SAFEYE, developed by DotNetix, is a cutting-edge intelligent onboard vehicle or machine vision system that helps to prevent collisions between vehicles, machinery, and pedestrians, making it the ideal solution for the safety demands of the construction, roadwork, and mining sectors.
Our system utilizes state-of-the-art technology, including deep neural network and 3D image processing, to accurately distinguish between pedestrians and their surroundings. This enables mines, ports, and industrial plants to improve their overall safety standards.
One of the key features of SAFEYE is its ability to function independently without the need for any tags or additional equipment. Our system seamlessly integrates multiple sensors for optimal performance and utilizes advanced AI to detect objects in the front and rear of the vehicle.
In the event of a potential collision, the system will analyze the situation and warn the driver. If the driver does not respond, the SAFEYE system will take action by communicating with the vehicle’s control electronics to stop the vehicle.
DotNetix has developed a long-range 3D camera that can accurately calculate the distance to an object up to 25 meters for pedestrians and 50 meters for mining and construction machines, and industrial vehicles. Additionally, longer distance detection is possible for other applications. With SAFEYE, we are dedicated to improving the safety of workers in their working environments and promoting overall safety in the industries we serve.
The use of cameras in collision prevention systems offers a number of advantages over traditional sensor-based systems. One of the primary benefits is the ability to detect and track objects in a wide field of view, which allows for more accurate and reliable detection of potential hazards. Cameras can also provide detailed visual information about an object, such as its size, shape, and distance from the vehicle, which can be used to determine its potential threat level.
Another advantage of using cameras in collision prevention systems is their ability to detect objects in a variety of lighting conditions, including low light and glare. This makes them more reliable than systems that rely on radar or lidar sensors, which can be affected by environmental factors such as fog or rain.
Cameras also have the ability to detect and track multiple objects simultaneously, which allows for a more comprehensive and accurate assessment of the driving environment. This can lead to a reduction in false alarms and improved overall system performance.
Finally, the use of cameras in collision prevention systems can help to reduce costs, as they are often less expensive to manufacture and maintain than other types of sensors. This makes them a cost-effective solution for improving the safety of machines.