with edge computing to upgrade the capabilities of IoT nodes in computing power, storage space, and reliable connectivity. We use EdgeX as an edge computing platform to develop a thermal comfort considering PMV-based optimization engine with a PSO algorithm to generate the resident’s friendly environment parameters and rules engine to detects the environmental change of the smart home in real-time to maintain the indoor environment thermal comfortable. For evaluating our proposed system that maintenance resident environment with thermal comfort index based on PSO optimization scheme in smart homes, we conduct the comparison between the real data with optimized data, and measure the execution times of optimization function. From the experimental results, when our proposed system is applied, it satisfies thermal comfort and consumes energy more stably.

Highlights

With the fast development of infrastructure and information technology, the Internet of Things (IoT) has become a promising field in the domain of global information and communication technology
In order to provide a residential environment customized for resident thermal comfort, we propose an environment optimization scheme based on edge computing using Particle Swarm Optimization (PSO) for efficient thermal comfort control in resident space
We investigate smart home control-related technologies

Summary

Introduction

With the fast development of infrastructure and information technology, the IoT has become a promising field in the domain of global information and communication technology. A smart home is one of the applications of the IoT, which is the connectivity of physical objects that allows a digital device, sensor, application, and network communication inside a home [3]. The author [4] describes a smart home as a user armed with a technology of computing and information, which inference and reacts to the requirement of the residents, trying to improve their living experiences such as convenience, comfort, and security by the control system within the home environment and connections to the world beyond. There is a control system called “gateways”, which provides communication ability to connect switches and sensors. The control system develops a user interface that allows consumers to interact with the system through a smartphone, a tablet, or a laptop

Methods

Results

Conclusion