Direction « the Location Intelligence » can not be called new or innovative. The technology appeared on the Gartner Hype Cycle of Emerging Technologies curve back in 2013. Its older relatives, BI and geographic information systems (GIS), have also been widely used for decades. In the military-industrial complex, LI technologies were actively used even earlier.
At the same time, the demand and scope of LI are growing with each enviable dynamics. Today's big data and artificial intelligence conferences rarely go without talks about geoanalytics, geofencing, geolocation marketing, and other technologies that start with geo.
Companies enthusiastically share their successful experience in determining the optimal location of points of sale, sending notifications to customers who are near a certain location, ingenious planning of premises inside stores taking into account knowledge of customer behavior (yes, our behavior with you is an object of serious research), talk about the results analysis of sales by geolocation based on receipts, solving logistics and other tasks aimed at increasing the effectiveness of advertising and improving the customer experience. Real estate funds even more actively reflect on the topics of real estate valuation and best-use asset analysis , taking into account the current capabilities of Data Science and Machine Learning (hereinafter - ML).
The marketing pursuit of our wallets is just one small example of the use of LI.
Over the past 7-10 years, the effectiveness of LI has increased significantly due to three main reasons:
growth in the number of data sources . The volume of data generated daily in the world with reference to a geographic location is amazing and confidently allows us to call them BIG DATA (BIG GEO DATA or BIG SPATIAL DATA, one clear definition, as usual, has not yet been found), and work with them in all severe Data Science laws. These are sensors and IoT sensors, "smart cities" and "smart homes", cars, mobile devices with built-in GPS receivers, online cash registers, social networks, payment systems, data from video cameras and others.
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* This article reflects the application and development of LI in the civilian sector of industry, although, like for many other technologies, the main drivers for the development of this concept is the solution of the problems of the military-industrial sector. The tasks of the military, which are solved using LI (from open sources, of course), will be reflected in other reviews.