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Perimeter Security System Offered by Bosch Video Systems (named IVA Pro Perimeter)

Intrusion detection software offers swift and dependable identification of unauthorized individuals at boundaries.

Bosch Video Systems' IVA Pro Perimeter Surveillance Solution
Bosch Video Systems' IVA Pro Perimeter Surveillance Solution

Perimeter Security System Offered by Bosch Video Systems (named IVA Pro Perimeter)

In the realm of security, false alarms can often lead to complacency and overlooked threats. To address this issue, IVA Pro Perimeter has developed an AI technology that significantly improves perimeter security by reducing false positives and enhancing intruder detection.

This innovative technology leverages deep learning models to accurately distinguish between genuine intruders and benign objects or movements. By doing so, it minimizes false alarms triggered by non-threat entities like animals, weather effects, or debris. This results in an earlier and more dependable detection of real threats at perimeter boundaries.

One of the key elements of IVA Pro Perimeter is its deep learning-based object detection and classification. This improves the system’s ability to differentiate between humans, animals, vehicles, and irrelevant motion. By layering advanced background subtraction and optical flow analysis, it can detect and classify objects, even if they are moving suspiciously or disguised.

The AI technology in IVA Pro Perimeter also enables early, reliable identification of intruder presence. This strengthens perimeter defense by facilitating rapid operator action or automated responses. Moreover, processing intelligence locally (on the device) supports real-time threat detection without delays from cloud communication, helping to speed up accuracy in alert generation.

Scalability is another advantage of IVA Pro Perimeter. The software is designed to meet customer requirements, and calibration is reduced to a single click followed by manual verification. It also includes person-based autocalibration, making it easy to deploy.

The new IVA Pro Perimeter sends instant alerts when a person or vehicle is near a defined virtual zone. It provides early and reliable detection of intruders at long distances and in challenging environmental and lighting conditions. Furthermore, it uses neural network-based detectors that are more reliable and accurate than the previous generation of optical flow analytics.

False positive triggers, such as dust particles and vehicle headlights, are ignored by IVA Pro Perimeter. It offers easy setup with Person-based Autocalibration, making it an attractive option for security integrators who are turning to AI-enabled approaches over traditional surveillance systems for enhanced perimeter security.

In the face of advanced threats, reliable and effective perimeter security is increasingly critical. Early detection allows operators more time to make decisions based on real-time data, including geolocation, object type, speed, and size. IVA Pro Perimeter notifies upon perimeter breaches and reliably detects and classifies individuals, even when disguised or moving suspiciously.

In addition, DMP has introduced JamAlert, a device designed to combat the growing threat of illegal cell jammers. This device complements the IVA Pro Perimeter system, ensuring that security measures are robust and comprehensive.

In conclusion, IVA Pro Perimeter's AI technology represents a significant leap forward in perimeter security. By reducing false positives, enhancing intruder detection, and providing early, reliable identification, it offers a more efficient and effective solution for securing facilities.

The AI technology in IVA Pro Perimeter not only reduces false alarms but also improves the system's ability to differentiate between humans, animals, vehicles, and irrelevant motion, thus making it more efficient in perimeter security. Furthermore, this technology enables early and reliable identification of intruder presence, strengthening perimeter defense and facilitating prompt operator action or automated responses.

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