Wu, Ka WaiSung, Pei-HsuanLin, Kuan-FuMarrero, AlexanderKanakamedala, Venkata Chaitanya2025-01-232025-01-232024-12-11CS 5934https://hdl.handle.net/10919/124325Brief overview: The D.C. Crime Insights Application can be used to analyze valuable data regarding D.C. crime statistics. The application has multiple different pages that serve different functions. Features in the Web Application: - Dashboard: Provides high-level information such as general statistics over the past 30 days, past 12 months, and Crime Trends over the past few years using a variety of different graphs to display information in a clean and concise format. - CrimeMap: This page can be used to display crimes across D.C. and can filter crimes by the crime type, crime zone, and date range over the past 30 days. - Reports: This page can take dates from a specified range, as well as a neighborhood cluster to generate a report of information regarding various data for the users on the webpage. - Crime Prediction: This page contains two sections. The Linear Regression Graph tab contains a linear regression graph that can be used to help predict the number of crimes that will occur for a specific method in D.C. over the coming weeks. The Advanced Predictions tab can be used to predict the number of crimes over a certain timeframe for a specified region. Both of these tools are very valuable for helping users predict future crime trends. - Safe Routing: This page takes start and destination locations and generates a safe route for the user to take by leveraging past crime data. - Public Safety Resources: The page provides various resources users can look at to help report crimes or keep them safe. - Settings: This page can be used to change the colors in the sidebar to help make the application look nicer. Features Working in the Background for the Web Application: - Live Database Hosted Using AWS: The database is currently hosted on Amazon RDS. All calls used to gather data in the application pull data from the tables hosted in the live database. - Database Autoscheduler: This uses Amazon Lambda and Amazon EventBridge to automatically schedule updates to the database to add new crimes. The code used is in the backend section of the database but does not work if you try to run the Python file since the code is built to be run using Amazon Lambda. Data: Data used for the project can be found using the following link: https://crimecards.dc.gov/ Create your filter at the top for the data you want and then press the download data link underneath it Link to the GitLab repository: https://code.vt.edu/sungpeihsuan/crime-report-web-application Link to our project demo: https://www.youtube.com/watch?v=YEhgr6ytN5U Developed by: Alex Marrero, Ka Wai Wu, Kuan-Fu Lin, Pei-Hsuan Sung (Patty), Venkata Chaitanya Kanakamedala Guided by: Soheil SibdariThe D.C. Crime Insights application is an advanced web-based platform designed to analyze, visualize, and predict crime data in the D.C. area. Its goal is to offer users intuitive, data-driven tools, including an AI-powered chatbot, crime prediction analytics, safe routing, crime mapping, comprehensive graphs, and a report generation feature. The application uses data from an Amazon RDS database, updated daily using an auto-scheduler powered by AWS EventBridge and AWS Lambda. By combining advanced analytics with interactive visualizations, the platform allows users to explore a variety of crime metrics and gain valuable insights into crime patterns and trends.enCreative Commons Attribution-NonCommercial 4.0 InternationalD.C.Data VisualizationMachine LearningSoftware EngineeringWeb ApplicationDatabaseAIPredictive AnalyticsCrime DataCrime MappingCrime AnalyticsAWS ToolsTechnical report