New Vision System Autonomously Detects and Identifies Drone Threats

New Vision System Autonomously Detects and Identifies Drone Threats

ATLANTE – Commercial and recreational use of drones has exploded in recent years as the technology has become cheaper and easier to use. From infrastructure inspection and emergency response to filmmaking and amateur photography, drones have a wide and growing range of applications. Unfortunately, drones can also pose threats, intentional or not. In places where drones pose a threat, such as airports, prisons, border patrols, and military scenarios, airspace security becomes paramount.

Fortunately, as drone technology has advanced, drone detection capabilities have also advanced. Radio frequency sensors, radars, acoustic sensors, cameras and other technologies are typically used for such tasks. Some technologies even offer standalone capabilities.

Drone threats emerge

In the United States alone, the number of drones registered with the Federal Aviation Administration is approaching one million, with 314,689 commercial drones. and 538,172 recreational drones registered at the time of writing. What was once considered a future concept has become commonplace. At the same time, security measures and technologies related to drones must evolve, as drones ultimately pose a myriad of threats.

Examples include flying too close to restricted airspace, depositing contraband in prison yards, transporting drugs across borders, conducting prohibited surveillance and reconnaissance, and even dropping small bombs or explosives. According to the Cybersecurity & Infrastructure Security Agency, recognizing threats and implementing security practices that comply with federal, state, and local regulatory requirements are crucial steps in successfully managing potential security incidents associated with drones.

There are several methods to mitigate risk, starting with researching and implementing legally approved counter drone technology and understanding the aerial domain around a facility or area. Autonomous detection systems such as the AirScout Sentry from Walaris combine industrial cameras, powerful edge processing, and proprietary computer vision and artificial intelligence (AI) algorithms for optical detection capabilities in critical applications.

Autonomous threat detection

Depending on application requirements, the hardware-independent AirScout can deploy cost-effective cameras from Axis or Bosch or use other off-the-shelf multispectral or infrared imaging cameras for longer deployments. scope. AirScout Sentry from Walaris offers a complete detection, tracking and identification solution, while companies looking to use other detection modalities, such as radar, can use AirScout Verify, a tracking and identification software solution. ‘identification.

Each AirScout Sentry deployment of the system involves multiple sensor cameras that continuously monitor an area of ​​interest. Detections from these video feeds are transmitted to a verification camera, which confirms the threat and either alerts operators or rejects false positive detections. If the AirScout Sentry software detects relevant data such as birds or a drone, it captures the coordinates of the object. A pan-tilt-zoom algorithm triggers a camera to zoom into the coordinates to further investigate the object, while AI and focus range control algorithms allow the system to find the target, to maintain a clear picture and to classify, identify and track it.

Once the system classifies an object as a drone, it provides an alert to the system operator, along with a full-screen video with the classification determination. The operator can then decide how to handle the situation. Different operators will treat information differently, depending on the market they serve. In military or federal government operations, this often means engaging and mitigating the target. At an airport, that might mean closing runways, while a jail request might involve securing the yard and bringing inmates inside.

A clean data acquisition pipeline

Classifying drones with a high degree of confidence presents several challenges. They’re small, fast-moving objects at a distance, clutter can be present in the area of ​​interest, and drones can fly through complex backgrounds, according to Kyle Meloney, co-founder and CEO of Walaris in Atlanta.

“Using state-of-the-art AI algorithms allows the system to perform optical classification in near real-time and with limited optical information, but getting to this point requires a lot of preparation when it comes to data,” he said. .

AirScout’s AI algorithms continuously train on a growing data set. Walaris’ data acquisition pipeline involves acquiring images and cleaning that data to ensure that all images are properly labeled so that the training process uses high quality images to train better their models.

“Our training process is lifelong,” Meloney said. “We are constantly adding clean, labeled images to the dataset and improving the algorithms over time, so the system works more efficiently over time.”

Powerful edge processing for powerful AI

At the heart of the overall AirScout system is the software, which includes, among other things, the proprietary detection, classification and PTZ algorithms. Previous optical detection methods involved looking for motion and/or contrast in an image. This technique works well in simple scenarios, but complications arise when the scene becomes more complex, according to Meloney.

“If a drone is flying in a cloudy sky and birds are present in the scene, then there is a lot of movement and different levels of contrast and it can become difficult to spot the drone,” he said. “By processing the entire image in near real-time and marking each object to determine its relevance, we can reduce false positives and automate the detect-track-identify response chain.”

Running complex AI algorithms requires powerful processing capabilities, so Walaris sourced a custom-configured industrial PC from CoastIPC with an NVIDIA graphics processing unit (GPU) to run the AirScout software. .

“Critical applications require reliable and rugged PCs,” Meloney said. “Every PC provided by CoastIPC has arrived on time and meets exactly the requirements we specified to deliver and execute each mission without failure.”

eyes in the sky

The market offers several methods of detecting drones, and no one option is necessarily the best possible solution. For those looking to take a hands-off, holistic approach, however, systems that leverage cameras and AI software can provide comprehensive solutions for detecting, tracking, and identifying drones in dynamic environments.

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