With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …

Deep learning has exploded in the public consciousness, primarily as predictive and
analytical products suffuse our world, in the form of numerous human-centered smart-world …

Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

Crime and violation are the threat to justice and meant to be controlled. Accurate crime
prediction and future forecasting trends can assist to enhance metropolitan safety …

There are widespread concerns about the use of artificial intelligence in law enforcement.
Predictive policing and risk assessment are salient examples. Worries include the accuracy …

A crime is a deliberate act that can cause physical or psychological harm, as well as
property damage or loss, and can lead to punishment by a state or other authority according …

Predicting crime using machine learning and deep learning techniques has gained
considerable attention from researchers in recent years, focusing on identifying patterns and …

The security of a community is its topmost priority; hence, governments must take proper
actions to reduce the crime rate. Consequently, the application of artificial intelligence (AI) in …

Machine learning is useful for grid-based crime prediction. Many previous studies have
examined factors including time, space, and type of crime, but the geographic characteristics …

This article examines the impact of new AI‐related technologies in data mining and big data
on important research questions in crime analytics. Because the field is so broad, the review …