“Imagination is not only the uniquely human capacity to envision that which is not, and therefore the fount of all invention and innovation. In its arguably most transformative and revelatory capacity, it is the power that enables us to empathize with humans whose experiences we have never shared.” – J. K. Rowling
“It’s always about timing. If it’s too soon, no one understands. If it’s too late, everyone’s forgotten.” – Anna Wintour
Ovidiu VermesanJoël Bacquet
Digital technologies transforming products, | |
Digitising European Industry – working group 2 | |
IoT platform landscape. | |
The pathway of IoT digital transformation. | |
The dynamics of IoT digital age. | |
IoT “neuromorphic” structure. | |
IoT components as part of research, innovation, | |
Distributed and federated heterogenous IoT | |
IoT Research topics addressed at different IoT | |
IoT European large-scale pilots programme. | |
IoT value and benefit paradigm. | |
IoT sensors/actuators map. | |
IoT electronic devices across the architecture | |
IoT connecting people, cities, vehicles, industrial | |
IoT Communication technologies. | |
Wearables system architecture. | |
Wearable electronic market segmentation. | |
Preferred locations for wearable technology. | |
Integrated IoT framework for active and healthy | |
Smart building implementation. | |
Smart Building connected by a Smart Grid. | |
IoT concept for residential buildings using the | |
IoT technologies and the gateway role in microgrids and nanogrids management systems. | |
Energy cloud 2030. | |
Mobility patterns. | |
Replacing sensory functions with technology. | |
Automotive disruption radar globally. | |
IoT centralised and distributed networks – gateway | |
IoT Communication topologies across the | |
Wi-Fi Network – Mobile data consumed by network | |
Gateway trade-off – data rate vs. range. | |
Network requirements – un-balance and | |
LPWA, NB-IoT and LTE-M for low data rates IoT | |
Smart contracts on the left-hand side and | |
IoT Platforms covering the data value chain. | |
Implementation elements in the main areas covered by IoT platforms. | |
From a centralised cloud to distributed edge IoT | |
Communication protocols used by different IoRT | |
Architecture of an IoRT learning system | |
Blockchain – Payment process – Current vs | |
Blockchain-Enabled convergence framework. | |
Three levels of blockchain. | |
Different types of robots share the blockchain | |
IoRT layered architecture. | |
A conceptual architecture for the IoRT. | |
Robotic system and its relations with robot | |
Conceptual model of a marketplace for an IoRT | |
Robots classification per application areas | |
STARTS Ecosystem. | |
STARTS Prizes 2016 and 2017. | |
VERTIGO artistic residencies. | |
European Large-Scale Pilots Programme. | |
Future STARTS lighthouse pilots – catalysts | |
Different levels of artistic collaboration | |
IoT SDOs and Alliances Landscape. | |
AIOTI three layers’ functional model. | |
The traditional manufacturing pyramid. | |
Cyber Physical Production Systems. | |
Identifiers examples in the IoT Domain Model | |
ARMOUR Security Framework. | |
Positioning of ARMOUR experiments over IoT | |
ARMOUR Model Based Security Testing | |
Security Test Patterns definition methodology. | |
ARMOUR overall test environment. | |
End-to-End security description. | |
Large-Scale End-to-End scenario. | |
ARMOUR benchmarking methodology | |
Test pattern template associating security | |
Certification execution levels. | |
Association between security properties and marks based on metrics. | |
Marks for likelihood and impact parameters. | |
Proposed IoT EU Security Certification | |
Combination of security and privacy | |
IoT European Large-Scale Pilots Programme | |
ACTIVAGE Deployment Sites in 7 EU countries. | |
ACTIVAGE uses cases distribution. | |
Mapping of needs and use cases. | |
Model of AHA-IoT ecosystem. | |
Conceptual architecture of AIOTES. | |
Illustrative story of the vision on IoT | |
Geographical coverage of the IoF2020 trials | |
The IoF2020 architectural process to ensure | |
IoF2020 Project approach and structure. | |
An example of the type of open air events that | |
Hamburg DOM is Northern Germany’s biggest | |
The overall MONICA concept. | |
MONICA IoT Architecture. | |
SynchroniCity cities and regions. | |
Street light in Santander. | |
High level architectural view of the SynchroniCity | |
Interactive light art in Eindhoven. | |
The SynchroniCity contribution to standards | |
Project flow. | |
IoT European Large-Scale Pilots Programme | |
CREATE-IoT activities. | |
CREATE-IoT project axes. | |
U4IoT overall concept. | |
U4IoT General Methodology. | |
Basic concept of TagItSmart project. | |
The TagItSmart use cases under the Digital product | |
The idea of Digital product use case. | |
The idea of Lifecycle management use case. | |
The idea of Brand protection use case. | |
The idea of Dynamic pricing use case. | |
The idea of Home services use case. | |
TagItSmart Platform functional architecture. | |
D code with sensor area. | |
Data Matrix code with two functional inks. Code | |
Printed tag with an inkjet printed photochromic ink | |
The PICs are produced on stainless steel sheets. | |
Architecture of the authentication system | |
Examples of SmartTags being successfully decoded | |
Dynamic pricing scenario; different price calculated |
IoT open platform architecture requirements | |
Some standards gaps and their perceived | |
Standards gaps mapped on the AIOTI HLA | |
List of defined vulnerabilities | |
Vulnerabilities overview | |
Overview of Pilot Cities and Events | |
AUTOPILOT project sites and applications | |
IoT based automated driving services |
Source: VisionMobile 2015.
