6.2 Glossary

The scope of the ECS SRIA is very broad and spans many disciplines, each of which has developed a specific understanding of some of the terms used in this report. As a result, the same term can have different meanings for specialists in different ECS domains. This glossary defines some of those terms in an exclusive way to ensure there are no inconsistencies across the various chapters. Although there may be readers that feel uncomfortable with a few of the definitions provided here if they differ from what they commonly mean in their own areas, we feel that developing a common language is important in building a strong and integrated ECS community.

2D materials: materials that can be obtained in a single or very few monolayers, and whose advantageous properties derived from this fact; as opposed to much thicker 'thin films', and even thicker 'bulk materials'

3D integration: a vertical stack of circuitry or integrated circuits (ICs) for meeting electronic device requirements such as higher performance, increased functionality, lower power consumption, and a smaller footprint. In general, 3D integration is a broad term that includes technologies such as: 3D wafer-level packaging; 2.5D and 3D interposer-based integration; 3D stacked ICs (3D-SICs), monolithic 3D ICs; 3D heterogeneous integration; and 3D systems integration.

3D printing: also known as additive manufacturing, this is the construction of a three-dimensional object from a computer-aided design (CAD) model or digital 3D model. The term “3D printing” can refer to a variety of processes in which materials are deposited, joined or solidified under computer control to create a three-dimensional object, with typically the materials (such as liquid molecules or powder grains being fused together) being added on a layer-by-layer basis.

5G: fifth-generation wireless (5G) is the latest iteration of cellular technology, engineered to greatly increase the speed and responsiveness of wireless networks. With 5G, data transmitted over wireless broadband connections can travel at multi-gigabit speeds, with potential peak speeds as high as 20 gigabits per second (Gbps) by some estimates. These speeds exceed wireline network speeds and offer latency of 1 millisecond (ms) or lower, which is useful for applications that require real-time feedback. 5G will enable a sharp increase in the amount of data transmitted over wireless systems due to more available bandwidth and advanced antenna technology. 5G networks and services will be deployed in stages over the next few years to accommodate the increasing reliance on mobile and internet-enabled devices. Overall, 5G is expected to generate a variety of new applications, uses and business cases as the technology is rolled out.

6G: (sixth-generation wireless) is the successor to 5G cellular technology. 6G networks will be able to use higher frequencies than 5G networks and provide substantially higher capacity and much lower latency. Millimeter waves (30 to 300 GHz) and terahertz radiation (300 to 3000 GHz) will most likely be used in 6G. Hundreds of gigabits per second transmission rates will be obtained. One of the important goals of the 6G internet is to support one microsecond latency communications. Artificial Intelligence will be important in designing and optimizing 6G architectures, protocols, and operations.

Advanced Packaging : suite of novel technologies, processes and competences that in a cost-and resource-efficient way allows the physical, electrical and functional integration of any set of technological diverse components required to build an advanced electronic system.

Ambient Assisted Living (AAL): information and communication-based products and services that integrate modern technologies (sensors, microcontrollers, connectivity, secure elements, Artificial Intelligence, etc) into the homes and lives of disabled persons, and vulnerable or older adults. These technologies aim to improve the lives of those facing some of the challenges of ageing, and those who care for older people if they need help. An impact of AAL is also in reducing the costs of health and social care.

Artificial Intelligence (AI): the theory and development of information processing systems able to perform tasks usually requiring human intelligence (such as visual perception, speech recognition, decision-making, and translation between languages) with a certain degree of autonomy. Currently, Large language models, or LLMs have received most attention in AI. They are a type of AI that can mimic human intelligence. They use statistical models to analyze vast amounts of data, learning the patterns and connections between words and phrases.

Augmented reality (AR): an interactive experience of a real-world environment where the objects that reside in the real world are enhanced by computer-generated perceptual information, sometimes across multiple sensory modalities, including visual, auditory, haptic, somatosensory and olfactory.

Autonomous system (AS): performs desired tasks in unstructured environments without continuous human guidance.

Biologic drugs: products that are produced from living organisms or contain components of living organisms. Biologic drugs include a wide variety of products derived from human, animal or microorganisms by using biotechnology. Types of biologic drugs include vaccines, blood, blood components, cells, allergens, genes, tissues and recombinant proteins.

