As Foursquare adds more than 30,000 users per day and is close to pass the 10-Million users, we can safely say that location-based applications have crossed the chasm and have gone mainstream. It was a matter of time: mobile networks now can deliver (mostly) reliable data communication; the smart phone industry has consolidated around a few solid and rich platforms – iPhone and Android; business models that foster bottom-up innovation have replaced top-down service design.

Not that disclosing location information is new or has not been done in massive amounts for a long time already. We do it all the time whenever we use a mobile phone, an internet connection, swipe a credit card, or cross the field of view of a safety camera. While in Foursquare, Facebook, Twitter and many others we deliberately disclose information, a variety of other services simply need to capture that information to be able to provide us with communication, transportation, security and a plethora of other essential services which make up our modern lives. Deliberately or not, we leave behind every day dozens of clues about our location, spread over a variety of digital system and organizations.

Now enter the Internet of Things. There are about 2 billion users connected to the Internet in 2010: estimates are that about 50 billion connections will be active by 2020, mostly non-humans (vehicles, buildings, streets, body sensors, etc.). If we are already disclosing location and personal information continuously, there will be many many more opportunities to capture data and information that directly or indirectly says something about us, where we are, how we move, what we like. All this will generate data on a scale that we can hardly conceive yet.

Taken individually, all this information will enable a wealth of targeted experiences and services. Some will be consumer oriented; many will be of business importance and affect public services and private enterprises.

But what about our collective behavior? If all these traces say something about us as individuals, what do they tell us about our collective use of, say, cities or transportation systems? A few years back, when TV was a relevant media and choice was limited, media executives joked that the best way to detect when TV commercials were aired was to monitor simultaneous spikes of electricity, telephone and water consumption (open the fridge, make a call, use the toilet). Aggregated and anonymous digital breadcrumbs of individual behavior can provide fascinating clues about how we move, aggregate and act as societies or tribes. Call it Collective Sensing: the ability to understand collective behavior based on digital anonymous clues. Web 2.0 and the upcoming Internet of Things provide the mass of data that makes Collective Sensing a reality.

There are many good reasons to explore Collective Sensing. Police and safety organizations struggle to anticipate unsafe crowd concentrations or behaviors and in many cases seem incapable of avoiding the worst-case scenario. Tourism agencies have scattered evidence of where tourists come from, which sites they visit most and which ones they neglect, how they make choices and move in cities. Without such evidence investments in promotion, valorization and protection of historical heritage or natural wonders may well be of little impact. Cities struggle to reduce CO2 footprints, create more environmental friendly living, regenerate neglected urban areas and design better mobility systems. How can they invest wisely if they are unable to measure the impacts of policies as they unfold?

Hundredths of questions like these explain the interest for exploiting the mass of data continuously generated by telecoms, social networks, vehicles or buildings, in a new and intelligent way.

Early examples, such as modeling of tourism flows through Flickr public pictures, emphasize visualization and info-graphics as ways of exploring patterns and hidden data content. Research carried out at the Senseable City lab of MIT – one of the pioneers in the field – provides hints of business utilization, opening up a city platform for application development while exploring a city in real-time. Applications devised by Currentcity, an applied R&D organization, illustrate the potential of telecom traces combined with other data sources to detect city anomalies, measure people presence or tourism flows. Examples include early detection of the closure of the Amsterdam Airport due to the Volcanic cloud in April 2010; or the ability to measure how many people are present in near real-time during large events; or the ability to predict propensity of tourists for short trips from their main destination.

All this may still be at an early stage: R&D is ongoing, technology is still developing, business models have to be worked out, users have to become aware of the potential. However, it is only a matter of fact that Collective Sensing can answer fundamental questions in a way that no other methods can, and can shed light on social phenomena in ways that were simply unconceivable until now. It is only a matter of time before we will see Collective Sensing reach mainstream and become part of our daily vocabulary.

Originally published at NEXT Word!

About the author
Euro Beinat holds an MSc in Computer Science and Systems Engineering and a PhD in Economics. He has 20 years of experience in management, consulting and R&D. At present he is Professor of “Geoinformatics, Location and Context Awareness” at Salzburg University (Austria) and Chairman of the Currentcity foundation (Amsterdam, Netherlands). His business affiliation is with Zebra Technologies Corporation (Chicago, US), as Vice President Location Solutions. His home base is Amsterdam, Netherlands.

As Academic, Euro is part of the leadership team of the Geoinformatics PhD School in Salzburg and oversees research on the Internet of Things, Collective Sensing and Sensor Analytics. As responsible for Location Solutions at Zebra Technologies, he designs the global strategies for Location and Context aware solutions, in particular for the process industry.

He coined the term “Collective Sensing” for describing the growing science and practice of measuring and predicting the dynamics of large complex systems, such as cities, based on aggregating anonymous digital breadcrumbs continuously left by all of us during daily personal or business activities.

Keen to find out more? Check out Euro’s talk at NEXT11: