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Introducing SousZen

See how Xinova partners with PepsiCo and Innit to launch the new Seattle restaurant tech startup, SousZen, that aims to digitize ‘back of house’.

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The IRI conference attracts Leaders in Innovation from all over the globe to talk about everything R&D. While these companies span a wide variety of industries, many innovators were seeking solutions to similar problems. Karen Lightman, Executive Director of Metro21 shares how centralizing public data can lead to solving real-world problems. 

We really care about that intersection of technology and humanity,”  -Karen Lightman, executive director, Metro21, Carnegie Mellon University

Realizing that technology is designed to serve a purpose for humans, Lightman’s Metro21 group is charged to solve problems with air quality, climate change, water, waste, transportation, mobility, infrastructure, and city operations–all areas where technology has the potential to be used as a tool to deliver an exponential human benefit.

Figuring this out is never easy. “The path to connecting technology to a solution is not straight,” said Lightman. And when you’re dealing with technology solutions for governments and the public, it is only so far that they can see into the problem. “A municipality often doesn’t understand the problem they have. They understand the impact,” explained Lightman. 

As Xinova works on a Smart Cities project of their own, Project CitizenOS, Xinova CEO Edward Jung comments “Thousands of cities around the world need innovative solutions for information technology deployments to help their citizens live healthy, happy and productive lives using socially-conscious and equitable systems that respect privacy and the role of government policy.” 

The keystone to solving many community problems is easily accessible and open digitized data. One example of a problem they’ve been able to manage through public data is building inspections. For example, in the city of Pittsburgh, there are 20,000 buildings and only six inspectors have only five years to inspect all those buildings. Data about these buildings, such as 311 and 911 calls, are very valuable to inspectors, but they’re strewn about on a laptop, a spreadsheet, or a piece of paper. By getting all that data digitized, centralized, and open, the Metro21 group was able to create a predictive model to determine the likelihood of a fire in a building with 85% accuracy. Now, that they have some knowledge of risk factors of each building, they can prioritize which buildings to inspect first.

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