Blockchain: decentralised, chronologically updated database with a consensus mechanism created from a network for the permanent digital securitisation of property rights.

Brain–computer interface (BCI): a direct communication interface between a (biological) brain and a technical (IT- and/or ECS-based) system. A BCI can transfer information in both directions – e.g. enabling the brain to control the technical system or enhancing human perception (such as hearing) with additional information from the technical system (e.g. hearing aid).

Care pathway: the sequence of health and care services a patient receives after entering the care systemduring an episode of care.

Cath lab: examination room in a hospital or clinic with diagnostic imaging equipment used to visualise thearteries of the heart and the chambers of the heart.

Cloud: the on-demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct active management by the user. The term is generally used to describe data centres available to many users over the internet (from Wikipedia).

Component: a combination of devices and other elements (such as passives) that fulfil a specific need, such as transduction of a single physical parameter within a well-specified case. A component is not self-contained in all its functions, as it requires the close support of other components for operation (e.g. in data processing, power handling, embedded software).

Computer-aided design (CAD): the use of computers (or workstations) to aid in the creation, modification, analysis or optimisation of a design. CAD software is used to increase the productivity of the designer, improve the quality of design, improve communications through documentation, and to create a database for manufacturing.

Conformal electronics: newly developed microelectronics that overcome the standard planar paradigm and can be prepared on arbitrary curvilinear surface.

Contract-based design: a design methodology where the system, itself as well as its constituents (subsystems, components, modules, etc), are described by contracts that are formalised by specifications of their functional behaviour and properties. This is often given in a “assume-guarantee” format (e.g. for a certain software module a contract could be: “If the other components of the system guarantee the availability of input data at certain, well-defined times and if the hardware platform on which this module is running guarantees the availability of certain processing and memory resources (assumptions), then (guarantee) this module will produce its output within a certain, guaranteed time interval”). In this methodology, a designed system is “correct” if (informally): (i) all assumptions of all constituents are met by guarantees of other constituents; and (ii) the contracts of all constituents together imply the contract of the complete system.

Coopetition: a neologism for the act of cooperating and competing at the same time. Companies that compete in the market with their products might still cooperate on topics that are either pre-competitive or non-product differentiating. Typical examples here are interoperability, standards and development processes.

Cyber-physical system (CPS): an ECS in which a physical artefact is controlled or monitored by algorithms. A CPS is the result of tight intertwined hardware and software components capable of creating a link between the physical world and the digital world, to operate on different spatial and temporal scales, exhibit multiple and distinct behavioural modalities, and interact with each other in ways that depend on the context. Examples of CPS include smart grid, autonomous automobile systems, medical monitoring, industrial control systems, robotics systems and automatic pilot avionics.

Cybersecurity: the protection of information against unauthorised disclosure, transfer, modification or destruction, whether accidental or intentional (IEC 62351-2).

Deep edge: the farthest extreme node where subsystems (sensors, actuators, data loggers) interface with the real world. This node is connected to the cloud, but the connection can be intermittent or absent for long periods of time. The emergence of “tiny machine learning” is based on this premise to enable AI in performance-constrained environments (ultra-low power, limited memory size and calculation power), but always very close to the subsystem.

Deep learning (DL): a special form of machine learning based on artificial neural networks, DL is where the system is able to automatically discover the representations needed for feature detection or classification from raw data. The adjective “deep” in deep learning comes from the use of multiple layers in the network (from Wikipedia).

Deeply embedded software: software that runs on dedicated hardware and not on standard microprocessors. In its simplest form, it is called “firmware”.

Dependability: according to IEC 60050-192:2015, dependability (192-01-22) is the ability of an item to perform as and when required. An item here can be a device, component, module or system. Dependability includes availability (192-01-23), reliability (192-01-24), recoverability (192-01-25), maintainability (192-01-27) and maintenance support performance (192-01-29), and in some cases other characteristics, such as durability (192-01-21), safety and security. A more extensive description of dependability is available from the IEC technical committee on dependability (IEC TC 56).