Source: Google.
Acronym | Meaning |
3GPP | 3rd Generation Partnership Project |
API | Application Programming Interface |
ARM | Architecture Reference Model |
Bluetooth | Proprietary short range open wireless technology standard |
BUTLER | EU FP7 research projectuBiquitous, secUre inTernet of things with Location and contExt-awaReness |
CAGR | Compound annual growth rate |
DoS/DDOS | Denial of service attackDistributed denial of service attack |
EC | European Commission |
ESOs | European Standards Organisations |
ESP | Energy Service Provider |
ETSI | European Telecommunications Standards Institute |
EU | European Union |
FP7 | Framework Programme 7 |
GS1 | Global Standards Organization |
IBM | International Business Machines Corporation |
ICT | Information and Communication Technologies |
iCore | EU research projectEmpowering IoT through cognitive technologies |
IERC | European Research Cluster for the Internet of Things |
IETF | Internet Engineering Task Force |
IoB | Internet of Buildings |
IoE | Internet of Energy |
IoT | Internet of Things |
IoT6 | EU FP7 research projectUniversal integration of the Internet of Things through an IPv6-based service oriented architecture enabling heterogeneous components interoperability |
IoT-A | Internet of Things Architecture |
IoT-I | Internet of Things Initiative |
IoV | Internet of Vehicles |
IP | Internet Protocol |
IPv6 | Internet Protocol version 6 |
LTE | Long Term Evolution |
M2M | Machine to Machine |
MIT | Massachusetts Institute of Technology |
OASIS | Organisation for the Advancement of Structured Information Standards |
OpenIoT | EU FP7 research projectPart of the Future Internet public private partnership Open source blueprint for large scale self-organizing cloud environments for IoT applications |
PAN | Personal Area Network |
PET | Privacy Enhancing Technologies |
PPP | Public-private partnership |
PV | Photo Voltaic |
SENSEI | EU FP7 research projectIntegrating the physical with the digital world of the network of the future |
SmartAgriFood | EU ICT FP7 research projectSmart Food and Agribusiness: Future Internet for safe and healthy food from farm to fork |
SmartSantander | EU ICT FP7 research projectFuture Internet research and experimentation |
SRIA | Strategic Research and Innovation Agenda |
TC | Technical Committee |
W3C | World Wide Web Consortium |
ZigBee | Low-cost, low-power wireless mesh network standardbased on IEEE 802.15.4 |
Z-Wave | Wireless, RF-based communications technology protocol |
Authentication and authorization | Support multi-layer authentication and authorization |
Auto-configuration | Support auto-configuration that allows the IoT system to react to the addition and removal of components such as edge devices and networks. |
Autonomous management | Support self-configuring, self-optimizing, self-healing, self-protecting capabilities, for adapting to various application domains, different communication environments, different numbers and types of edge devices. |
Compliant components | Support the connection and integration of various heterogeneous set of components performing differing functions based on stakeholders’ and applications requirements. Architectural support for discovery and use of components whose characteristics are known and described using standardized semantics and syntaxes. |
Cognitive and Artificial Intelligence | Support the cognitive and artificial intelligence components, processes and operations at different IoT architectural layers including end-to-end security. |
Privacy and confidentiality | Support for privacy and confidentiality of IoT applications. Possibility to address to scale the solutions and offer context-based implementations. |
Content-awareness | Support content-based awareness to enable and facilitate services for path selection and routing of communications, or configuration decisions based on content. |
Context-awareness | Support context-based awareness that enable flexible, user-customized and autonomic services based on the related context of IoT components and/or users. The context-based information forms the basis for taking actions in response to the current situation, possibly using sensors and actuators information. |
Data analytics | Support for analytics components performed at the different IoT layered architecture, cloud or edge including real-time, batch, predictive, and interactive analytics. The real-time analytics conduct online (on-the-fly) analysis of the streaming data. Batch analytics runs operations on an accumulated set of data. Predictive analytics focusing on making predictions based on various statistical and machine learning techniques. Interactive analytics runs multiple exploratory analysis on both streaming and batch data. |
Data collection protocols | Support for various types of protocols used for data communication between the components of an open IoT platform that need to be scaled to large number of heterogeneous edge devices. Lightweight communication protocols used to enable low energy use as well as low network bandwidth functionality. |
Discovery services | Support discovery services across domains and applications for IoT users, services, capabilities, devices and data from devices to be discovered according to different criteria, such as geographic location information, type of device, etc. |
