Periodic Reporting for period 2 - iNGENIOUS (Next-GENeration IoT sOlutions for the Universal Supply chain)
Reporting period: 2022-04-01 to 2023-03-31
iNGENIOUS aimed to design and evaluate Next-Generation IoT (NG-IoT) solutions for logistics and supply-chain-scenarios, with a particular emphasis on 5G and the development of edge and cloud computing extensions for IoT. Additionally, it aimed at providing smart networking and data management solutions with AI/ML.
During the last decades, supply chains have become huge networks of individuals, organizations, resources, and activities involved in the creation, delivery, and sale of products to the end users. In such complex environments, the variability and volatility have become major risk factors that companies and organizations must address. To succeed and exploit EU supply-chain actors’ strengths, new technological advances must be used to catalyse the digitalization of supply chain management. This changes how products and services are made and delivered, and enables the creation and sharing of supply chain information in new ways by a more diverse set of actors.
Under this paradigm, iNGENIOUS exploited some of the most innovative and emerging technologies in line with the standardised trend, contributing to the NG-IoT and proposing technical and business enablers to build a complete platform for supply chain management solutions. The project has defined six use cases (UCs) for converging the IoT solutions brought to the NGI scope with the real needs that the next generation supply chain will require:
- Automated Robots with Heterogeneous Networks (Factory UC) - Transportation Platform Health Monitoring (Transport UC) - Situational Understanding and Predictive Models in Smart Logistics (Port Entrance UC) - Improve Driver's Safety with Mixed-Reality and Haptic Solutions (AGV UC) - Inter-Model Asset Tracking Via IoT and Satellite (Ship UC) - Supply Chain Ecosystem Integration (DVL/DLT UC)
During the last decades, supply chains have become huge networks of individuals, organizations, resources, and activities involved in the creation, delivery, and sale of products to the end users. In such complex environments, the variability and volatility have become major risk factors that companies and organizations must address. To succeed and exploit EU supply-chain actors’ strengths, new technological advances must be used to catalyse the digitalization of supply chain management. This changes how products and services are made and delivered, and enables the creation and sharing of supply chain information in new ways by a more diverse set of actors.
Under this paradigm, iNGENIOUS exploited some of the most innovative and emerging technologies in line with the standardised trend, contributing to the NG-IoT and proposing technical and business enablers to build a complete platform for supply chain management solutions. The project has defined six use cases (UCs) for converging the IoT solutions brought to the NGI scope with the real needs that the next generation supply chain will require:
- Automated Robots with Heterogeneous Networks (Factory UC) - Transportation Platform Health Monitoring (Transport UC) - Situational Understanding and Predictive Models in Smart Logistics (Port Entrance UC) - Improve Driver's Safety with Mixed-Reality and Haptic Solutions (AGV UC) - Inter-Model Asset Tracking Via IoT and Satellite (Ship UC) - Supply Chain Ecosystem Integration (DVL/DLT UC)
The work performed in the second half of the project is detailed in the final report. The project has made good progress towards the proposed objectives on the different work categories. The main focus was on IoT technologies, thus most of the effort performed during its lifetime was mostly technical.
This technical work concerned the development of components for each use case, as well as setup, testing, and validation of these components against use case requirements and KPIs previously defined. The tight integration of all technologies in an end-to-end infrastructure was key to enabling the innovative use cases of the project. The cross-layer architecture that enables them is represented in the attached figure. It shows all technical components contributed by partners and how these components work together. The figure highlights which of these components have been improved or newly developed by iNGENIOUS partners, and which are based on existing technologies.
The mapping of architecture components to use cases is as follows:
- Transport UC: vibro-acoustic sensors, secure compute module, 5G satellite, monitoring tools
- Port Entrance UC: sensors in port, AI/ML models for optimizing port operations, visualization tools
- AGV UC: automated guided vehicles, mixed-reality (MR) cockpit and haptic gloves
- Ship UC: sensors in container, smart IoT gateway, 5G satellite
- DVL/DLT UC: Data Virtualization Layer (DVL), Cross-DLT interoperability layer
- All UCs: networking infrastructure, including: 3GPP-and non-3GPP modems, various radio access technologies, 5G Core components, AI/ML-enhanced MANO, M2M platforms
This technical work concerned the development of components for each use case, as well as setup, testing, and validation of these components against use case requirements and KPIs previously defined. The tight integration of all technologies in an end-to-end infrastructure was key to enabling the innovative use cases of the project. The cross-layer architecture that enables them is represented in the attached figure. It shows all technical components contributed by partners and how these components work together. The figure highlights which of these components have been improved or newly developed by iNGENIOUS partners, and which are based on existing technologies.
The mapping of architecture components to use cases is as follows:
- Transport UC: vibro-acoustic sensors, secure compute module, 5G satellite, monitoring tools
- Port Entrance UC: sensors in port, AI/ML models for optimizing port operations, visualization tools
- AGV UC: automated guided vehicles, mixed-reality (MR) cockpit and haptic gloves
- Ship UC: sensors in container, smart IoT gateway, 5G satellite
- DVL/DLT UC: Data Virtualization Layer (DVL), Cross-DLT interoperability layer
- All UCs: networking infrastructure, including: 3GPP-and non-3GPP modems, various radio access technologies, 5G Core components, AI/ML-enhanced MANO, M2M platforms
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.
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.