We Predict Human Behavior in Cities

Case Study 1

City Government


So much city data. So many possibilities.



The Challenge

City governments collect an incredible amount of spatial data: the public health department knows where health emergencies occur, there are sensor data and data about other events such as 311 calls. However, cities do not have the tools nor the resources to effectively leverage this information and solve future problems. 

The Solution

Zoba brings together thousands of variables that show how a city works as a system. These data are both spatial and temporal in nature and allow us to look at historical events in the context in which they occurred. 

The combination of our data and algorithms with a government's spatial data allows that government to make predictions that drive critical planning and operations.

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The ability to anticipate when and where events will happen allows governments to front-load resources, making for more proactive governance, happier citizens, and safer cities.

For example, governments can anticipate how to staff one fire station vs. another, saving money and better protecting citizens. They can also anticipate distribution of 311 calls, forward-placing resources and decreasing time to service.