Mobotix Releases M7 Platform and M73 Camera at GPC
Mobotix 4K M73 IoT Camera.
The M7 system platform and the M73 camera were presented to over 500 technology and sales partners at this year’s MOBOTIX Global Partner Conference (GPC) in Germany.
“The MOBOTIX 7 is our most powerful decentralized and secure modular IoT-video system based on deep learning modules, and sets new standards for intelligent video technology,” explained Hartmut Sprave, chief technology officer at MOBOTIX AG.
“Our hardware and software are ‘Made in Germany’, and tailor-made camera apps provide limitless possibilities for expanding the MOBOTIX 7. This will revolutionize numerous IoT processes — not only for us, but for our technology partners and customers in various markets too,” Sprave said.
The MOBOTIX 7 already comes with pre-installed apps that are verified and certified by MOBOTIX and meet the highest 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 program their own solutions and have these certified by MOBOTIX.
“This means that the range is growing dynamically in response to customers’ needs, so virtually any current and future market requirement can be met with a tailor-made application installed directly on a camera featuring the MOBOTIX 7 platform,” explained Sprave.
The new MOBOTIX video system is also suitable for customers’ 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 immediately and automatically triggers 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 behavior, such as stopping, accelerating, etc, is enabled for traffic and transport applications. The information that is immediately available can improve the road safety for drivers and passengers, while enabling other road users to continue moving in an unobstructed flow.