PLANNING AND DESIGN OF RESTAURANT ESTABLISHMENTS USING ARTIFICIAL INTELLIGENCE
Abstract
Creating an attractive design for a restaurant enterprise is the key to its success, as it plays a key role in forming the first impression for guests and creating an atmosphere conducive to a pleasant pastime. One of the notable trends in modern interior design for restaurants is the increased attention to creating unique designs and forging an emotional connection with the guests of the establishment. At the same time, one should not forget about functionality. The rational organization of the interior of the establishment largely determines the quality of service, because a reasonably organized space is responsible for the speed of movement of the employees and the comfort of the visitors. However, despite the large number of existing solutions, designing restaurant establishments remains a complex, multifaceted task. The use of modern informational technologies, particularly, artificial intelligence, allows to significantly simplify the process of creating new designs. Therefore, the task of this study is to analyze the capabilities of artificial intelligence for designing restaurant establishments. The application of artificial intelligence in the design of restaurant spaces covers a wide range of tasks, from analytical to creative. Generative models act as a powerful tool for visualizing ideas, allowing designers and architects to quickly generate and test a variety of stylistic and planning solutions. The main areas of using artificial intelligence tools in restaurant design include: concept and style generation, visualization of interiors, preliminary planning and optimization of space, selection of materials and furniture, lighting analysis, model personalization and testing. However, while this can significantly simplify and accelerate a designer’s work, generated text, images, and videos are not guaranteed to be accurate, especially in regards to geometry and technical data. Models created by artificial intelligence can be wrong, so the results require careful expert verification to check their compliance with existing building codes and technical specifications.
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