Location Analytics for Addressing Crime
Updated: Feb 3, 2022
There is a certain charm in solving a case involving crime - from detecting the incident and investigating the suspects to uncovering the motive and identifying the culprit. People of all ages tend to enjoy this methodical unraveling of mystery in their novels or on their screens. A majority of such content is fictional, however, what increases the thrill factor multi-fold is if the content is non-fiction or even just 'based on a true story'.
What if such a thriller is narrated by the protagonist in real life himself? Wouldn't that be doubly fascinating? If you have twenty minutes on your watch, you are likely to find this endearing tale recounted by IPS Amit Lodha below worthwhile.
All crimes, barring cyber, happen at a physical location. And anything which involves positional information can always be mapped, analysed and visualized - more effectively using technology.
For example, Location Analytics helps to identify historical crime patterns and make data-backed decisions about resource allocation. Consider this case - The map below depicts all recorded Crime locations and Police Station locations in a city with five districts over a period of time.
Using geo-processing tools we compute and identify which areas lie within rapid reach of the police stations. The pink shaded region in the map below is reachable within 5 minutes of driving time from the nearest police station (This computation takes into the account the existing road network and real time traffic can also be accommodated).
We figure that 922 out of the 1025 black spots i.e. crime locations are within the pink shaded region implying that the rapid response coverage is currently touching 90%.
Some of you may also observe that a significant portion of the city (area within the thick black boundary) do not have rapid response coverage notwithstanding that the crimes have not occurred there historically.
A density / heat map of the crime locations helps to better identify and visualize the underlying pattern -
Upon overlaying the coverage layer on the density layer in the map below we can easily identify the areas which need attention - The plain blue areas on the edges of the city should be prioritized with rapid response coverage.
If we were to take this case further, we can even shortlist the least number of police stations which could be set up so as to have the maximum coverage of the areas which need attention. Optimization and Network Modelling capabilities are included in Location Analytics platforms.
While we generalized all crimes under one bucket in the case above, in the real world, visualizing crimes by the degree of severity and conducting analysis thereafter would help in generating more meaningful findings.
Explore this interactive map based crime dashboard of a Central American country by clicking on the image below. This dashboard is dynamic in nature - it allows us to visualize the data from various perspectives in a real time basis - please use the various filters and navigation options present in the dashboard for experiencing it.
Just as in the image on your left, one can add video feeds to such map based dashboards - CCTV footage, Drone footage etc. which would enable enhanced virtual monitoring.
For decision makers within the law enforcement / fraud detection fields, location analytics can help in understanding historical developments, monitor real time operations as well as predict future scenarios.
From monitoring innocuous doctor prescriptions to unearthing a drug-trafficking ring, see how advanced location analytics helps unearth sophisticated crime from the video below.
The data processing was done using an advanced Location Analytics platform - ArcGIS Insights
IPS Amit Lodha, in the video at the beginning of this article, mentions extensively how he used cell phone locations to nab the gangster. In his case, he knew the gangsters' phone numbers. What if you don't and have to sift through plenty of records to detect patterns and identify suspects?
Location Analytics platforms are robust - they can handle millions of data points just like in the image below which contains 1.28 million cellular records of nearly 2.5 thousand mobile phone users over a period of 45 days.
In the map below, we have marked 3 areas (shaded in purple) where we understand the crime syndicate is operating from and our job, among other things, is to identify suspects who have visited all the 3 regions in this 45 day time frame.
While the location analytics platform can handle vast amounts of data, you may wonder that it would still be a mammoth, time consuming challenge for us to unearth patterns sifting through this quagmire. Not to worry - there are unique ways to filter out less important data and/or highlight the crucial aspects.
So, in this case, charts such as the one below can highlight visitors who have traveled to two or more locations only -
We can choose to focus on only a few high potential suspects by filtering the data as indicated in the visual on your left and below
And most importantly, we can sift through data in time i.e. analyse movement spatio-temporally.
Just as positional data adds the new dimension of 'location' in the data and enables us to perform meaningful analytics on it - adding time as another dimension to the positional data and performing visual analytics on it is even more powerful.
Because Location Analytics for Crime is a niche field, certain geo-processing tools have been custom built for this sector. Explore a Story Map of one such module by clicking on the image below -
Location Analytics for crime can be done on traditional GIS (Geographic Information System) platforms. These platforms are robust and one can conduct tactical and strategic analysis, intelligence analysis as well as create dashboards for public information sharing.
See all of this come together in a short four minute video involving situational awareness for a sporting event-
Intelloc Mapping Services | Mapmyops is engaged in selling products which capture geodata (Drones & Drone Services), process geodata (Geographic Information System) and enhance geodata (Imagery & Location Analytics). Together, these help organizations to benefit from Geo-Intelligence for purposes such as operations improvement and project management.
Write to us on projects@mapmyops.com.
Regards,
Arpit