Assaults by firearm kill about 11,000 people in the US each year, which translates to a roughly 1-in-370 lifetime chance of death from gun violence. That’s almost 50% more likely than the lifetime odds of dying while riding inside a car, truck, or van. These measures also suggest Americans are more likely to die from gun violence than the combined risks of drowning, fire and smoke, stabbing, choking on food, airplane crashes, animal attacks, and forces of nature.
Mass shooting incidents or incidents where “four or more [are] shot or killed, not including the shooter are also increasing. US Gun Violence Archive has a record of 340 mass shootings in 2018. In 2019 so far, there have been over 360 mass shootings, an increase in the number of violent shootings compared to the annual average of 250, according to Riker. “More significantly, the real concern here is other types of weapons — explosives — and, of course, firearms and different types of knives and other systems,” Riker said
A mass dismay took over central London on the Black on 24th Nov, leading to a human stampede in one of the busiest streets of the capital. Hundreds of people ran for their lives after reports of gunshots at Oxford Circus underground station in central London on November 24, but it turned out to have been a false alarm. David Lowe, a former police officer and counterterrorism consultant, said it might be time to try new technology in London in a bid to avert further mass panics.
Mr. Lowe said he thought it was also time for a complete rethink of security in London’s underground stations. “We are going to have to start looking at places like underground stations where there is a high volume of people. We need to look at evacuation procedures and ensuring we get the right message over to passengers. It’s one of the busiest Tube stations in London and there are always some parts of the station that are not covered by CCTV,” he told Sputnik.
Security forces are trialling many technologies that could End Mass Shootings. One of the technologies the security agencies are increasing showing interest in gunfire detection technology following the Oct. 2 shooting in Las Vegas where a gunman opened fire from a hotel and targeted people at a music festival. The mass shooting killed 58 people and wounded hundreds of others.
Many US cities use gunshot detection technology, which can tell whether a gun has been fired in a certain location. In cities like Chicago, which are prone to gang warfare, police cars respond to the alerts sent out by the ShotSpotter system before anyone even makes a 911 call.
As the disturbing prevalence of mass shootings increases, growth in the security market is projected to follow similar patterns. According to Grand View Research, by 2025 the physical security market is projected to reach US$292.4 billion. This is equal to a compound annual growth rate of 9.4 percent.
We are in a data-rich world. Our ability to analyze and understand massive amounts of data is unprecedented in breadth and scope. data analytics is one technology which hold enormous potential to search and nab potential suspects with weapons before they resort to the crimes. companies like Aegis AI and Athena Security, new tech firms leveraging artificial intelligence to identify firearms and alert law enforcement within seconds.
Recently Intel, with Honeywell, spoke about an artificial intelligence inferencing technology using a variant of facial recognition to identify people with firearms, and immediately sending an alert if an armed individual were approaching a monitored site (I’m kind of surprised that schools don’t have that now). This same technology likely could identify where the shooter was located, point first responders to both the attacker and the most injured, and be a huge part of a semi-automated response.
Gun control advocate in former New York City, Chipman envisions gun-detection camera systems being implemented in spaces, both public and private, where governments and businesses want to protect people. He characterizes such systems as “metal detectors 3.0″—ones that could be used in places like schools, sports stadiums, and malls to help react more quickly to shooters. And Chipman sees this technology being useful beyond the prevention of mass shootings. Chipman thinks gun-detection systems would be invaluable in hot spots for urban gun violence, where most people neither see nor hear a gunshot and where any witnesses might be unlikely to report a crime to police anyway.
One of the challenge is that these mass shooting give very little time for response.The Dayton shooter, Connor Betts, needed less than 20 seconds—the amount of time it took police to respond to the scene—to murder nine people and injure over a dozen more.
