New technologies help police and crime scene techs get the most information from evidence. Here are a few interesting use cases.
Photos and video have been used for decades as evidence and documentary support in courtrooms, but with the advent of more big data-friendly technology tools, it's easier to prosecute, defend, and document cases. Newer big data capture technologies in particular can also corroborate another premise: That big data is only as valuable as what you can get out of it, and to extract value, you have to have the right tools.
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Here are three examples of how law enforcement and insurance companies are using newer data capture technologies to extract maximum value from big data.
Documenting the scene of the crime
Investigators examine a crime scene carefully and methodically. They collect information at the scene, being careful not to disturb or compromise evidence. They walk through the crime scene taking detailed notes, but it's very time consuming and subject to errors and oversights.
One law enforcement agency, the Johnson County (Kansas) Criminalistic Lab in a Kansas City suburb, decided to economize and optimize the process. Rather than shooting photos and taking notes, the agency used a 3D laser scanner to capture data and document a homicide—a man shot to death in his car—with the goal of mapping the crime.
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In the process, investigators conducted three exterior scans, mounting a laser scanner on a tripod. After the body of the victim was removed from the car, the investigators then mounted the scanner on the car's center console armrest, where they captured a 360-degree scan of the car's blood-stained interior. They then conducted a second 360-degree scan from the car's rear seat for a total of five scans.
The scans were later stitched together in the department's CAD system. The entire onsite investigation took a total of 60-90 minutes, and the investigative team dramatically reduced the risk of human compromise of evidence at the scene.
Using drones to document traffic accidents
It can take two to three hours to document a highway traffic accident. Meanwhile, lanes are closed, and oncoming traffic slows to a crawl.
The tedium of documenting these accidents, and the adverse impacts on traffic, have prompted law enforcement and insurance company investigators to employ drones that use thermal imaging to capture accident data from the air. This thermal imaging can generate maps, imagery, and models for post-crash investigations by engineers and public safety officials.
"Overall, [drones] can cut 60% off the downtime for traffic flow following a crash," said Capt. Robert Hainje of the Tippecanoe County (Indiana) Sheriff's Office.
Defending yourself from a negligent driving charge
A large truck from a major logistics company crossed an intersection and collided with an oncoming car whose driver didn't have enough time to brake. Both drivers claimed that the other party was at fault.
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The car driver alleged that the truck driver was negligent: He crossed the intersection and never looked for oncoming traffic. The truck driver alleged that the car driver was speeding, and that it was impossible for him to brake and avoid a collision.
The case went to court.
In preparing for the case, the truck driver's logistics company's insurer decided to use a 3D simulation. Data for the simulation was captured by mounting a camera on a car and driving the car along the same stretch of highway where the accident occurred. The insurer then used "what if" modeling that simulates the car accident at different speeds to determine the likelihood of an accident at each speed. By using these simulations, the insurer was able to demonstrate that the car had to be traveling at least 80 miles per hour for an accident to occur.
Why this technology matters to law enforcement agencies
Each of these examples illustrates how big data capture, enabled with the proper tooling, yields big results.
As engineering CAD systems, municipal, county and state GIS systems, cameras, laser scanners, and lidar technologies take hold, the ability to extract greater amounts of information from daily events will exponentially expand, furthering the case for mission-critical applications that use big data.
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