Leonardo is one of the partners of InSecTT (Intelligent Secure Trustable Things), a European research project funded by the ECSEL (Joint Undertaking Electronic Components and Systems for European Leadership) and coordinated by Virtual Vehicle (Austria). The goal is to develop smart, safe and reliable solutions for European industry throughout the supply chain, bringing together the Internet of Things and artificial intelligence.
Leonardo’s experience in using AI to security and vigilance purposes, as well as electronics will contribute to the development of solutions for smart city public transport and ensure passenger flows at airports, as well as in the surveillance and protection of maritime infrastructure.
The expansion of connected devices and sensors, also known as the Internet of Things, has increased the availability of interconnected systems and data, with a number of benefits in different sectors ranging from manufacturing to critical infrastructure, transportation, automotive and the health
The availability of this enormous amount of data is advancing at the same pace as the development of new Artificial Intelligence (AI) and Machine Learning (ML) algorithms, enabling new applications such as automatic recognition, based on massive data analysis. The other side of the coin is the vulnerability of these devices in terms of security, reducing confidence in this type of technology.
Solving these problems is one of the keys to unlocking the benefits of IoT applications and is in line with the objectives pursued by the EU.
To improve both security and performance in IoT applications, the focus is to bring AI to the edge, that is, to process data locally on a hardware device closer to the sources that generate it. With edge computing, intelligent local processing moves AI from the center of the network (cloud) to the edge, without moving data in the cloud.
Within this context, InSecTT gathers 52 partners of 12 different countries (Europe and Turkey), with the main objectives of developing intelligent, safe and reliable systems, generating trust in systems and solutions and increasing the potential of the ‘artificial intelligence of things‘.
As partner of the consortium, Leonardo leads the use cases for the security of public transport and airports. The company also contributes to a use case for monitoring marine and port infrastructure.
First case of usedirected by Leonardo together eurotech, CINI Y MUSHROOM (Società Emiliana di Trasporti Autofiloviari), deals with the development of three security solutions based on AI applications for public transport in urban environments:
AI-based audio and video anomaly detection systems to increase passenger safety and security
A predictive algorithm to check the condition of vehicles using data from monitoring mechanical components through devices installed on board (predictive maintenance)
Systems to detect road defects, analysis of passenger flow and air quality on board vehicles to improve safety and security.
The second case of usestarring Leonardo with eurotech, CINI me Apulian airports focuses on airport security. In this case, the main objective is the monitoring of airports through four experimental solutions:
A new passenger recognition system to streamline embarkation and disembarkation procedures
Terminal area monitoring using techniques such as artificial vision, audio pattern recognition and detection systems for potentially dangerous substances
Solutions to detect and track suspicious persons who may have the intention of bringing dangerous goods into the airport
Experimental monitoring systems to check the most vulnerable points of the airport
The third case of use aims to develop internet of things solutions for the port and marine environment, providing innovative services for the safe management of commercial and tourist activities. Leonardo’s contribution deals with access control and monitoring of underwater areas around critical infrastructure, through networks of acoustic and magnetic sensors distributed on the seabed to track underwater threats.
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InSecTT has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No. 876038. The JU receives support from the European Union’s Horizon 2020 research and innovation program and from Austria, Sweden, Spain, Italy, France , Portugal, Ireland, Finland, Slovenia, Poland, Netherlands, Turkey.