"Smile, you are on camera!" is a pretty common sign in some areas like taxi cabs and retail stores.  The idea is to alert customers that their activities are being monitored.  These signs are not always required, as it is often quite apparent that there is a big camera aimed right at you.  For most of us, being "watched" on a CCTV camera is just a part of normal life in a big city.  However, this is nothing compared to how activity is being watched in other areas...

Big Data is changing many parts of our lives. One of the biggest areas being how municipalities are gathering information about the city through the use of advanced sensors.....and you may be surprised by all of the ways that they are doing it.

Here are some examples:

  1. A large development in New York is using sensors to provide information on a very broad spectrum of things....pedestrian flow, water usage, soil dampness of plants and even the heat of all light bulbs (to predict failures).  The idea is to reduce the environmental footprint by up to 50% over a standard development.
  2. Using data to monitor traffic flow is not new (all drivers have run over cables spread across the road that measure traffic for a long time), but the sheer amount of data (combined with the ability to crunch data at record speeds) is taking this to a new level.  In Lyon, IBM has developed a system that can do things such as automatic detours (based on congestion/accidents), change speed limits dynamically and modify on-ramp speeds....all based on real time data with decisions made in less than a second!
  3. By far the most controversial example is using Big Data to enhance the effectiveness of policing.  It has long been controversial for police to use tactics that stereotype people based on physical characteristics or race.  While this tactic may have had some good results, it ultimately was deemed to be discriminatory by most people's standard.  However, most are seeing the use of Big Data to predict crime to be less controversial.  Police use things such as lighting conditions, traffic patterns (both pedestrian and cars, especially those who loiter and differ from the usual patterns) and time of day to better predict areas that are more likely to see increased crime activity.  It has proven to be effective in a couple of Canada's larger cities, with significant reduction in crime rates.

Sounds great, what is the downside?

Like anything else, one has to worry about privacy.  Like many things that develop trends (ranging from car volume on highways to overall power consumption by home owners), the data tends to be grouped together, so it is not possible to gather data on an individual person.  As well, with most of our lives being on the Internet anyways (Reminder: post on FB about your leg cramp while running!), most of us have a decreased sense of what is actually private anyways.

As well, this data is being used to provide a better life for many of us.  When cities know the actual traffic patterns, they can provide more effective public transit and better roads.  As well, sensor data is invaluable for preventing major issues, reducing our environmental footprint and improving our overall safety.

Where the issues lie is that we need to keep a better eye on how this data is being used, and in fact, what is being gathered in the first place.  It is great to see cities sharing with the public what they are doing, why they are doing it and how it is helping....disclosure tends to reduce people's concerns somewhat.

The Bottom Line

Based on how I make a living, it is obviously in my best interest to see Big Data sensor data being further deployed.  However, like most people, we want to see it be done in a responsible manner – one that balances the benefits vs. the possible loss of privacy for all of us.