Today, the number of smartphones in use has increased the number of sensors that are in play. From accelerometers to GPS sensors to proximity detectors, smartphones are loaded with various sensors that automate different functionalities. Owing to these arrays of smart peripherals, location intelligence serves as one of the quintessential pieces of information for disparate operations. Using the GPS sensor, most of the location-based services are pre-configured through cloud applications. Consider Google Services for example. Right from the initial stages of providing relevant news articles at the start of the day, Google’s search engine optimizes routes, provides ambient and adaptive functionalities, relevant ads, and preferential data. These analytics pave the way for various types of monetized services that not only increase user experience but also provide a platform for third-party services to cater to the appropriate user demographic.
Similarly, big data aids the development of such cross-platform services by delivering business analytics and actionable insights as per the historical data collected from various sensors. An example of such actionable insights can be seen in the android platform where the operating system allows users to pre-configure profiles that trigger actions at a particular location. When an employee sets a specific destination as ‘work’ or ‘office’, the android OS automatically sets the smartphone on silent mode when that person reaches his workplace. With the use of big data, such actionable insights can be leveraged to provide users with relevant information and statistics as and when a particular action is performed.