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Smart Home Product Layout Design Method Based on Real-Number Coding Genetic Algorithm.

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This study introduces an optimized smart home product layout design using a real-number genetic algorithm. The method enhances design efficiency and planning rationality for smart homes, improving overall user experience.

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Area of Science:

  • Smart Home Technology
  • Artificial Intelligence
  • Computational Design

Background:

  • Current smart home product layout design suffers from inefficiency and irrational planning.
  • Optimizing spatial arrangement is crucial for smart home functionality and user experience.

Purpose of the Study:

  • To propose an efficient and rational layout design method for smart home products.
  • To develop an optimization model and algorithm for smart home spatial planning.

Main Methods:

  • Analysis of smart home product layout design principles and Internet of Things (IoT) system architecture.
  • Spatial functional division, visual feature extraction, and optimization model creation with area constraints.
  • Implementation of a real-coded genetic algorithm for layout optimization.

Main Results:

  • The proposed method accurately extracts smart home product layout features.
  • The algorithm effectively classifies home layout configurations.
  • Demonstrated improvements in layout design efficiency and planning rationality.

Conclusions:

  • The real-number coding genetic algorithm provides an effective solution for smart home product layout optimization.
  • This approach enhances both the efficiency and rationality of smart home design.
  • The method offers a valuable tool for improving smart home spatial planning.