The world is changing, and the pace of that change is accelerating exponentially. Traditional ways of detecting that change cannot keep pace. It used to take weeks or months to gather data, process it, analyze it, and put it into a map to communicate with decision-makers. This worked adequately, but it was never ideal. In today’s rapidly-changing world, it is insufficient.
Historically, to build a traditional 2D or 3D dataset we would gather data from airplanes or satellites and then process it to place it on the earth’s surface and create a mosaic of all our images. Once we had an accurate mosaicked image, we would digitize on top of the imagery and integrate it into the GIS, which was a series of layered data. We had hydrology layers, street layers, building footprints, infrastructure layers, and on and on. Each department would maintain their own data specific to their own mission, and we would be lucky if we could see information from other departments, much less use it in our own analysis.
If we could get access to elevation data, we could build 3D models. This could take days or weeks. We could visualize them and serve them out over the web. Once we performed our analysis, we could build a map and then distribute that to the stakeholders for their use. This process took weeks or months, and by the time we finished, the information we derived from the data was out of date. If anything changed, or when a new dataset became available, the whole process would start over. Rinse and repeat, ad nauseum.
Today’s world moves at a faster pace, and stakeholders expect more. We have gotten used to getting information in seconds and applying it instantly. In some ways, we are spoiled by this unprecedented situational awareness, even with its challenges.
There is an ever-increasing number of sensors, distributed across our cityscapes, all collecting and sending data to the Internet. We get traffic data, air quality data, noise pollution data, etc., all of which can provide powerful insight into the state of the real world in that instant. But tracking these, especially if they are themselves in motion – such as in autonomous cars or transponders in aircraft – is especially difficult.
It can be done, especially with latest visualization and integration technology. Today, we can build a true 4D GIS system. In this integration, however, we still have only a time-stamped picture of the world. What businesses and governments need is the ability to perform analytics on top of that 4D data – to build a 5D information service. This service doesn’t deliver simply data or even software, but answers-as-a-service.
This is what we are striving to create with the breadth of Hexagon technology. That’s the power of dynamic information: it provides true situational awareness. It is not simply data, nor just information, but a stream of analysis about the real world, coming to you live.