Distributed end-to-end security | Support an end-to-end framework for security with secure components, communications, access control to the system and the management services and data security. Physical, digital, virtual and cyber security aspects need to be considered. Support for blockchain components and distributed implementations. |
Heterogeneity | Support heterogeneous devices and networks with different types of edge devices regarding communication technology, computing capabilities, storage capability and mobility, different service providers and different users and support interoperability among different networks and operating systems. Support for universal, global-scale connectivity including legacy system interworking. |
Location-awareness | Support for IoT components that interact with the physical world and require awareness of physical location, while the accuracy requirement for location is based upon the application. Components describe their locations, and the associated uncertainty of the locations. |
Manageability | Support management capabilities to address aspects such as data management, device management, network management, and interface maintenance and alerts. Availability of lists of edge devices connected to the IoT platform, while tracking the operation status, handle configuration, firmware updates, and provide device level error reporting and error handling. |
Modularity | Support components that can be combined in different configurations to form various IoT systems. Standardized interfaces for providing flexibility to implementers in the design of components and IoT systems. |
Monetization | Support for monetization of functionalities of robots is crucial as an incentive for ecosystem participation. Examples for such monetization range from micro payments for ordering the help of a service robot at an airport, to ordering a fully customized manufacturing process at an automated plant. Besides the monetization of functionalities and services of robots, the data collected by robots can be monetized as well. For both aspects, functionalities and data, concepts and mechanisms for monetization, such as an ecosystem-wide |
Network connectivity | Support connectivity capabilities, which are independent of specific application domains, and integration of heterogeneous communication technologies needs to be supported to allow interoperability between different IoT devices and services. Networked systems may need to deliver specific Quality of Service (QoS), and support time-aware, location-aware, context-aware and content-aware communications |
Openness | Support IoT platforms openness, based on standardised, interoperable solutions allowing any edge device, from any IoT platform, to be able to connect and communicate with one another. |
Regulation compliance | Support compliance with relevant application domain specific regulations and regional requirements. |
Reliability | Support the appropriate level of reliability for communication, service and data management capabilities to meet system requirements. Provide resilience and support the ability to respond to change due to external perturbations, error detection and self-healing. |
Risk management | Support operational resilience under normal, abnormal and extreme conditions. |
Scalability | Support a large range of applications varying in size, complexity, and workload. Support systems integrating evolving sensing, actuating, energy harvesting, networking, interface technologies, involving a large number of heterogeneous edge devices, applications, users, significant data traffic volumes, frequencies of event reporting etc. Provisions for components that are used in simple applications to be usable in large-scale complex distributed IoT systems. |
Shared vocabularies | To be able to build up ecosystems of robots and IoRT platforms, it is crucial to establish shared vocabularies as a basis for interweaving them and enabling collaboration. Thereby, such shared vocabularies are needed wherever data is serialized and transmitted or exchanged.The types, terms and concepts in the data (e.g., measured data, metadata, authorization data) need to be defined and these definitions should be part of documented vocabularies so that they can be correctly (re)used. |
Standardised interfaces | Support standardised interfaces to the platforms components at different architectural layers based on established, interpretable, and unambiguous standards. Standardized web services for accessing sensors/actuators information, sensors observations and actuators actions. |
Support for legacy components | Support legacy component integration and migration, while new components and systems are designed considering that present or legacy aspects do not unnecessarily limit future system evolution. Legacy components integrations need to ensure that security and other essential performance and functional requirements are met. |
Time-awareness | Support for event management including time synchronicity among the actions of interconnected components by using communication and service capabilities. Time stamp associated to a time measurement from the physical world and combine or associate data from multiple sensors/actuators and data sources. |
Timeliness | Support timeliness, in order to provide services within a specified time for addressing a range of functions at different levels within the IoT system. |
Unique identification | Support standardised unique identification for each component of the IoT (e.g. edge devices and services) to provide interoperability, support services (i.e. discovery and authentication across heterogeneous networks) and address object identity management. |