Development or design tools, development or design frameworks, design flow: design tools are software tools supporting engineers with different tasks during system designs. Ideally, these tools are integrated into frameworks that: (i) provide a uniform user interface to all tools; (ii) “sort” the tools according to the different steps in the design process; and (iii) ensure interoperability between the integrated tools. Regardless of whether the tools used are integrated into a framework or not, the order in which the tools are used is called the “design flow”.

Device: in the context of the SRIA, and if it is not further qualified, a device will designate a “packaged chip”, whether it is a packaged integrated circuit (e.g. system on a chip, memory, processor, microcontroller) or a micro-electromechanical system (MEMS)/micro-opto-electro-mechanical system (MOEMS). A device performs a general electrical, electronic or electrical/electronic-physical transduction role.

Digital infrastructure: foundational services necessary to the IT capabilities of a nation, region, city or organisation.

Digital Product Passport: digital identity of a physical product gathering information about the entire product lifecycle.

Digital twin: a digital replica of a living or non-living physical entity. Digital twin refers to a digital replica of potential and actual physical assets, processes, people, places, systems and devices that can be used for various purposes. The digital representation provides both the elements and the dynamics of how the physical entity operates and “lives” throughout its lifecycle. To be useful in systems engineering, digital twins need to be executable (i.e. engineers must be able to use them in simulations as representatives of the actual physical entity) and/or amendable to formal analysis methods. The more aspects of the physical entity are represented in a digital twin, the more useful it becomes.

Divide and conquer strategy: a strategy in systems engineering where a large problem (i.e. designing and building a complex system or even System of Systems) is iteratively broken down (“divided”) into smaller problems (i.e. designing subsystems, modules and components), which are then divided further or solved (“conquered”). The results of each step are then integrated into a solution for the next-level larger problem. Divide and conquer typically leads to hierarchical designs; it is also a strategy well suited for distributed developments within supply chains and platform economies.

Edge computing: a computing paradigm where computation and data storage are close to the location where they are needed, to improve response times, save bandwidth and increase independence. It can also include the gateway between deep edge devices and other edge devices (organised in a federation of devices, see fog computing), or with the cloud (modified from Wikipedia).

Embedded (or edge) high-performance computing: provides supercomputing processing performance in rugged, compact and easily deployable computing architectures optimised to work in harsh environments in the field. Bringing high-performance computing capabilities from data centres to field-deployable applications means reducing space, weight and power absorption, increasing resistance, robustness and reliability while maintaining the same advanced computational performance and energy efficiency. Embedded (or edge) high-performance computing is an enabling technology for many vertical domains, such as autonomous driving, UAV, and security and surveillance systems.

Embedded software: the software that runs on embedded and cyber-physical systems, providing the low-level functionalities required to use the available hardware resources, dedicated operating systems, run-time environments, virtualisation and containerisation platforms, application software, micro-services, etc. Embedded software is specifically conceived to optimally exploit the limited hardware resources of embedded and cyber-physical systems. For deeply embedded software, see the separate definition.

Embedded system: an ECS generated from the combination of a microprocessor(s), GPUs or system on a chip, memory, input/output peripheral devices and embedded software that have a dedicated function within a larger mechanical or electrical system.

Extended reality (XR): refers to all real and virtual combined environments and human–machine interactions generated by computer technology and wearables, where the “X” represents a variable for any current or future spatial computing technologies.

Fog computing: an architecture that uses edge devices to carry out a substantial amount of computation, storage and communication locally, and routed over the internet backbone (from Wikipedia).

Functional safety: the ability of a system or piece of equipment to control recognised hazards to achieve an acceptable level of risk – such as maintaining the required minimum of operation even in case of likely operator errors, hardware failures and environmental changes – to prevent physical injuries or damages to the health of people, either directly or indirectly.

Prosthetics: the branch of medicine or surgery that deals with the production and application of artificial body parts.

Healthcare: the preservation of mental and physical health by preventing or treating illness through services offered by the health profession.

Heterogeneous integration: refers to the integration of separately manufactured components into a higher-level assembly (system in a package) that, in the aggregate, provides enhanced functionality and improved operating characteristics. In this definition, components should be taken to mean any unit, whether individual die, MEMS device, passive component or assembled package or subsystem, that are integrated into a single package. The operating characteristics should also be taken in its broadest meaning to include characteristics such as system-level performance and cost of ownership (from ITRS Assembly & Packaging chapter).

