Breakthroughs, discoveries, and DIY tips sent every weekday. Creating mock crime scene evidence can help forensic scientists better read the stories left behind by gruesome bloodstains. To decode some of these bloody stories, all a team from North Carolina State University needed was a combination of high-speed cameras, cotton fabrics, and a bit of pig's blood. Forensic science is a relatively new concept, historically speaking. There are multiple major moments in its development, but the field of study can largely be traced back 115 years ago to a man named Edmond Locard.

Crime is a critical problem -- which often takes place behind closed doors, posing additional difficulties for investigators. To bring hidden truths to light, evidence at indoor crime scenes must be documented before any contamination or degradation occurs. Here, we address this challenge from the perspective of artificial intelligence (AI), computer vision, and robotics: Specifically, we explore the use of a blimp as a "floating camera" to drift over and record evidence with minimal disturbance. Adopting a rapid prototyping approach, we develop a proof-of-concept to investigate capabilities required for manual or semi-autonomous operation. Consequently, our results demonstrate the feasibility of equipping indoor blimps with various components (such as RGB and thermal cameras, LiDARs, and WiFi, with 20 minutes of battery life). Moreover, we confirm the core premise: that such blimps can be used to observe crime scene evidence while generating little airflow. We conclude by proposing some ideas related to detection (e.g., of bloodstains), mapping, and path planning, with the aim of stimulating further discussion and exploration.

Technologies such as robotics, Artificial Intelligence (AI), and Computer Vision (CV) can be applied to crime scene analysis (CSA) to help protect lives, facilitate justice, and deter crime, but an overview of the tasks that can be automated has been lacking. Here we follow a speculate prototyping approach: First, the STAIR tool is used to rapidly review the literature and identify tasks that seem to have not received much attention, like accessing crime sites through a window, mapping/gathering evidence, and analyzing blood smears. Secondly, we present a prototype of a small drone that implements these three tasks with 75%, 85%, and 80% performance, to perform a minimal analysis of an indoor crime scene. Lessons learned are reported, toward guiding next work in the area.

NEW YORK – The masked gunman wanted in connection with the ambush shooting death of UnitedHealthcare CEO Brian Thompson Wednesday morning fled the crime scene using various modes of transportation before police believe he got on a bus out of the Big Apple, authorities told Fox News. Police traced his route from the crime scene near 54th Street and Sixth Avenue up to Central Park, which he exited at 77th Street and Central Park West, Chief of Detectives Joseph Kenny told Fox News Friday. Kenny's boss, new NYPD Commissioner Jessica Tisch, added that investigators have picked up an abundance of video and digital evidence in addition to physical evidence they hope can lead them to the killer. "We actually have a tremendous amount of forensic evidence in this case that we've collected- DNA evidence, fingerprint evidence, which is all at the lab now being processed," she told Fox News Friday. This undated photo provided by UnitedHealth Group shows UnitedHealthcare chief executive officer Brian Thompson.

In 2017, detectives at the East Bay Regional Park District Police Department working a cold case got an idea, one that might help them finally get a lead on the murder of Maria Jane Weidhofer. Officers had found Weidhofer, dead and sexually assaulted, at Berkeley, California's Tilden Regional Park in 1990. Nearly 30 years later, the department sent genetic information collected at the crime scene to Parabon NanoLabs--a company that says it can turn DNA into a face. Parabon NanoLabs ran the suspect's DNA through its proprietary machine learning model. Soon, it provided the police department with something the detectives had never seen before: the face of a potential suspect, generated using only crime scene evidence. The image Parabon NanoLabs produced, called a Snapshot Phenotype Report, wasn't a photograph.

Artificial intelligence can accurately identify whether or not fingerprints left by different fingers came from the same person. This could help forensic investigators uncover if one individual was present at separate crime scenes. Current technologies are only capable of matching fingerprints left by the same finger. But previous studies have hinted there may be fundamental similarities between all of a person's fingertips. How this moment for AI will change society forever (and how it won't) So, Gabe Guo at Columbia University in New York and his colleagues trained a machine learning model to determine if it could identify whether fingerprints from different fingers belong to the same person.

Thousands of cold cases could be solved thanks to an breakthrough in fingerprint analysis by artificial intelligence. A computer using artificial intelligence system has shattered the received wisdom of decades that each fingerprint from a person's finger is unique. So if a criminal left a thumbprint at one crime scene, and a print from his index finger at another, there would be no way to link the two. The breakthrough came about when a Columbia University student attempted to see if artificial intelligence could find links between apparently very different fingerprints from the same person. To test the idea, Gabe Guo, an engineering graduate with no background in forensics presented a computer with images of some 60,000 fingerprints in pairs.

He spent about six hours at the property, which was the scene of a quadruple homicide in November. As the University of Idaho community reels from the shocking slayings of four undergrad students in an off-campus rental home in Moscow, Idaho, this past November, school officials have already announced plans to tear the building down. "The owner of the King Street house offered to give the house to the university, which we accepted," University of Idaho President Scott Green said last week. "The house will be demolished. This is a healing step and removes the physical structure where the crime that shook our community was committed."

Serve Robotics has teamed with several companies including Uber, Domino's and Amazon to launch a pilot program for robot delivery. When one of its robots encountered crime scene tape, it was able to sneak by with a little help from a nearby TV cameraman.

Video of a sidewalk delivery robot crossing yellow caution tape and rolling through a crime scene in Los Angeles went viral this week, amassing more than 650,000 views on Twitter and sparking debate about whether the technology is ready for prime time. It turns out the robot's error, at least in this case, was caused by humans. The video of the event was taken and posted on Twitter by William Gude, the owner of Film the Police LA, an LA-based police watchdog account. Gude was in the area of a suspected school shooting at Hollywood High School at around 10 a.m. when he captured on video the bot as it hovered on the street corner, looking confused, until someone lifted the tape, allowing the bot to continue on its way through the crime scene. A food delivery robot forces it's way across a police crime scene.