Year: 2022

Canadian federal transport minister has fined 37 passengers on a flight from Montreal to Mexico were fined $59,500. The charter flight from Montreal to Cancun took place in late December 2021.

Videos seen on social media showed the unmasked passengers partying in the aisles and on seats, drinking alcohol and vaping. Transport Canada has a continuing investigation into the flight and says “further sanctions could be issued.”

Sunwing Airlines cancelled the return charter flight once the videos were seen on social media. Two airlines, Air Canada and Air Transat, refused to book the group of passengers on return trips to Canada.

Cignal, a small business that develops high-performance computing (HPC) and simulation environments to rapidly train Automated Threat Recognition (ATR) systems, announced that it was selected as a presenter at the 2022 Department of Homeland Security (DHS) Science and Technology Directorate’s (S&T) Silicon Valley Innovation Program (SVIP) Demo Week on Machine Learning.

During its presentation, Cignal will discuss and demonstrate its HPC software stack, which facilitates the dynamic training, evaluation, and deployment of next-generation ATR systems for emerging and complex threats. The Cignal HPC Stack permits users to create new screening paradigms, novel objects, and new artificial intelligence (AI) and machine learning (ML) models to protect the public and critical infrastructure against emerging and complex threats. Using this stack, Cignal created the industry’s first volumetric million-bag dataset, which supports advanced X-ray and CT X-ray systems and AI/ML training for large-scale, trillion-parameter ATR models.

The Cignal HPC Stack consists of CignalRay, Checkpoint, Designer, and Cignal Toolkit (CTK) and PyCTK. CignalRay, a patent-pending compute and render engine, generates 2D and 3D-imagery and labels for AI/ML training. Checkpoint is a dynamic training environment that simulates interactions between materials and objects and also allows users to manipulate objects and their properties, creating an unlimited number of dataset variations. To quickly address emerging threats, Designer allows novel firearms, concealments, and explosive designs to be integrated into the training pipeline for rapid detection of threats, which may be too difficult or hazardous to evaluate in real-world environments. CTK and PyCTK provide AI/ML model developers with seamless, interactive command line and Python access to the underlying compute and rendering engine, while enabling convenience in working with massive datasets.

Cignal will be presenting at the 2022 DHS SVIP Demo Week on Machine Learning on Tuesday, May 3, 2022.

AI/ML models rely on large amounts of labeled training data to learn, and generating this data for ATR applications currently is a labor-intensive, manual process. Cignal’s HPC and simulation capabilities eliminate these barriers, allow users to quickly train or test new detection models without the time, cost, or potential hazards associated with conventional approaches.

Russelectric, A Siemens Business, maker of power control systems and automatic transfer switches, is offering a robust and reliable emergency power system which provides backup power during a utility power loss. The paralleling switchgear systems offer redundant programmable logic controller (PLC) controls and manual backup capability. Trusted by the largest critical facilities in the world, the Russelectric Emergency Power System has been used by airports.

Complete systems are custom designed and fully manufactured by Russelectric. All systems are UL listed and can incorporate such sophisticated control functions as peak shaving and load curtailment. Russelectric paralleling systems incorporate dual, redundant, hot synchronized PLCs for system control. The unique system design allows manual start and synchronization of generator sets if automatic controls malfunction. Discrete switches, meters and control devices are standard to allow manual control capability in the event that both system PLCs fail.

Designed for maximum safety and operating simplicity, the systems are supervisory control and data acquisition (SCADA)-capable. A 23-inch LCD HMI touchscreen display enables operators to view system one-line diagrams, alarms, and setpoints.
Load demand sensing determines the number of engine generators in operation based on the loading. The system permits first priority loads to transfer to the connected engine generator set, while delaying the transfer of lower priority loads until additional generator capacity has been connected. Lower priority loads then transfer to the emergency power system as generator sets are added to the bus.

Addressing the need for large-scale, safe uncrewed aviation, Iris Automation announces the commercial availability of Casia G, a ground-based version of its detect and avoid (DAA) surveillance solution. Using the same patented AI and computer vision technology as Iris Automation’s onboard solutions, it provides a full optical, 360° degree field of regard designed to detect, alert and enable operators to avoid both co-operative and non- cooperative aircraft for safe beyond visual line of sight (BVLOS) flight. 

Casia G creates a perimeter of sanitized, monitored airspace for UAVs to perform work safely, without additional payload. It’s ideal for operations in fixed or temporary locations, supporting drone in the box operations and augmenting or replacing human visual observers. BVLOS flight for uncrewed systems has been challenging due to right of way concerns, specifically the inability for uncrewed aircraft to successfully see and avoid other aircraft. 

“A human has sufficient visual acuity to see airborne traffic only within a +/-5 degree field of view around our focal point – we have to scan the sky, and are frankly not very good at it,” said Jon Damush, CEO, Iris Automation. “Casia G sees the entire sky, with uniform probability and resolution, 10 times per second – without distractions or breaks. This is a solution for airspace awareness that covers a large majority of small UAS use cases, but at a price point that is economically viable and without complex integration.”

Iris Automation says Casia G provides an operator with airspace awareness:
– at a price point that allows operators to fix their costs and enjoy lower per-flight costs as
operations scale.
– operating multiple, dissimilar types of aircraft within the coverage area, since no direct
aircraft integration is required.
– without requiring difficult or expensive integrations with aircraft systems.
– without consuming valuable size, weight and power (SWaP) from the aircraft.
– without requiring approvals from agencies other than the FAA.

Casia G can be expanded by simply adding additional units in a mesh to create a network of detection nodes for large-area air risk mitigation. The system then provides a single feed of cooperative and non-cooperative air traffic, available to an operator’s UTM system. This provides a path to approvals for both larger area and one-to-many operations by enabling a holistic view of the airspace. Casia G has already obtained a BVLOS waiver on behalf of the City of Reno, and Iris Automation is in the process of proving additional deployment patterns and concepts of operation with the FAA.

“The Casia portfolio of products is a force multiplier for safety. Whether enabling autonomous flight or adding an additional layer of safety for piloted flight, it’s an extra level of surveillance. Casia G offers an extremely scalable ground-based solution for times where onboard isn’t an option or a fixed location needs to be surveyed, creating a safety zone ideal for a wide range of surveillance use cases,” said Jason Hardy-Smith, VP of Product, Iris Automation.