Another main obstacle, according to Chipman, is that people carrying firearms in states that guarantee the right to concealed carry could claim Athena Security or Aegis AI’s gun-detection systems are invasions of their privacy
Athena Security Motion detection and alert system
Ahena Security uses object-motion detection to spot when an individual brandishes a fireman, and immediately send an alert to their client, whether that’s a private security firm or local law enforcement. The company’s AI object-motion detection is camera agnostic, meaning it can work on any CCTV system. When a gun is detected, the video feed of the active shooter is made available to the client both on mobile devices and desktop computers, allowing officers to know what they are dealing with and where it is happening, all in the space of three seconds, according to Falzone.
Currently, Athena Security is in use by a number SWAT teams, Fortune 500 companies, the Al-Noor Christchurch mosque in New Zealand (the site of a religiously-motivated act of domestic terrorism last March), as well as by schools and governments. Falzone says that Athena Security is currently deploying its software on existing camera systems for its clients.
“We send an alert to e-911 and then they have that link and see exactly what’s going on during the crime,” Falzone explains. “Lots of police forces have tested the technology, the results of which are detailed in the white paper. We’ve created a really accurate algorithm to achieve over 99% accuracy.
Liberty Defense to Beta Test MIT Security Technology at MTCC
Security technology company Liberty Defense Holdings announced that it will launch a beta test of its Hexwave technology at the 700,000 square foot Metro Toronto Convention Center (MTCC) in early 2020.
Hexwave is a security technology that detects metallic and non-metallic weapons through the use of 3D imaging and automatic threat-detection systems. “This is a technology that has come out of the Massachusetts Institute of Technology (MIT) Lincoln Lab, and it is very specifically designed for the prevention of mass-attack weapons being brought into the facility,” Bill Riker, CEO of Liberty Defense, told the Investing News Network. Riker discussed a pain point across security operations: mass shootings. This is something the company is aiming to address with its technology.
The security technology incorporates both 3D imaging and machine learning to detect concealed weapons. “The 3D imaging is a form of low-energy radar that is projected across a detection space,” said Riker. “It creates a three dimensional image — that 3D point cloud comes from that radar system — and that 3D data set has a lot of information on it, over 3,000 data points over a person’s body, for example.”
Riker elaborated on the artificial intelligence capabilities of the security technology. “We use a form of deep neural network artificial intelligence to analyze that data and really zero in on an object on a person’s body,” said Riker. “This process enables us to do real-time detection and determination of people moving through a detection space.”
Beta testing for the Hexwave technology is expected to begin late 2019, with testing to continue into 2020. Testing will be predicated on real-life physical testing centers, such as stadiums and a wide cross section of other facilities.
Gunshot detection technologies
The technology enabling gunshot detection are wireless sensor Networks (WSN). WSN is a wireless network consisting of spatially distributed autonomous devices using sensors to monitor physical or environmental conditions. The self-powered nodes are equipped with sensors of light, sound, heat, pressure, e.t.c, communicating components and data processing that gather information or detect special events and send the data to the base station to be processed.
These are of great practical importance to military in surveillance missions as they allow monitoring of border and other critical areas to provide early warning of hostile events and targets while removing the risk to human personnel. Military applications of Wireless sensor networks include detection, classification, and determining the direction of movement of intruding personnel and vehicles. The Army used Raytheon’s Boomerang system in battlefields to find sniper locations and now casinos are showing interest in the technology.
They are also useful in detection, classification and accurate localization of battlefield acoustic transient events, namely gunshots, RPG, and artillery fires, especially in urban environments. They can also useful for detection of Nuclear, Biological and chemical (NBC) agents.
Acoustic Gunshot Detector – Gunfire sensor
Active-shooter detection systems are generally designed for outdoor, urban environments. But now, researchers at at Pacific Northwest National Lab (PNNL ) have created a gunshot detector specifically for indoor environments, such as schools and public buildings. The small, inexpensive device is battery powered and can connect wirelessly to existing security systems. It can distinguish between gunshots and other sounds. The device has already been licensed to commercial companies for integration into lockdown and reporting systems.
The device measures the energy of a sound wave and identifies if it is a firecracker, a slamming door, or a gunshot. It then records the waveform indicating the caliber of the weapon, which helps first responders better prepare with the right personnel and protective gear
Combined with additional technology, it automatically alerts authorities to the exact location of the gunfire, down to the room number and can trigger a lockdown system. The device costs about $100 per unit.
