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Generative AI in Graph-Based Spatial Computing: Techniques and Use Cases

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  • Sankara Reddy Thamma

Abstract

Generative AI has proven itself as an efficient innovation in many fields including writing and even analyzing data. For spatial computing, it provides a potential solution for solving such issues related to data manipulation and analysis within the spatial computing domain. This paper aims to discuss the probabilities of applying generative AI to graph-based spatial computing; to describe new approaches in detail; to shed light on their use cases; and to demonstrate the value that they add. This technique thus incorporates graph theory, generative models to model spatial relations, generate new spatial forms and improve on spatial decision-making processes. The paper surveys such methods, describes typical applications, and outlines further development of the subject.

Suggested Citation

  • Sankara Reddy Thamma, 2024. "Generative AI in Graph-Based Spatial Computing: Techniques and Use Cases," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 11(2), pages 1012-1023, April.
    • Handle: RePEc:etm:ijsrst:v11:y2024:i2:id:545
    DOI: 10.32628/IJSRST24112135
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