We providesan explanation of AI, and highlights how AI is currently used throughout the technical cycle of operation within some security technologies, and across the AI types, domains and spectrum of AI paradigms. The document highlights future opportunities and risks associated with the adoption, or absence, of AI. This analysis is supported by a risk factor check list as an aide memoire to help security professionals consider ways to assess their opportunities and risks within the context of AI enhanced security technologies is, its true functional capabilities, and objectively consider the benefits and risks associated with the adoption of AI enhanced security technologies, ensuring such risks are accounted for in organizational risk registers.In the last decade, with the availability of a significant amount of data and increased computational power, experts have been able to take the theoretical ideas of deep learning and put them to practical use, specifically in the domain of computer vision.
Artificial intelligence and machine learning product that helps security personnel detect threats by scanning the underside of passing vehicles.The system uses strategically angled high-resolution cameras to make a 3D image of anomalies, like improvised explosive devices, illegal weapons, drugs, and other suspicious material. Anubrain claims that the technology will work even when the vehicle moving up to twenty-eight MPH, meaning that the technology can detect objects that might otherwise escape the human eye.
According to new marketing research , home security is predicted to succeed in $135.27 billion by 2027, up from $84.90 billion in 2021. This rise is essentially attributed to the introduction of AI , deep learning, and therefore the increasing ubiquity of IoT connected devices. Indeed, AI is revolutionizing home security because the technology can solve one among the most important issues faced by traditional home security solutions; human error and false alarms. One solution, Lighthouse AI, uses AI to provide you with a warning of humans, pets and other things that might be of interest while you’re faraway from home.
Technology is an AI-based system that permits threat screening on an enormous scale. The technology utilizes AI and face recognition software to research live footage of approaching visitors to work out if they’re approved persons, like regular visitors, VIPs, employees, and other persons who should be granted entry. If a visitor is highlighted as a non-permissible person of interest, their profile are going to be sent to security officers, and a person’s expert can review and verify the info . The technology claims to permit a minimum of one person to be allowed entry per second. This particular technology isn’t designed to completely eliminate the human element of threat analysis and may be best utilized at locations like airports, sporting events, and schools. If utilized successfully, this is able to effectively put an end to long lines and bottlenecks.
Artificial intelligence and machine learning are adding a layer of proactive trouble detection to CCTV cameras. With the addition of AI , CCTV cameras are now ready to spot potential shoplifters and alert shopkeepers to suspicious behavior. One solution called “AI Guardsman” developed by a Japanese company can scan live video streams to make estimations of “suspicious” behavior. Through AI and machine learning, the system tracks the posture and movement of shoppers, and analyses it to match the posture and movement of confirmed shoplifters derived from previous data.
The military potential for AI is large . there’s a natural convergence between the 2 areas, with military hardware rife with cameras, sensors, communication networks, and data that might enjoy AI . The capacity for humans to affect the sheer volume of knowledge on the fashionable battlefield is becoming a roadblock, affecting deciding and therefore the ability for information to flow right down to where it’s needed the foremost .
Scientists from Manchester Metropolitan are performing on a cutting-edge polygraph which will determine if an individual is lying about who they’re and why they’re traveling.
BorderCtrl – a European-funded project that has the potential to vary the way we approach border control. Virtual border guard that uses AI to inform if an individual is lying or telling the reality through imperceptible signs, like facial micro-gestures.
Artificial intelligence based solutions have also breached the oil and gas sector, a sector that has only fairly recently brought into the advantages of IoT connected devices and increased connectivity to the surface world. Indeed, AI is revolutionizing how offshore oil & gas workers maintain the safety of offshore oil and gas platforms.
There are currently several solutions on the market that utilize a mixture of ai-driven software, sensors, real-time and historical data to assure cognitive security. as an example , offshore oil workers can receive recommendations and on the way to prevent security breaches and make sure the longevity of kit .
The objective of VCA software is to analyses the video stream, one frame at a time, and create a structured database of information out of the unstructured video data. The VCA engine accepts the raw video stream and converts it to a comprehensible format. It then processes the same using computer vision & deep learning technology. As part of this processing, it performs the following critical tasks:
Accurate face detection and recognition are very critical to law enforcement agencies. It helps in identifying people of interest and is also helpful in post-incident investigations. Broadly, some of the benefits of Facial Recognition application are:
AI technology has enabled VCA applications to detect traffic violations accurately and automatically. The availability of a large set of video data and computational resources have enabled the respective DNN models to be trained effectively. Here are some of the VCA uses cases for Traffic & Road Safety: