Neil Huntingdon

Like most industries, the fields of security, access, and safety have been transformed by technology, with AI-driven automation presenting a clear opportunity for players seeking growth and leadership when it comes to innovation. In this respect, these markets know exactly what they want. They require solutions that accurately (without false or negative positives) classify and track people and/or vehicles as well as the precise location and interactions between those objects. They want to have access to accurate data generated by best-of-class solutions irrespective of the sensor modality. And, they need to be able to easily deploy such solutions, at the lowest capex and opex, with the knowledge that they can be integrated with preferred VMSs and PSIMs, be highly reliable, have low install and maintenance overheads and be well supported. With these needs in mind, camera and computer vision technology providers, solutions providers, and systems integrators are forging ahead and have created exemplary ecosystems with established partnerships helping to accelerate adoption. At the heart of this are AI and applications of Convolutional neural networks (CNN), an architecture often used in computer vision deep learning algorithms, which are accomplishing tasks that were extremely difficult with traditional software. But what about 3D sensing technologies and perception? The security, safety, and access market have an additional crucial need: they must mitigate risk and make investments that deliver for the long-term. This means that if a systems integrator invests in a 3D sensing data perception platform today, it will support their choice of sensors, perception strategies, applications, and use cases over time without having to constantly reinvest in alternative computer hardware and perception software each time they adopt new technology or systems. This begs the question - if the security industry knows what it needs, why is it yet to fully embrace 3D sensing modalities? Perception strategy Intelligent perception strategies are yet to evolve which sees designers lock everything down at the design phaseWell, one problem facing security, safety, and access solutions providers, systems integrators, and end-users when deploying first-generation 3D sensing-based solutions is the current approach. Today, intelligent perception strategies have yet to evolve beyond the status quo which sees designers lock everything down at the design phase, including the choice of the sensor(s), off-the-shelf computer hardware, and any vendor-specific or 3rd party perception software algorithms and deep learning or artificial intelligence. This approach not only builds in constraints for future use-cases and developments, it hampers the level of perception developed by the machine. Indeed, the data used to develop or train the perception algorithms for security, access, and safety use cases at design time is typically captured for a narrow and specific set of scenarios or contexts and are subsequently developed or trained in the lab. Technology gaps As those in this industry know too well, siloed solutions and technology gaps typically block the creation of productive ecosystems and partnerships while lack of commercial whole products can delay market adoption of new innovation. Perception systems architectures today do not support the real-time adaptation of software and computing engines in the field. They remain the same as those selected during the design phase and are fixed for the entire development and the deployment stage. Crucially, this means that the system cannot deal with the unknowns of contextually varying real-time situations where contexts are changing (e.g being able to reflex to security situations they haven’t been trained for) and where the autonomous system’s perception strategies need to dynamically adjust accordingly. Ultimately, traditional strategies have non-scalable and non-adaptable competing computing architectures that were not designed to process the next generation of algorithms, deep learning, and artificial intelligence required for 3D sensor mixed workloads. What this means for industries seeking to develop or deploy perception systems, like security, access, and safety, is that the available computing architectures are generic and designed for either graphic rendering or data processing. Solutions providers, therefore, have little choice but to promote these architectures heavily into the market. Consequently, the resulting computing techniques are defined by the computing providers and not by the software developers working on behalf of the customer deploying the security solution. Context…. we don’t know what we don’t know Perception platform must have the ability to adjust to changes in context, thereby improving the performance post-deployment To be useful and useable in the security context and others, a perception platform must have the ability to adjust to changes in context, can self-optimize, and crucially, can self-learn, thereby improving the performance post-deployment. The combinations of potential contextual changes in a real-life environment, such as an airport or military base, are innumerable, non-deterministic, real-time, often analog, and unpredictable. The moment sensors, edge computing hardware, and perception software are deployed in the field, myriad variables such as weather, terrain as well as sensor mounting location and orientation all represent a context shift where the perception systems’ solution is no longer optimal. For example, it might be that a particular sensor system is deployed in an outdoor scenario with heavy foliage. Because the algorithm development or training was completed in the lab, the moving foliage, bushes, or low trees and branches are classified as humans or some other false-positive result. Typically, heavy software customization and onsite support then ensue, requiring on-site support by solutions vendors where each and every sensor configuration needs to be hand-cranked to deliver something that is acceptable to the end customer. A new approach for effective perception strategies Cron AI is building senseEDGE, which represents a significant evolution in the development of sensing to information strategy.  