Elbit Systems’s May gunshot detection system
Elbit Systems’ Elisra subsidiary has developed a new wide-area acoustic sensing device called May. The system works with an autonomous network of static sensors that provides detection, classification, and geo-location of acoustic events such as gunshots, artillery fire, or explosions. It can also discern events that would be of more interest to law enforcement agencies, such as shouting and screaming.
Hadar Halili, marketing and sales director, land electronic warfare for Elisra said that the system is equipped with a complex set of algorithms that eliminate false alarms and locations due to echo or reflection, a feature that makes it suited for urban environments. It can be used to cue security cameras or other surveillance devices and could be used as a complementary capability to signals intelligence systems.
Network communications are usually provided through an integral cellular or wireless network, but wired connections are an option. The system is also suitable for border coverage. May is based on an open architecture and has been successfully integrated with command and control systems, although Halili was unable to provide details.
SST has developed and deployed “ShotSpotter”, the wide-area protection system designed for civilian and critical infrastructure applications. This system deploys multiple collaborative acoustic sensors perched atop roofs and light poles, throughout a coverage area up to 20 or more square miles. The sensors are paired with audio analysis software that identifies the unique signature of gunshots and other loud explosive sounds in real time.
Once the gunfire is detected, SST helps law enforcement respond safely and effectively to incidents by providing precise location of gunfire, both latitude/longitude and street address, number and exact time of shots fired, shooter position, speed and direction of travel (if moving). It can also provide Gunfire incident history and do pattern analysis.
SST’s ShotSpotter being improved to reduce false alarms
ShotSpotter was trialled in the UK in 2011/12 but the results were not positive. In August 2012 West Midlands Police, which covers the city of Birmingham, said only two out of 1,618 alerts produced by the system since November 2011 were confirmed gunshots and ShotSpotter had failed to pick up four other shootings.
Ralph Clark, CEO of ShotSpotter said the number of US cities now using ShotSpotter had consequently risen from 30 to 100.There were around 20 sensors per square mile in New York and each was equipped with noise cancellation software which lowered the ambient noise and made it easier to pick up “spiky noise” like a gunshot, he added. He said ShotSpotter was able to differentiate between gunshots and other similar noises like fireworks and cars backfiring.
The SENTRI Solution: A New Age In Law Enforcement
Safety Dynamics is currently selling and supporting a system for law enforcement called SENTRI (Sensor Enabled Neural Threat Recognition and Identification). The system is a breakthrough technology that recognizes gunshots and explosions and sends range and bearing details to cameras which can then locate the source of the event.
It is portable or can be at fixed locations and detect gunfire or the acoustic signatures of other incidents such as glass breaking or explosives. “In the case of Las Vegas, if we had been there — either indoors or within a range of being able to pick it up outdoors — we would have picked up that glass breaking,” said Sally Fernandez, president of Safety Dynamics, an Arizona-based company known for its SENTRI system. “And we would have picked up the first shots.”
The patented Dynamic Synapse Neural Network (DSNN) technology developed by the Laboratory for Neural Dynamics at the University of Southern California is at the core of the acoustic recognition capability and is based on neurobiological principles of brain signal processing, and allows, like the human brain, accurate temporal pattern recognition of acoustic signals even in the presence of high noise. Whether standing alone in a choke-point or working with mulitple units to cover a large area, SENTRI is part of a network of surveillance cameras which listen for gunshots and provide police with the ability to use audio and video for the identification of crimes in progress.
DARPA had developed “Shooter Localization” technology under its Network Embedded Systems Technology (NEST) program. Ad-hoc wireless network of cheap acoustic sensors were used to accurately locate enemy shooters. Nodes detect shockwave and muzzle blast and send back their data to the base station and Base station then determines shooter location. Fast and accurate enemy shooter localization are key in reducing friendly casualties and neutralizing enemy combatants. The Performance parameters were Average accuracy of 1 meter and Latency of 2 seconds.