French Tech Innovation: IN Groupe and Datakalab Make Border Crossings Smarter and More Secure
PARIS,Oct. 12,2021 -- Leading European player,IN Groupe is a trusted partner and a moral guarantee to support citizen identity transformation and corporate assets.
Seamless,fast and secure border crossings,a main concern for countries
Countries are constantly increasing their requirements border controls management,particularly through new regulations. Border crossing must be balanced between high security and a seamless and quick process.
In Europe,this will result in the control of people travelling in the Schengen area,whether they are Europeans or not,with or without a visa.
Thus,it is important to anticipate and provide efficient long-term solutions involving physical and digital identities,while guaranteeing the conditions necessary to protect the sovereignty of countries and associated issues.
IN Groupe and Dakatalab,the way to improve border crossing efficiency
Making border crossings smoother means increasing the use of automated control equipment such as the Parafe systems familiar within Europe.
Trusted partner of countries in the exercising of their sovereignty,IN Groupe has joined forces with French start-up Datakalab to develop a unique intelligent technological solution for automated border control. They plan to integrate their technologies into single-person access checking equipment,used to verify that only one person has actually entered an eGate with interlocking function to pass through a checkpoint. Until now,solutions relied on sensors that were no longer able to take into account these new levels of requirements. This collaboration will offer a more secure,simpler and flexible solution,whose technology is designed to meet a higher level of control.
Artificial Intelligence,a tool to streamline border crossings
IN Groupe and Datakalab have succeeded in developing a solution based on artificial intelligence. This innovation detects a breach of the single person access system,using edge computing technologies to analyze images to enable them to be processed by local neural networks.
The results show much higher performance levels than traditional methods based on single passage detection. In addition,thanks to a built-in iterative learning mechanism,the equipment is made to become even more efficient and smarter. This technology is not only compliant with current regulations (GDPR in particular) but will also adapt to future developments,while maintaining the same flexibility.
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