Sense Networks uses anonymous location data for nightlife discovery

16 Jun 2008

The U.S. start-up Sense Networks launched last week an application for its software platform Macrosense, which analyzes historic and real time location data from mobile devices. The alpha-version of the program called Citysense is supposed to be a "real-time social navigation and nightlife discovery application" for San Francisco.

After collecting massive amounts of anonymous location data emitted from mobile phones and automobiles Macrosense leverages machine learning technology to analyze each new data point in the context of billions of historic location data points. The platform allows companies and investors to quantify aggregate consumer behavior and to detect macro trends in spending and sentiment in real-time.
Chief Scientist, co-founder of Sense Networks, and Director of the Machine Learning Laboratory at Columbia University, Tony Jebara compares the technology behind Citysense to Google indexing pages on the Internet to optimize web discovery: "Sense Networks has indexed the real places in a city and characterized them by activity, versus proximity or demographics, to better understand the context of consumers' offline behavior."
Because of showing nightlife hotspots in real-time, the Citysense alpha release allows users to identify the busiest places, with another option to only view spots with unusually high activity based on years of historic data.
According to Sandy Pentland, Chief Privacy Officer, co-founder of Sense Networks, and Director of Human Dynamics Research at MIT, Citysense demonstrates the power of combining anonymous, aggregate location data for social navigation.
At the moment Citysense can only be downloaded on BlackBerry phones; an iPhone version is announced for July 11.