Mobotix is launching the company’s new Mobotix 7 open solution platform and the M73 high-end camera that uses it. Supported by artificial intelligence and application solutions based on deep learning, the new generation of video cameras not only enables an unlimited set of functions but it also opens up new possibilities beyond traditional video security. This means that the Mobotix systems remain fully reliable and secure, as cyber security and data security continue to have high priority.
At this year’s Mobotix Global Partner Conference (GPC) in Mainz, Hartmut Sprave, Chief Technology Officer at Mobotix explained, “The Mobotix 7 is by far our most powerful decentralised and secure modular IoT-video system based on deep learning modules, and sets new standards for intelligent video technology. Our hardware and software are ‘Made in Germany’, and tailor-made camera apps provide limitless possibilities for expanding the Mobotix 7. This will revolutionise numerous IoT processes — not only for us, but for our technology partners and customers in various markets too.”
Even at its launch, the Mobotix 7 already comes with pre-installed apps that are verified and certified by Mobotix and meet the company’s high standards in terms of cyber security. These apps are supported by artificial intelligence (AI) and deep learning, and cover a significant number of industry-specific, individual requirements. It is also possible for partners, customers or users to develop and programme their own solutions and have these certified by Mobotix.
The new Mobotix video system is also suitable for very particular and individual challenges in specific areas: for example, one of the Mobotix camera apps can detect when a building is in danger of becoming overcrowded. In this case, the camera would immediately and automatically trigger a diversion for any further persons wishing to enter the building, thus reliably preventing accidents and panic. By combining image sensors and environmental sensors with AI-based analytics, industrial enterprises can increase their production efficiency and improve fire prevention measures, for example.
The object-based recognition of individual road users, such as trucks, cars or people, and their behaviour, such as stopping, accelerating and so on, is enabled for traffic and transport applications. The information that is immediately available can improve road safety for drivers and passengers, while enabling other road users to continue moving in an unobstructed flow.
