Abstract
One of the challenges governments and communities face to achieve smart city goals is dealing with enormous amount of data available - sensors, devices, social media, Web activities and commerce, tracking devices, all generate enormous amount of data, so called Big Data. Our goal is to empower the city government and its citizens to create a safer city by enabling crime and risk analysis of unstructured crime reports, criminal history of suspects, auto-license data, location-specific data, etc. for crime fighting efforts. We present intelligent solutions for Data-based Smart City Platform in Newark, NJ. We used a Machine Learning approach to automate and help crime analysts identify the connected entities and events by collecting, integrating and analyzing diverse data sources to generate alerts and predictions for new knowledge and insights that lead to better decision making and optimized actions.