We are all keenly aware that today’s world is in a state of great transition. Not only is technology advancing at an ever-increasing rate but our physical world is changing as well. The people living in our cities are becoming more diverse, fashions change, and are very weather is changing due to global climate change. In order to respond to these changes, it is necessary to have comprehensive and reliable forms of data collection and analysis. For instance, at this juncture, many of our buildings, especially in historic cities, were simply not constructed with modern needs in mind. Concerns regarding global climate change and rising energy costs now shape the current building and renovation trends. This requires information and data on current buildings that need to be upgraded, the kinds of problems that these upgrades will have to address, and other structures that are already successful.
It is even more important than ever to all industries to demonstrate flexibility and be able to adapt quickly. However, it is not enough only to recognize the need to adapt and it is not always immediately clear how to act efficiently.
This is where Nam.R comes in.
Nam. R. aims to make this easier through their interactive data library. Through the customization of their data packages, researchers of a wide variety of industries can use both their time and resources more efficiently. For instance, to use the example of energy efficiency, in real space, you are able to look at buildings and pull up information about them with the click of a mouse. Information like materials used, slope, window orientation, and much more allow the user to easily conduct research and make informed decisions regarding energy efficient upgrades. The 3D maps generated by Nam.R allow the user to experience the data in an intuitive way; visualizing the data through the space in which they actually exist.
Nam.R uses open data sources and extracts the relevant data through the use of artificial intelligence and machine learning. They use open data, or data that is freely available for public use, but go beyond simply collecting it. Their programs then interpret the information and compile and organize it so that it can actually be made usable. To again use the example of energy efficient construction, Nam.R’s programs scour public aerial and satellite images then recognize objects such as buildings, foliage, and automobiles. They are then trained to use these combinations of data sources to generate and compile the data of interest. Through their use of algorithms that are adaptable and able to interpret the data themselves from new and variable sources, Nam.R is able to compile their data from any number of information sources and quickly make it available to for use as their own databases are updated.
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