Intelligent Secure Trustable Things
2020 - 2023
Artificial Intelligence of Things (AIoT) is the natural evolution for both Artificial Intelligence (AI) and Internet of Things (IoT) because they are mutually beneficial. AI increases the value of the IoT through machine learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. Therefore, InSecTT – Intelligent Secure Trustable Things, a pan-European effort with 54 key partners from 12 countries (EU and Turkey), will provide intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together. InSecTT aims at creating trust in AI-based intelligent systems and solutions as a major part of the AIoT, i.e. moving AI to the edge and making AI and ML based systems trustable, explainable and not just a black box.<br> InSecTT will foster cooperation between big industrial players from various domains, a number of highly innovative SMEs distributed all over Europa and cutting-edge research organisations and university. The project features a big variety of industry-driven use cases embedded into various application domains, i.e. smart infrastructure, building, manufacturing, automotive, aeronautics, railway, urban public transport, maritime as well as health. The demonstration of InSecTT solutions in well-known real-world environments like trains, ports, airports and the health sector will generate huge impact on both high and broad level, going from citizens up to European stakeholders. It will establish the EU as a center of intelligent, secure and trustworthy systems for industrial applications enabled by a strong industry with a strong reputation and an informed society, in order to enable products and services based on AI compliant to European values and “Made in Europe".
Our role
We participate in 2 project use cases and 9 tasks all together. Within the indoor localization use case we will develop a smartphone app for the indoor positioning and navigation without communication network available. Within the smart hospital use case we will devekop a patient risk assesment method from his/her biomedical data based on deep learning.
ECSEL / H2020