It is a 3D sensing perception and computer vision platform built from the ground up to address and remove the traditional deployment and performance bottlenecks we’ve just described. senseEDGE is aware of the user application reaction plan indication to trigger an alarm or turning on a CCTV camera The entire edge platform is built around a real-time scalable and adaptable computing architecture that’s flexible enough for algorithms and software to scale and adapt to different workloads and contexts. What’s more, it has real-time contextual awareness, which means that the entire edge platform is, at any time, aware of the external context, the sensor and sensor architecture, and the requirements of the user application. Furthermore, when it produces the object output data, it also aware of the user application reaction plan indication, which could be triggering an alarm or turning on a CCTV camera when a specific action is detected. This approach turns traditional perception strategies on their head: it is software-defined programmable perception and computing architecture, not hardware-defined. It is free from the constraints imposed by traditional CPU or GPU compute dictated by hardware architecture providers and not limited to the perception built defined during design time. And, being fully configurable, it can be moved from one solution to another, providing computation for different modalities of sensors designed for different use cases or environments, and lower risk of adoption and migration for those developing the security solution.  Future perception requirements senseEDGE is also able to scale to future perception requirements, such as algorithms and workloads produced by future sensors as well as computational techniques and neural networks that have yet to be invented. Meanwhile, latency versus throughput is totally software-defined and not limited by providers of computing architecture. Finally, contextually aware, it is fully connected to the real world where the reflexes adapt to even the subtlest changes in context, which makes all the difference in time and accuracy in critical security situations. This is how CronAI sees the future of perception. It means that security and safety innovators can now access and invest with low risk in a useable and scalable perception solution that can truly take advantage of current and future 3D sensor modalities.

CNL Software, globally renowned developer of Physical Security Information Management (PSIM) software solution, is pleased to announce that it will be exhibiting at Intersec 2020. CNL will focus on the technology that is driving the digital transformation of control rooms across the Middle East region. CNL will be joined by Cepton Technologies, Inc. a developer of industry-leading 3D sensing solutions, who will be showcasing their latest correlation of LiDAR data with real time video visualization. Scalable and secure PSIM solutions CNL Software will share valuable insights into its open, adaptable, scalable and secure PSIM solutions CNL Software will share valuable insights into its open, adaptable, scalable and secure PSIM solutions as chosen by regional governments, military, enterprises and cities.  It will discuss how security operations can leverage the latest technology developments such as Artificial Intelligence (AI) and Machine Learning (ML) to help to identify and respond to incidents faster and more accurately. “CNL IPSecurityCenter is trusted by the best-informed security operations in the Middle East to provide proactive control from a central command center and supports autonomous local operations”, said Craig Menzies, General Manager – Middle East for CNL Software. “The region is changing, we are seeing the digitalization of control rooms as organizations evolve to meet today’s security challenges. CNL is driving this within our customers, enabling them to leverage from the best of breed technologies.” Integration with IPSecurityCenter When integrated with IPSecurityCenter, Cepton further enhances the industry’s most comprehensive PSIM system solution, providing users with access to more of the tools they need to quickly see, understand, assess and properly resolve perimeter security and surveillance incidents, consistently. “For the first time in the Middle East, Cepton will be showcasing the correlation of LiDAR data with real time video visualization. From a technical perspective the camera will be calibrated into a common coordinate system with the LiDAR. As a result, it will provide 3D world coordinates from the LiDAR onto a 2D video stream,” said Neil Huntingdon, VP Business Development at Cepton. LiDAR network detection Neil further adds, ”This ground breaking system provides instant video confirmation of targets detected by the LiDAR network, which will reduce false positives and allow threats to be identified faster. We have also created targeted zones for critical areas, where we can use superior algorithms without the need for additional computing hardware. This functionality also allows us target sections of video, which can be stored in high-resolution while the rest is stored in lower resolutions leading to increased efficiency and reducing the need for expensive processing and storage.”

