Consensual Negotiation-Based Decision Making for Connected Appliances in Smart Home Management Systems

Area of Science:

• Computer Science
• Artificial Intelligence
• Energy Systems

Background:

• The Internet of Agent concept enables distributed intelligence and data processing at the data source.
• Home energy management systems require intelligent solutions for efficient resource allocation and demand reduction.

Purpose of the Study:

• To propose a novel decentralized home energy management system (DHEMS) leveraging the Internet of Agent concept.
• To develop a framework for intelligent, collaborative, and decision-making capabilities among connected home appliances.
• To address the load balancing problem in smart homes through dynamic scheduling and load shifting.

Main Methods:

• An Internet of Agent framework is presented, detailing sensing, communication, and collaboration among appliances.
• A decentralized management approach is proposed, utilizing consensual negotiation and intelligent techniques for appliance scheduling.
• Connected appliances are modeled as intelligent agents capable of independent decision-making and resource negotiation.

Main Results:

• The proposed system effectively manages energy consumption in a simulated smart home environment.
• The decentralized approach demonstrates successful load balancing by shifting demand away from peak hours.
• Consensual negotiation among agents facilitates dynamic scheduling of connected appliances.

Conclusions:

• The Internet of Agent concept offers a viable framework for decentralized home energy management.
• The developed approach effectively reduces electricity demand during peak hours through intelligent load balancing.
• This research highlights the potential of agent-based systems for optimizing smart home energy efficiency.