Optimizing Municipal Infrastructure with Smart City Planning
There’s a lot of buzz in the technology world about Smart City Planning. A Smart City collects and analyzes the data it produces to make improvements in areas like accessibility, sustainability, and walkability. During the pandemic countries like Singapore, Korea, and Taiwan used Smart City techniques to keep track of and contain Covid-19 infections.
The Smart City market is forecast to become a trillion-dollar industry, and many private companies are jumping in to create technologies to make cities more livable for residents. However, ethical concerns have arisen about private corporate control of cities' public data. Luckily people like Dr. Xuesong Zhou are working on open source projects, creating transparent alternatives that give the power to make data-driven decisions back into the hands of the community. Given that millions of people are moving to cities every week, efficiency has become an essential priority.
The Vision of a Communal Tool
Dr. Xuesong Zhou is an Associate Professor of Civil Engineering at Arizona State University specializing in dynamic traffic assignment, traffic estimation and prediction, and large scale routing and rail scheduling. He’s also passionate about the democratization of urban planning. He saw the potential of OpenStreetMap, an open source alternative to Google Maps, but knew it needed better functionality if it were to compete as a city planning tool. The Smart City Planning project was born.
The data packages built by Dr. Zhou and his partners extract the OpenStreetMaps data and add layers to make it more usable. To date, it’s been downloaded over 16,000 times from Github and is being used by universities and departments of transportation across the nation, including by Cambridge Systematics Inc. in the modeling system developed for Northern Virginia Transportation Authority’s TransAction Program.
The Bridge Between Data and Community
For Dr. Zhou, the various problems affecting cities (traffic, pollution, accessibility) are related and solvable with data. By bringing together academics, community leaders, and non-profit organizations, he hopes to develop an open data source that will serve as the framework for running simulations and informing data-driven infrastructure decisions. Dr. Zhou has also been an avid participant in DemocracyLab’s hackathons, where volunteers updated the data package versions with additional data layers, such as traffic light timing.
That vision is already beginning to manifest. Through a program sponsored by Arizona State University, high school students have been able to contribute to Dr. Zhou’s project. Earlier this year, Xenia Zhao worked with Dr. Zhou to research food bank optimization in her local city and her paper won first place in the Arizona Science and Engineering Fair. The high school student currently working with Dr. Zhou, Rachel Dai, is using the Smart City data package combined with US census data to understand how to optimize accessibility for vulnerable and elderly populations
The Future of Smart City Planning
The long-term goal of the project is to build digital “twin cities” that mirror the physical space and infrastructure of a metropolitan area. Users will be able to easily run real-time simulations that model a city's utilities, transportation, physical infrastructure, civic services, and more. By building digital twins that are accessible and easy to use, the project enables community-supported city planning. Dr. Zhou hopes to continue partnering with high school and college students who are passionate about social change and who want to work on creative ways to use technology to improve their cities.
How to get Involved
The Smart City Planning project is currently looking for anyone familiar with OpenStreetMaps software or knowledge of Python, especially high school or college students interested in sharpening their skills with hands-on experience. Check out the project page on DemocracyLab and sign up to get started!