CNL Software, globally renowned provider of Physical Security Information Management (PSIM) software, is pleased to announce a technology partnership with Cepton Technologies, global developer of 3D sensing solutions, at the GSX event in Chicago. The partnership will drive the automation of threat detection, tracking and escalation in real time using the latest PSIM, LiDAR and video assessment technologies.  Helius smart lider network Cepton's Helius system is a smart lidar network utilizing edge computing to provide real-time detection Cepton Technologies’ Helius system is a smart lidar network utilizing edge computing to provide real-time detection, tracking and classification. It can seamlessly track an object from sensor to sensor, providing 3D data on location, dimensions, and velocity, while maintaining the same identification of the object. By connecting multiple laser-powered sensors, it offers comprehensive coverage of a given area as well as high resolution imaging of objects. Sensors can be clustered as needed but act as one to maximize the simplicity of use and integration. With the in-built software in the hardware unit, Helius is browser-based and can launch on computers and mobile devices for instant monitoring and configuration, without installations of additional software. Furthermore, being edge-based, Helius processes data locally and outputs low-bandwidth data to the central server. Lidar sensor technology “CNL Software is committed to working with new and innovative technologies that will give our customers improved security and greater efficiency. Cepton’s lidar sensor technology brings the technological leaps that have taken place in autonomous vehicles to the security industry, especially in the government and critical infrastructure markets where we are experiencing growing demand for the integration of multiple different security system and sensor technologies,” comments Keith Bloodworth, CEO, CNL Software. Helius enhances the industry’s most comprehensive PSIM system solution" Keith further said, “When integrated with IPSecurityCenter, Helius further enhances the industry’s most comprehensive PSIM system solution, providing users with access to more of the tools they need to quickly see, understand, assess and properly resolve perimeter security and surveillance incidents, consistently.” IPSecurityCenter integration Neil Huntingdon, Cepton’s VP of Business Development stated “Our technology’s ability to detect and track events in traditionally difficult environments combined with IPSecurityCenter’s ability to correlate this data with data from other security systems and sensors and provide decision support is a powerful proposition.” He further adds, “We’re really excited to be partnering with CNL Software to bring this game changing solution to the government, critical infrastructure, safe city and transportation markets, in particular. It will unlock that ‘missing layer’ by filling the medium-range sensor gap and improve it with the capability to classify objects as well as behaviors.”

Kit (PEK), combines the unerring accuracy of lasers to scan the environment in much the same way a radar does, but at a much higher resolution, building an image of the world around it regardless of lighting conditions. Presenting the technology in the UK for the first time at IFSEC International in London’s ExCeL, Cepton’s VP Neil Huntingdon says that because the device combines the sensor with a powerful micro-computer in a single package it can process the information directly at the “edge” and highlight only potential threats, such as an intruder or a suspicious package. This then guarantees the anonymity of those not involved in any suspicious incident. Enhanced data protection Lidar can see in the dark, it only transmits a fraction of the information a video would" Neil, Cepton’s VP of Business Development, said: “Our technology allows for far greater protection of data – because it allows operators to zero in on possible issues in a way other technology cannot. There are many advantages to this; most notably Lidar can see in the dark, it only transmits a fraction of the information a video would, reducing the burden of data storage and network bandwidth charges, while opening the door to more mobile installations.” “Perhaps most importantly it means we can guarantee the anonymity of people or objects not deemed a threat. This is a step-change from existing technology, where everyone’s face is captured and held on video storage, regardless of whether they were involved in an incident or not.” 3D Lidar sensor detection technology In addition to being more dynamic than video technology, the system has been designed with user simplicity in mind. “You hand someone a camera and they know what it is and what to do with it. This is often not the case with a Lidar and Cepton intends to change that.” said Jerone Floor, Head of Product at Cepton. He further states, “Our customers should not need to be Lidar experts to set up and test our system, but, at the same time, the tools are available to take it to the next level and develop products based on our Vista family of sensors.” Wireless connectivity Cepton’s technology, which can operate over Wi-Fi, mobile networks or Ethernet, can also be used to enable driverless cars and to monitor traffic and infrastructure usage, enabling smarter modeling of transport networks. Neil added, “This technology is undoubtedly an exciting prospect for security and transport – and we believe it is the key to the delivery of truly smart cities that can make our communities safer and more connected.”