CONSIDERING that the traffic problem in Metro Manila is caused by multiple reasons, common sense would dictate to us that the problem would also require multiple solutions. Admittedly, the problem is caused by density and volume, but quite obviously, the problem is also caused by the supply and demand of time and space.
It is understandable that many people in the government agencies would not yet be able to fully understand what Big Data is and what it could do, considering that the concept is still fairly new in the realm of human experience.
While some traffic managers would tend to immediately resort to obvious tools such as printed flat paper maps, they should sooner or later realize that digital maps that are derived from databases are more accurate and thus more reliable.
In much the same way that flat paper maps are probably just printouts of electronic images, the digital maps are actually just derivatives of databases that are really nothing more than receptacles of input data.
Big Data by itself is useless without data analytics, and perhaps it is for that reason why some experts are now combining these two separate terms into Big Data Analytics, now being used as a collective term.
To fully understand this collective term, however, we must first understand what the basic term Big Data means, how it is collected and what it is supposed to do.
Although Big Data could be built or formed out of pre-existing data collections, the proper thing to do is to develop a strategic plan that would enable organizations to purposely collect new data sets for a predetermined purpose. In a manner of speaking, it could be said that Big Data is only a means to an end, because the means should really be influenced by the ends or the outcomes.
At the risk of stating the obvious, the basic purpose of building or forming Big Data is to have the raw materials to analyze, hence data analytics. The interaction should not end there however, because it should also be understood that Big Data could not be built or formed without the Internet of Things (IOT), without social media and without mobile commerce that would of course involve the use of smartphones.
As a matter of fact, many experts are actually saying that smartphones represent the first generation of IOT devices. By the way, I am using the term mobile commerce liberally here, to mean anything and everything that involves the use of smartphones.
Just as Big Data would be useless without data analytics, Big Data would also be useless without the internet cloud because that is where Big Data goes, analyzed or not. Going back now to the subject at hand, we could now say that the combined use of Big Data, IOT, social media, mobile commerce and the internet cloud would enable the government to plan and manage the flow of traffic in a way that is completely data-driven, and not just through the use of guesswork and analogue tools.
Without using this coterie of tools, it is difficult to imagine how any traffic manager could factor in density, volume, supply and demand into his or her planning and decision making.
Without going into details, we already know that service providers such as Waze, Grab and Uber are already using this coterie of tools, plus some amount of Geographic Information Systems (GIS) and Global Positioning Systems (GPS) of course, perhaps with the supplemental use of drones, balloons and satellite dishes. Somewhere in between, they could also be using Google Maps and Google Street View.
All of these assets are also accessible by the government, such that it could also do what the service providers are now doing. Aside from that the government has additional access to other assets such as those that are in the possession of the National Mapping and Resource Information Authority (NAMRIA) and Housing and Land Use Regulatory Board (HLURB).
Over and above the coterie of tools, there are other technologies that could be used by the government for purposes of data driven traffic management. Among these are Artificial Intelligence (AI), Augmented Reality (AR), supercomputer simulations, facial recognition and even fuzzy logic.
Some might say that these other technologies might be too expensive, but for sure, the funds invested into these could easily be recovered, considering that the cost of heavy traffic flows in Metro Manila could run into billions of pesos every day. That is not counting the opportunity costs that are incurred, plus the productivity that is lost while wasting time in the traffic jams./PN
