Structural design systems and methods to define areas of interest for modeling and simulation-based space planning

#The present disclosure relates generally to systems and methods for selecting and placing equipment for use in buildings. Disclosed systems and methods may involve automatically simulating equipment selection and placement locations in a floor plan.

#When designing the interior of a building, an architect or structural engineer may consider, from a large list of equipment specifications, which equipment may be appropriate for s space, where to place it, and how to orient it. At the same time, the architect or structural engineer must consider costs and structural issues that may arise from using one piece of equipment over another. Conventional approaches to this aspect of designing the interior of a building may rely on human judgment or overly simplistic algorithms, thereby lacking the ability to automatically perform these tasks in an efficient and optimized manner. Further, some areas within a floor plan, including areas inside a room, may have different requirement than adjacent areas, or may be particularly important. For example, camera coverage or the lighting of an egress may be more important to design than coverage in other areas of a room, and camera coverage may be undesired in private spaces such as bathrooms or changing rooms. Conventional solutions may fail to identify such areas of interest or disinterest accurately in automated way, or may be labor intensive and fail to efficiently scale or be consistently applied when planning using dozens, hundreds, or even thousands of floor plans.

#Embodiments consistent with the present disclosure provide systems and methods for architectural planning. The disclosed systems and methods may be implemented using a combination of conventional hardware and software as well as specialized hardware and software, such as a machine constructed and/or programmed specifically for performing functions associated with the disclosed method steps. Consistent with other disclosed embodiments, non-transitory computer-readable storage media may store program instructions, which are executable by at least one processing device and perform any of the steps and/or methods described herein.

#The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate various disclosed embodiments. In the drawings:

#FIG. 1 is a block diagram illustrating an example of an optimization-based generative analyses process, for identifying technical specifications and equipment locations, consistent with the disclosed embodiments.

#FIGS. 2A and 2B illustrate example rule-based generative analyses process for identifying technical specifications and equipment locations that may be performed, consistent with the disclosed embodiments.

#In architectural planning, selecting the appropriate specifications and locations for equipment to be used in many rooms in a floor plan can be a daunting task. For example, each room may have multiple functional requirements that may affect the selection and placement of equipment within the room. Further, there may be thousands of possible combinations of equipment specifications and placement locations, each with varying degrees of conformance to the functional requirements.

#Therefore, there is a need for unconventional approaches that enable users to input functional specifications for multiple rooms into a system configured to run a series of simulations to automatically suggest equipment and equipment placement within the rooms.

#The disclosed methods and systems are directed to provided new and unconventional methods of selective simulation of equipment coverage in a floor plan. Conventional approached to selecting equipment in a floor plan may be unable to generate accurate, optimized plans due to resource constraints given the labor-intensive engineering and drafting process or when information is lacking (e.g., a designer may make a “best guess” or assumption when estimating equipment location, install time, etc.). Additionally, the interconnectivity of multiple complex systems may impose significant challenges when attempting to select equipment to improve performance (e.g., improved energy efficiency). As a result, conventional approaches may lead to inefficiencies, high costs, sub optimal solutions, and/or rigid plans that are not customized to a particular need.