Browse Exhibits (2 total)
In the past decade, city developers have begun using data analytics to help recognize and respond to many of the problems faced in urban life. The principle of responsive neighborhood creation is a key factor in smart city development. Implementation of a digital city plan for smart cities should include resources about the Internet of Things, cloud computing, machine learning, sensor networks, and security infrastructure. This will help improve the responsiveness of civic engagement and governance in the digital age by linking important advancements in technology and data analytics with lessons about small-group communities. Understanding how to implement these technologies will produce more competitive, agile, and economically resilient cities. Several case studies highlight the benefits of these concepts in cities such as New York, Boston, Chicago and more. Expert utilization of these systems have proven to help mayors, chief technology officers, city administrators, investors, and nonprofit leaders address civic problems and security concerns that are related by inner-city limitations.
Chicago is creating algorithms from their collection of phone call complaints and social media postings over 12 years of time. They used this data to create and algorithm to predict a rat infestation 7 days before someone would see a rat. Data engineers save every tweet and Facebook post geocoded in Chicago. This info that is taken is organized as crime or sanitation complaints to look over and deal with later hoping they will be able to address all of them.