{"title":"Studying the impact of streetlights on street crime rate using geo-statistics","authors":"Srikanth Vadlamani, M. Hashemi","doi":"10.1109/IRI49571.2020.00040","DOIUrl":null,"url":null,"abstract":"Lack of adequate streetlights likely affect public safety, particularly in neighborhoods with higher crime rates. Several researchers have studied the influence of streetlights on crime. However, those studies compare the crime rate during the day and not night or explore crime patterns in socially disorganized communities. This study focuses on detecting the pattern of nighttime street crime near a broken or due-for-repair streetlights. Historical crime data and data on city streetlight service requests studied in this project. Analytical approaches for this projects include the least squares linear regression model applied to determine the relationship between streetlight and crime data and Ripley’s K function is used to detect crime clusters near broken streetlights. The Moran’s I index is used to measuring the spatial correlation between broken streetlights and crime rates. Optimized hotspot analysis is used to predict crime locations. This study found that broken streetlights cause increasing trends of crime near them The Moran’s I index’s large positive value underscored the statistically-significant clustering of street crimes around broken streetlights","PeriodicalId":93159,"journal":{"name":"2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science : IRI 2020 : proceedings : virtual conference, 11-13 August 2020. IEEE International Conference on Information Reuse and Integration (21st : 2...","volume":"42 1","pages":"231-236"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science : IRI 2020 : proceedings : virtual conference, 11-13 August 2020. IEEE International Conference on Information Reuse and Integration (21st : 2...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRI49571.2020.00040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Lack of adequate streetlights likely affect public safety, particularly in neighborhoods with higher crime rates. Several researchers have studied the influence of streetlights on crime. However, those studies compare the crime rate during the day and not night or explore crime patterns in socially disorganized communities. This study focuses on detecting the pattern of nighttime street crime near a broken or due-for-repair streetlights. Historical crime data and data on city streetlight service requests studied in this project. Analytical approaches for this projects include the least squares linear regression model applied to determine the relationship between streetlight and crime data and Ripley’s K function is used to detect crime clusters near broken streetlights. The Moran’s I index is used to measuring the spatial correlation between broken streetlights and crime rates. Optimized hotspot analysis is used to predict crime locations. This study found that broken streetlights cause increasing trends of crime near them The Moran’s I index’s large positive value underscored the statistically-significant clustering of street crimes around broken streetlights