Industry 4.0: the application of technology to digitally transform how industrial companies operate. These technologies include the industrial Internet of Things (IoT), automation and robotics, simulation, additive manufacturing, and analytics. Industry 4.0 is driven by a need to boost efficiency, become more agile to respond to market unpredictability, improve quality, and to enable new business models.

In silico clinical trials: in silico means performed on a computer or via computer simulation. The term characterises biological experiments carried out entirely on a computer. Although in silico studies represent a relatively new avenue of inquiry, they have begun to be used widely in studies that predict how drugs will interact with the body and with pathogens.

In vitro diagnostics: the technique of performing a given procedure in a controlled environment outside of a living organism. Many experiments in cellular biology are conducted outside of organisms or cells. One of the abiding weaknesses of in vitro experiments is that they fail to replicate the precise cellular conditions of an organism, particularly a microbe.

In vivo clinical trials: experimentation using a whole living organism as opposed to a partial or dead organism. Animal studies and clinical trials are two forms of in vivo research. In vivo testing is often employed over in vitro because it is better suited for observing the overall effects of an experiment on a living subject. Integrated practice unit: Involves a shift from the current siloed organisation by specialty department and discrete service to being organised around the patient’s medical condition. Care is delivered by a dedicated multidisciplinary team of clinicians who take responsibility for the full cycle of care for the condition, encompassing outpatient, inpatient, and rehabilitative care, and supporting services (e.g. nutrition, social work, behavioural health). The team measures processes and outcomes as a team not individually, and accepts joint accountability for outcomes and costs.

Integrated circuit: an electronic circuit formed on a small piece of semiconducting material, performing the same function as a larger circuit made from electronic building blocks.

Integrated Photonics: technology that in a microchip embodiment produces systems that detect, generate, transport and process light.

Integration platform: an ECS allowing the integration of different systems, applications and services into a single system. They can be found on all layers of the design hierarchy, ranging from “communication backplanes” in hardware design to “reference architectures” and “middlewares” in system engineering, to distributed service platforms in System of Systems. Integration platforms are an important basis for: (i) standardisation; and (ii) platform-based economies.

Internet of Things (IoT): the set of technologies that bring intelligence to objects, enabling them to communicate with other objects or with other devices. IoT describes the network of physical objects – “things” – that perform functions. For example, with these technologies, billions of sensors embedded in everyday devices can be designed to record, process, store and transfer data, and to interact with other devices or systems that use the network's capabilities.

Interoperability: the capability of computing systems to exchange information that can be understood and used by the receiving system.

Key digital technologies: electronic and photonic components, and the software that defines how they work. These technologies underpin all digital systems, including Artificial Intelligence and the Internet of Things.

Lab-on-a-chip (LOC): a miniaturised device that integrates one or several biological or chemical analysis functions on a single chip (e.g. detecting specific proteins).

Large-area electronics (LAE): electronics fabricated utilising printing and roll-to-roll fabrication methods that, as opposed to integrated circuit technologies, can be used on significantly larger substrates. Inorganic and organic inks and pastes are used for printing conductors and active components such as transistors. Substrates in LAE are typically flexible, such as plastic films or paper, giving rise to the term “flexible electronics”.

Large Language Model (LLM): A large language model is a type of language model notable for its ability to achieve general-purpose language understanding and generation. LLMs acquire these abilities by using massive amounts of data to learn billions of parameters during training. LLMs are artificial neural networks (mainly transformers) and are (pre-)trained using self-supervised learning and semi-supervised learning.

Machine learning: ability for a machine to learn by example without being explicitly programmed to perform the target function. This is one method for implementing Artificial Intelligence.

