The following paragraphs provide a summary of the progress beyond the state of the art (SotA) during the second reporting period and potential impact created by the innovations.
iNGENIOUS seeks to optimize logistics using a wealth of data made available by the Internet of Things (IoT). In addition to enabling more comprehensive monitoring, real-time information is used by machine learning (ML) applications to more accurately predict arrival times of sea vessels and trucks to optimise container handling and other operations in maritime ports. Selected real-time information is also used to optimise resource assignment in 5G networks that connect IoT sensors and actuators such as factory robots. Furthermore, the project innovated in IoT devices that enable new use cases, including remote operation of machinery in conditions that are unsafe for humans and monitoring of transportation equipment such as train carriages to increase safety while lowering costs and at the highest security levels.
The project progressed beyond the SotA in the following directions:
a) Development:
At the data management level, iNGENIOUS developed a novel Data Virtualisation Layer (DVL) that aggregates into one unified data pool a myriad of data sources that are, until now, locked into several, incompatible machine-to-machine (M2M) platforms. At the network level, more flexible, reconfigurable, resilient, and resource-aware components were built that enable semiautonomous network slicing and orchestration of the underlying network. At the things level, novel sensors that employ ML techniques to process measurements at the edge were developed, which avoids sending raw data over a network at high cost. A novel computer architecture for highly-secure IoT devices was also developed.
b) Implementation and integration:
Besides creating a standard interface granting security and consistency of the IoT data through M2M interoperability, the project brought together both novel and state-of-the-art technologies, including integration of a variety of radio access technologies (RATs) and communication protocols in a single and unified network level architecture and shared infrastructure to support new IoT use cases. For human-in-the-loop tactile IoT use cases, immersive head-mounted displays, haptic devices, and low-latency 5G networks were integrated for more efficient and safer control of machinery.
c) Security and privacy:
iNGENIOUS took a cross-layer, vertical approach to security and privacy. At the higher levels, data security across the supply chain was improved using manipulation-proof logging of data records using multiple distributed ledger technologies (DLTs) via a single endpoint for interaction, orchestration, and management via smart contracts. DVL ensures pseudonymization of personal information, and security and trust are rooted in IoT devices built using a secure-by-default computer architecture and operating system that enables stronger protection of IoT-to-cloud communication using remote attestation.
d) Validation:
The use cases validated the developed infrastructure components and their interactions according to the project’s test and evaluation plan. iNGENIOUS used real-world data to train new AI and ML models that allow more precise predictions, and hence better optimization of supply-chain and logistics operations, than conventional systems. They also help optimize 5G networks through novel components developed in the project. Field measurement campaigns performed have also been used to optimize novel low-power edge sensors.
e) Dissemination and standardisation:
The project conducted a survey with stakeholders to gather viewpoints and interacted with key industrial actors and academia at dissemination events. iNGENIOUS actively participated and contributed to standardisation bodies, including to 3GPP. Project results were presented at conferences, workshops, and in journals, and promoted in social networks.
