Connected and predictive cities will transform city living, says IBM Fellow Bernie Meyerson
People who live in cities are starting to get a lot more information to help plan their daily lives. Smarter City systems are telling residents about traffic congestion, the time the next bus will arrive, the potential for flooding on a block-by-block basis, and a host of other useful updates. The same wealth of data enables city service leaders to proactively send crews out to mitigate future damage, such as going out to replace water lines before small leaks become catastrophic sinkholes.
This is happening because cities are harnessing the streams of information from sensors to manage municipal systems better. Cities are complex systems of systems that have always generated vast amounts of information. Information flowing in from many small subsystems, such as local flood catch-basins, is integrated with other sources to provide guidance on the overall operation of a city's storm sewer system. This integrated data, from such systems of systems, is then given to city administrators in useful formats that can transform city living for the better.
The need for cities to maximise the efficient use of infrastructure and help residents be more productive without spending vast sums on new facilities is driving this process. The more efficient use of data and predictive analytics promises to help accomplish that goal.
In some cases, cities have moved well beyond just monitoring events in real time. They have begun to accurately predict future events likely to cause damage, and take action to avoid it. Predicting and altering the future may sound like science fiction, but it is here today and represents the future for urban management.
This feat begins with gathering as much data as possible on the issues that need to be addressed. Using the "internet of things", sensors embedded in a wide array of systems serving the public (traffic signals, buses, trains, parking spaces, water systems) report the status of the system they are monitoring via the Internet.
The number of devices such as these exceeded the number of people on the internet in 2008, and will reach 50bn in 2020, according to an article in the 8th November issue of the Journal of Sensor and Actuator Networks. Cities now gather the critical data required to build the models and predictive abilities to understand and alter the future for the better.
All these devices can constantly send information to central command posts where digital streams of data can be analysed and used to alert emergency responders or divert traffic in case of trouble.
Sensors that instantly detect a broken down subway car on a busy track can give repair crews valuable extra minutes of work time to correct matters. However, a true game-changer is the use of sensors to show that a bearing on a train car is running warmer than usual, allowing analytics software to alert maintenance workers and eliminate an impending problem long before a dangerous failure occurs.
IBM, has been using predictive analytics to help cities function better for almost a decade. For example, we have helped city police in Richmond, Virginia deploy their forces to predicted trouble spots and avert crimes. We have helped schools in Mobile, Alabama identify potential dropouts and target them for additional remediation.
In Rio de Janeiro, the city has built a sophisticated central command center in preparation for the World Cup in 2014, and Rio's mayor is counting on advanced analytics to monitor the deluge of data coming in from the region and spot problems long before any one individual could.
Rio currently employs sophisticated weather prediction systems capable of forecasting weather for areas as small as one square kilometer to alert city officials to the potential for heavy rainfall to cause highly localised mud slides in a specific neighborhood located on a steep mountain side. As the predictions are very precise, public safety officials can concentrate their safety teams at key locations, alerting residents to the potential danger and moving to evacuate them if deemed appropriate.
With super-cities of tens of millions of people now emerging, at a scale and complexity never before encountered, this ability to focus resources using deep understanding of the "big picture" becomes ever more critical. In 2010, for the first time in history, more people on the planet lived in cities than lived in rural areas. More importantly, in the next 20 years, some 2bn more people will move into cities, marking one of the most significant migrations in human history.
In some countries, India and China as examples, governments are building new cities to accommodate this transformation. However, on a worldwide basis, most migrants will move to existing cities where they may have personal relationships, prospects of a job, or some other incentive.
In those existing cities, the coming population growth will challenge even the most skilled city managers, and the legacy infrastructure of many such cities is not equipped with the ability to gather the data needed to guide city operations. Despite the seeming lack of data gathering infrastructure, another option exists given the shift from desktop computing to mobile devices and tablets.
Mobile technology has advanced dramatically in the past decade to the point where a lightweight smartphone may gather all manner of data, such as its location, velocity, local temperature and background noise levels. Furthermore, in the near future, additional capabilities are easily envisioned, where sensors could be embedded to detect both particulate and chemical pollution, local lighting conditions, vibration levels, and more.
This will enable a new era of participatory engagement by a city's population, where the very data required to optimise city operations is in part willingly provided by its citizens via smartphone apps.
It also raises complex societal issues that must be addressed as we face this new era, but similarly provides an unprecedented opportunity for the citizenry of a community to take an active role in the betterment of their community, not only in the reporting of critical environmental and transportation data, but in taking an active role in mitigating the very challenges their own data identifies.
It will be a cooperative and informed effort, with information technology enabling societal transformation, to address the growing challenges facing our cities in the coming decades.
Bernie Meyerson is an IBM fellow and vice president for innovation