MEMS, MOEMS, NEMS, MNS, MNBS: micro-electromechanical systems (MEMS) originally referred to miniaturised devices that provided a precise mechanical output (typically a small vertical, horizontal, or rotary displacement) upon an electric excitation (e.g. a microrelay), or vice versa, or an electronic signal from a mechanical excitation (e.g. a microaccelerometer or gyroscope). When the objective of such displacement was to interact with light (e.g. a micromirror), the term “micro-opto-electromechanical systems (MOEMS) was used. Gradually, the transduction domain was extended beyond the mechanical one and chemical and biological mediation were also considered. The overall size of MEMS devices could be in the mm or cm range, the term “micro” referring to the dimension of the device’s internal features to be mastered for the device to be functional. The term “nanoelectromechanical systems” (NEMS) is used when such critical dimension falls back into the nano domain. The terms “microsystem”, “micro-nanosystem” (MNS), or “micro-nano-bio system” (MNBS) were alternatively introduced for those small devices amenable to such generalised transduction principles. This kind of device could be fabricated in principle with different materials, but silicon technologies provided a micromachinable material and a miniaturised technology responsive to the integration of the electronic signal to be conveyed or transduced. MEMS, MOEMS, NEMS, MNS and MNBS are very successful means of interaction between the physical and digital worlds, providing information systems with the means to interact with their environment, sensing it, actuating on it or being powered by it.

Model-based design: where design artefacts (the system, subsystems, component, modules, as well as their connections and the environments in which they will be used), are represented by models that are abstract descriptions of certain aspects of such artefacts (typically, their functional behaviour, timing properties, etc). Ideally, these models are: (i) executable, thus usable in simulation and early verification and validation (V&V); and (ii) detailed enough to be usable in formal analysis and test methods.

Module: ensemble of properly integrated components so that their reunion embodies a definite functionality required for the proper working of a system (e.g. sensing and actuation module, control module, communication module, energy provision module). A module is self-contained in hardware and software, making it interchangeable between systems, and allowing higher abstraction level in systems design.

Molecular biology: study of phenomena in terms of biology molecular (or chemical) interactions. Molecular biology emphasises chemical interactions involved in the replication of DNA, its “transcription”: into RNA, and its “translation” into or expression in protein – that is, in the chemical reactions connecting genotype and phenotype.

Open source hardware: the blueprint of hardware artefacts that is (partially) freely available and which anyone can use, modify or enhance (depending on different licences associated with the blueprint).

Open source software: software with source code that is (partially) freely available and which anyone can use, modify or enhance (depending on different open source licensing models existing).

Operational design domain (ODD): comprises the “operating conditions under which a given […] system or feature thereof is specifically designed to function, including, but not limited to, environmental, geographical, and time-of-day restrictions, and/or the requisite presence or absence of certain [environmental] characteristics” (Surface Vehicle Recommended Practice — Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. SAE: J3016, 2018).

Optical coherence tomography (OCT): a non-invasive imaging test that uses light waves to take cross-section pictures of the retina to help with diagnosis. They also provide treatment guidance for glaucoma and diseases of the retina such as age-related macular degeneration (AMD) and diabetic eye disease.

P4 medicine: a shift in medicine from a reactive to a proactive discipline that is focused on predictive, personalised, preventive and participatory (P4). P4 medicine will be driven by system approaches to disease, emerging technologies and analytical tools.

Patient-generated health data (PGHD): health-related data created, recorded or gathered by or from patients (or family members or other caregivers) to help address a health concern.

Personalised medicine: tailoring of medical treatment for patient cohorts to be treated in a unique manner depending on their health status and previous course of a disease and analysis of personal characteristics.

Photonics: Photonics is the science and technology of light. It encompasses generating, guiding, manipulating, amplifying and detecting light. Photonic components process photons (light) analogous to electronic components processing of electrons. A photonic integrated circuit (PIC) or integrated optical circuit is a microchip containing two or more photonic components which form a functioning circuit.

Plug and play components: component with a specification that facilitates the discovery of a hardware component in a system without the need for physical device configuration or user intervention in resolving resource conflicts.

Point of care: the location at which patient services are delivered (excluding hospital, doctor’s office, patient’s home).

Point-of-care testing (POCT or bedside testing): performance of clinical laboratory testing at the site of patient care rather than in a laboratory, often by non-laboratorians.

Point of need: new model of having critical data and information when and where it is needed rather than at the point of care. These are diagnostics that can be done anytime, anywhere, for anyone – for instance, as a vital part of managing a chronic disease over time, resulting in improved treatment and patient outcomes.

Predictive maintenance: techniques designed to help determine the condition of in-service equipment to estimate when maintenance should be performed.

