Understanding the power of real-time geospatial analytics
I live in Bangalore which is also nicknamed the Silicon Valley of India due to the establishment and success of high technology firms. The city has seen a huge transformation from a Garden City to a IT hub with a disproportionate economic growth rate due to the advent of Information Technology (henceforth IT) companies. The development provided lucrative job opportunities leading to an increase in the number of car ownership, shopping malls and restaurants. But that also led to rapid growth in population as more number of people started coming to the city in search of jobs, which resulted in heavy traffic and choked roads. If there is a common factor that binds Bangaloreans, it is complaining about traffic, no matter which part of the city they hail from. Over the last nine years, there has been a significant decline in the average speed of the vehicle from 35 kmph to 9.2 kmph.
Poor traffic conditions, lack of public transport and less number of parking spaces has led to the exponential growth for on-demand taxi aggregators, food and grocery delivery startups in the city. The rise in taxi and food aggregators has facilitated the methodical collection of location-based data, which they aim to use not only to leverage business capabilities but also for public good. Location data is the core of their business model, it collects a million data points every minute through mobile and GPS devices fitted on vehicles attached to the company. Awareness of the location of on-the-move devices such as smartphones and connected vehicles opens up exciting new application opportunities. Support for these new applications requires highly scalable services that can analyze high volumes of data in real time.
Monitor mobile devices with the Geospatial Analytics service
With the Geospatial Analytics service in IBM Bluemix, you can monitor moving devices from the Internet of Things. The service tracks device locations in real time with respect to one or more geographic regions. Geospatial analytics can be used as a building block in applications that support several use cases. For example, a retail business might want to monitor for potential customers nearby its stores and send them promotions via push notifications or tweets. Geospatial analytics could also be used to detect connected motorists entering areas that they might want to avoid due to an accident, weather conditions, or other temporal event.
In addition to monitoring device movement there are a series of REST APIs that allow you to control the service state (starting, stopping, etc.) as well as manage defined geographic regions known as geofences. For each monitored device, a unique identifier along with its current position, comprising latitude and longitude, is passed to the service where the position is checked against the coordinates of the managed geofences. A trigger or region hit can be generated based on devices both entering and exiting a geofence. Below is a simple example of a person entering and exiting a hexagon that defines a geofence.