Designing any product requires a lot of analysis and research. It is also true for designing any building. Before we begin to design any building, we collect information about the location where we are designing, we check the budget, we do research about the background of the target audience and their likes and dislikes.

In designing any space you need to follow some preliminary steps, like budget analysis, client requirements, form & concept development, site analysis, and zoning.

Site Analysis is one of the major steps in the pre-designing processes. It involves analysis and evaluating topography, watercourses, trees, manmade features, site boundaries, habitats, wind circulations, connectivity to main roads, streets and pathways, distance to closest facilities or amenities, climatic conditions, and weather patterns.

Photo Credit: SERA Architects

In my Architectural Design course, we were given the assignment to design a restaurant in our home town, with very minimum and basic specifications. Having complete freedom to choose the site, concept, form, building materials, and cuisine offered, it required a lot of thinking and creativity.

But it is very difficult to locate the ideal location in such a big city as it also requires a huge amount of research to locate a site because the restaurant should also be successful in business after it starts to function. So instead of choosing my favorite or city’s most popular restaurant’s or cafe’s location as my site, I thought of implementing Data Science for analyzing the data of the restaurants in Pune (my home city, in the western Indian state of Maharashtra) and then using Machine Learning to locate the ideal site.

For Data Scienc_e_ you need a large amount of data for the results to be precise, so I collected data about restaurants in Pune through Zomato API’s, population data, pollution data, and keeping in mind the current situation, I even used the geospatial data of COVID-19 cases, from various available sources.

But the COVID-19 data was of not that use as the number of cases and containment zones change every day. So whatever area the Restaurant is in, precautions should be taken.

#data-visualization #restaurant #machine-learning #analytics #data-science