Product lifecycle management (PLM): process of managing the entire lifecycle of a product from inception, through engineering design and manufacture, to service and disposal of manufactured products.

Prognostics (a.k.a. health management): a method that permits the assessment of the reliability of the product (or system) under its application conditions. It predicts the occurrence of an event based on current and future operational and environmental conditions to estimate the time at which a system no longer fulfils its function within desired specifications (“remaining useful life”).

Prosthetics: the branch of medicine or surgery that deals with the production and application of artificial body parts.

Quality: in this SRIA, quality is defined as “the degree to which a product meets requirements in specifications that regulate how the product should be designed and manufactured, including environmental stress screening (burn-in) but no other type of testing”. In this way, reliability, dependability and cybersecurity, which some readers may have expected to be included under quality, will be treated separately.

Quantum computing: an area of computing focused on developing computer technology based on the principles of quantum theory, which explains the behaviour of energy and material on the atomic and sub-atomic levels. A quantum computer utilises quantum entanglement between qubits to solve a set of computationally complex problems efficiently. The computational power of quantum computers is estimated to grow faster than classical computers in the future.

Quantum sensing: sensor technologies that make use of quantum technology.

Quantum technology: the creation, manipulation and detection of single particle quantum states accurately, enabling the use of quantum superposition and entanglement, where quantum states of several particles cannot be described independently, even when spatially separated. Currently, quantum effects typically require very low temperatures and the use of cryogenic technologies.

Recommender-based (methods and) tools: methods and tools in which the current status of a system under design is analysed and evaluated by design-supporting software, which then gives recommendations to the engineer as to possible further steps and/or options for completing the design, ideally together with an evaluation of the pros and cons for each option.

Reliability: the ability or probability, respectively, of a system or component to function as specified under stated conditions for a specified time (ISO 25010).

Safety (a.k.a. functional safety): freedom from unacceptable risk of physical injury or of damage to the health of people, either directly or indirectly as a result of damage to property or the environment (IEC 61508).

Security of ECS (a.k.a. IT security/cybersecurity): in this SRIA, security of ECS is defined as the prevention of illegal or unwanted penetration, intentional or unintentional interference with the proper and intended operation, or inappropriate access to confidential information. Security is considered to be composed of confidentiality, integrity and availability (ISO 21549-2).

Self-X: in self-X, X stands for adaptation, reconfiguration, etc. Usually in self-reorganising systems the major issue is how to self-reorganise while preserving the key parameters of a system, while being coherent with the initial requirements (e.g. performance, power consumption, real time constraints). Self-adaptation and self-reconfiguration has an enormous potential in many applications.

Smart city: an urban area that uses different types of electronic methods and sensors to collect data. Insights gained from that data are used to manage assets, resources and services efficiently; in return, that data is used improve the operations across the city (from Wikipedia).

Smart drug delivery system (SDDS): an advanced method of drug-targeted (DT) delivery. The smart drug delivered by this system must fulfill the following criteria: (i) increase the doses of delivered drug to the targeted body part of interest (tissue/cells/organs); (ii) not be degraded by any of the body fluids; (iii) diminish side effects by improving the efficacy of drug treatment; (iv) absorption of the delivered drug must cross a biological membrane; and (v) drug is released in appropriate dosages to the body part of interest. SDDS is highly complex and involves an integration of various disciplines, such as biology, chemistry and engineering.

Smart systems integration (SSI): (integrated) smart systems incorporate sensing, actuation and control up to cognitive functions to describe and analyse a situation, and make decisions based on the available data in a predictive or adaptive manner, thereby performing smart actions. The enabling principles of these functions include nanoelectronics, micro-electromechanics, magnetism, photonics, chemistry and radiation. SSI is an assembly of technologies that: build products from components; combine functions in products and systems; connect and network systems to other systems; and, importantly, enable systems to receive and store a “knowledge base” – the software that makes them “smart”.

Stretchable electronics: newly developed microelectronics that overcome the standard planar paradigm and can be prepared on stretchable substrates.

Structural electronics: integrating electronics into the body of structural parts of products of different materials.

