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Multimodal property video neuroanalytics.

Arturas Kaklauskas1, Valeria Minucciani2, Gianluca D'Agostino2

  • 1Vilnius Gediminas Technical University, Saulėtekio al. 11, LT-10223, Vilnius, Lithuania. arturas.kaklauskas@vilniustech.lt.

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Summary
This summary is machine-generated.

This study introduces Multimodal Property Video Neuroanalytics (MOVE), a low-cost system analyzing building data and investor emotions. MOVE enhances property valuation and provides recommendations for increasing value and improving green building ratings.

Keywords:
Affective computingBig real-time and low-cost dataCustomer-perceived valueEmotionsMultimodal property video neuroanalyticsRegression and multiple criteria analysisSustainability

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Area of Science:

  • Neuroscience
  • Computer Science
  • Real Estate

Background:

  • Smart technologies generate multimodal big data in buildings, but real-time well-being data remains inadequate.
  • Low-cost data collection methods are needed for detailed building insights.
  • Existing green building rating systems lack an emotional dimension.

Purpose of the Study:

  • Develop Multimodal Property Video Neuroanalytics (MOVE) for comprehensive property and investor analysis.
  • Integrate diverse data sources to assess emotional, affective, and physiological states (MAPS).
  • Provide evidence-based recommendations for property value enhancement and green building improvements.

Main Methods:

  • Combined circumplex model of affect, somatic marker hypothesis, regression, and multi-criteria analysis.
  • Integrated text, biometrics, audio, and image analysis technologies.
  • Developed multimodal analysis, fusion, regression, decision support, and value analysis subsystems.

Main Results:

  • MOVE determines perceived investment value by analyzing property, context, and investor MAPS.
  • The system provides digital, evidence-based recommendations to increase property value.
  • Incorporating investor MAPS data can significantly improve green building ratings.

Conclusions:

  • MOVE offers a novel, low-cost approach to collecting and analyzing multimodal building and investor data.
  • The system facilitates data-driven property valuation and strategic improvements.
  • Including an emotional dimension in green building rating systems is recommended for better quality reflection.