Using Analytics to Detect Blight and Enforce Codes in Cities
Blight and code enforcement monitoring is a major expense for cities. The current monitoring process depends on community reporting via systems such as 311 or through code enforcement officers physically driving through neighborhoods. This process is reactive and by the time a property is identified it is often extensively blighted leading to high remediation costs. In addition, enforcement officers must perform several return trips to monitor the progress of remediation. Our process of automated code enforcement and blight detection is proactive and frees up code enforcement resources to focus on remediation. High quality and high frequency monitoring allows us to detect nuisance properties before they reach a ‘tipping point’, provides code enforcement officers with specific and universally defined code violations to help alleviate perceptions of bias, and helps cities prioritize remediation.
Dr. Erik Johnson is an Assistant Professor of Economics in the Culverhouse College of Business at the University of Alabama. He has a Ph.D. in Economics from the University of Colorado-Boulder and current affiliations with the Alabama Transportation Institute and the University of Alabama Institute for Data Analytics. His academic specializations include urban and rural economics, public finance, and machine learning.
Dr. Johnson is also the CEO of several smart city tech startups that make use of artificial intelligence and machine learning (AI/ML) techniques
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