System: for the purpose of this SRIA, a system is a set of electronic-based constituents (subsystems, modules and components, realised in hardware, software, or both) that are integrated in a way to together allow the system to perform a desired (set of) function(s).

Note that:

• Due to ECS typically being constructed hierarchically, a (e.g. camera or other sensor) “module” being part of the electronic “system” in an autonomous car might itself be referred to as a “system” when designing it (e.g. while integrating lower-level components to together achieve the “camera function”) (see also: system in a package, system on a chip, and others).

• The difference between a “system” (comprising subsystems, modules and components) and a “System of Systems” (also comprising subsystems) is that the constituents of a system are chosen and integrated during design-time (i.e. completely under control of the engineers), while in a System of Systems the constituent (sub)systems are independent and dynamically form (and disband) a System of Systems at run-time.

System in a package (SiP): a number of integrated circuits and other electronics building blocks (e.g. MEMS, antennas) enclosed in one single package.

System on a chip (SoC): an integrated circuit that incorporates multiple building blocks of an electronic system, including processors, memory units, accelerators, and input/output ports, and which covers the complete functionality of an electronic system.

System of Systems (SoS): a collection of independent and distributed embedded and cyber-physical systems dynamically composed to generate a new and more complex system, provided with new functionalities and driven by new goals not present in the constituent embedded and cyber-physical systems individually. An SoS must satisfy five characteristics: operational independence of constituent systems; managerial independence of constituent systems; geographical distribution; emergent behaviour; and evolutionary development processes. A system that does not satisfy these characteristics (specifically the first two) is not considered an SoS.

Teleoperation: teleoperation (or remote operation) indicates operation of a system or machine at a distance. It is similar in meaning to the phrase “remote control” but is usually encountered in research, academia and technical environments. It is most commonly associated with robotics and mobile robots, but can be applied to a whole range of circumstances in which a device or machine is operated by a person from a distance.

Telepresence: the use of virtual reality technology, especially for remote control of machinery or for participation in distant events.

Tracking mode simulation: adapting simulation by respective measurements of the real counterpart.

(Technical) Trustworthiness: having some reasonably well thought-out assurance that the technical realisation of a system is worthy of being trusted to satisfy certain well-specified requirements (e.g. safety, security, reliability, robustness and resilience, ease of use and ease of system administration, and predictable behaviour in the face of adversities, such as high-probability real-time performance).

Value-based healthcare: a healthcare delivery model in which providers, including hospitals and physicians, are paid based on patient health outcomes. Under value-based care agreements, providers are rewarded for helping patients improve their health, reduce the effects and incidence of chronic disease, and live healthier lives in an evidence-based way.

Verification and validation (V&V): independent procedures that are used together for checking that a product, service or system meets requirements and specifications, and that it fulfills its intended purpose. Verification checks whether the development implemented the specified requirements of a product correctly (“are we building the product right”), while validation is a system test checking whether a product can fulfil its intended purpose in a real environment (“are we building the right product?”).

Virtual commissioning: the practice of using “virtual” simulation technology to “commission” – design, install or test – control software with a virtual machine model before it is connected to a real system.

Virtual reality (VR): computer technology that makes a person feel like they are somewhere else. It uses software to produce images, sounds and other sensations to create a different place so that the user feels they are really part of this other place. Applications of virtual reality can include entertainment (e.g. video games) and educational purposes (e.g. medical or military training).

Wearables: wearable technology is a category of electronic devices that can be worn as accessories, embedded in clothing, implanted in the user’s body, or even tattooed on the skin.

X-in-the-loop: where “X” can be hardware-, software-, models-, systems-, etc. The term is used when testing ECS (or parts of an ECS). The system (e.g. component, module) to be tested is called “system-under-test” (SUT). This SUT is embedded into a testbed (or test environment) that provides the necessary input data (according to a specific test scenario), and which then monitors its outputs, comparing these actual outputs to the expected/specified ones. Within these testbeds, data flow therefore forms a “loop” (from the testbed through the SUT back to the testbed). Depending upon the realisation of the SUT (e.g. as a hardware component/module, software module, simulation model, complete system), different testbeds are needed and the resulting test process is called “hardware-in-the-loop”, “software-in-the-loop”, etc, or when referred to in a general way “X-in-the-loop”.