Usability | Plug and Play capabilities to enable on-the-fly, on-the-air generation, composition or the acquisition of semantic-based configurations for seamless integration and cooperation of interconnected components with applications, and responsiveness to application requirements |
Virtualisation | Virtualisation of edge objects, networks and layers. |
“Artists should be incorporated as catalysts for new ways of thinking, not only about art, but about the world we live in, to change the way things are done, made and developed in the world.” Camille Baker, FET-Art Project
State of the art security – Costs – Purposes + Impact
Nature of the Gap | Type | Criticality |
Competing communications and networking technologies | Technical | Medium |
Easy standard translation mechanisms for data interoperability | Technical | Med |
Standards to interpret the sensor data in an identical manner across heterogeneous platforms | Technical | High |
APIs to support application portability among devices/terminals | Technical | Medium |
Fragmentation due to competitive platforms | Business | Medium |
Tools to enable ease of installation, configuration, maintenance, operation of devices, technologies, and platforms | Technical | High |
Easy accessibility and usage to a large non-technical public | Societal | High |
Standardized methods to distribute software components to devices across a network | Technical | Medium |
Unified model/tools for deployment and management of large scale distributed networks of devices | Technical | Medium |
Global reference for unique and secured naming mechanisms | Technical | Medium |
Multiplicity of IoT HLAs, platforms and discovery mechanisms | Technical | Medium |
Certification mechanisms defining “classes of devices”? | Technical | Medium |
Data rights management (ownership, storage, sharing, selling, etc.) | Technical | Medium |
Risk Management Framework and Methodology | Societal | Medium |
Gap | Impact |
Competing communications and networking technologies | Network layer |
Easy standard translation mechanisms for data interoperability | IoT and application layers |
Standards to interpret the sensor data in an identical manner across heterogeneous platforms | IoT layer |
APIs to support application portability among devices/terminals | IoT layer |
Fragmentation due to competitive platforms | Not specific to HLA |
Tools to enable ease of installation, configuration, maintenance, operation of devices, technologies, and platforms | Mostly IoT layer, also Appl. and Network |
Easy accessibility and usage to a large non-technical public | Not specific to HLA |
Standardized methods to distribute software components to devices across a network | IoT and network layers |
Unified model/tools for deployment and management of large scale distributed networks of devices | All layers; critical in IoT layer |
Global reference for unique and secured naming mechanisms | All layers |
Multiplicity of IoT HLAs, platforms and discovery mechanisms | Addressed by HLA |
Certification mechanisms defining “classes of devices” | Network layer |
Data rights management (ownership, storage, sharing, selling, etc.) | All layers |
Risk Management Framework and Methodology | All layers; interface definition |
Id | Title |
V1 | Discovery of Long-Term Service-Layer Keys Stored in M2M Devices or M2M Gateways |
V2 | Deletion of Long-Term Service-Layer Keys stored in M2M Devices or M2M Gateways |
V3 | Replacement of Long-Term Service-Layer Keys stored in M2M Devices or M2M Gateways |
V4 | Discovery of Long-Term Service-Layer Keys stored in M2M Infrastructure |
V5 | Deletion of Long-Term Service-Layer Keys stored in M2M Infrastructure equipment |
V6 | Discovery of sensitive Data in M2M Devices or M2M Gateways |
V7 | General Eavesdropping on M2M Service-Layer Messaging between Entities |
V8 | Alteration of M2M Service-Layer Messaging between Entities |
V9 | Replay of M2M Service-Layer Messaging between Entities |
V10 | Unauthorized or corrupted Applications or Software in M2M Devices/Gateways |
V11 | M2M System Interdependencies Threats and cascading Impacts |
V12 | M2M Security Context Awareness |
V13 | Eaves Dropping/Man in the Middle Attack |
V14 | Transfer of keys via independent security element |
V15 | Buffer Overflow |
V16 | Injection |
V17 | Session Management and Broken Authentication |
V18 | Security Misconfiguration |
V19 | Insecure Cryptographic Storage |
V20 | Invalid Input Data |
V21 | Cross Scripting |
Test Pattern ID | Test Pattern Name | Related Vulnerabilities |
Resistance to an unauthorized access, modification or deletion of keys | V1, V2, V3, V4, V5 | |
Resistance to the discovery of sensitive data | V6 | |
Resistance to software messaging eavesdropping | V7 | |
Resistance to alteration of requests | V8 | |
Resistance to replay of requests | V9 | |
Run unauthorized software | V10 | |
Identifying security needs depending on the M2M operational context awareness | V12 | |
Resistance to eaves dropping and man in the middle | V13 | |
Resistance to transfer of keys via of the security element | V14 | |
Resistance to Injection Attacks | V16 | |
Detection of flaws in the authentication and in the session management | V17 | |
Detection of architectural security flaws | V18 | |
Detection of insecure encryption and storage of information | V19 | |
Resistance to invalid input data | V20 |