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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
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Consensual Negotiation-Based Decision Making for Connected Appliances in Smart Home Management Systems.

Khac-Hoai Nam Bui1, Jason J Jung2, David Camacho3

  • 1Department of Computer Engineering, Chung-Ang University, Seoul 156-756, Korea. hoainam.bk2012@gmail.com.

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|July 11, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a decentralized home energy management system using the Internet of Agents. It enables smart appliances to negotiate energy use, effectively balancing loads and reducing peak demand.

Keywords:
Internet of Agentconsensual negotiationdecentralized systemload balancingsmart decision-makingsmart home energy management system

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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.