Cyber-physical systems integrate computational components (information processing) with physical processes, which interact through a network. Technological advances in the ‘Internet of Things’, ‘Robotics’, and ‘Autonomous vehicles’ are the foundation for making cyber-physical systems possible, and today there are examples of successful cyber-physical systems everywhere… from driver less trains, to smart buildings, to household appliances and everyday items such as cleaning robots, wearable fitness devices or electric bikes.
Cyber-physical systems provide an opportunity to positively improve our quality of life in many domains, ranging from transportation, to healthcare, farming, manufacturing, smart grids, and everyday living. A key challenge, however, is the need for engineering innovation to work in coordination with information technology innovation, as the physical meets the digital. Developing common languages and other commonalities in this pluri-disciplinary field will facilitate future development of these systems. In addition, as with many technological advances, unintended consequences of integrating cyber-physical systems are likely to emerge in future, and it is therefore important to think ahead about the ethics surrounding these systems and how future regulation can limit risks related to safety, responsibility, liability, privacy and more.
Technology trends
Robotics technology is developing quickly and is already able to replace human labour for a range of tasks. Vast improvements in the capabilities of robots are expected to continue and this will lead to changes across many industries[1,2,3]:
- Healthcare will benefit from the increased use of robots in basic medicine and diagnostics, reducing costs for individuals and the economic burden of publicly funded health services.[1]
- Robots will continue to take over human labour in manufacturing, displacing workers as a result – the pace of technological development may create extreme pressures on education and training systems to support the adaptation of workforces (see ‘Effects of automation’).[1,4] However, robotics is also expected to lead to new types of work[5], as large numbers of robotics technicians will be required to maintain these ‘fleets of robots’ and the data generated and collected by robots will be immense, leading to growing demand for data scientists to make use ofit.[3]
- The agricultural sector will increasingly use robots for manual tasks such as seeding, weeding, and harvesting, with sensors improving in their ability to identify ripe produce, harvest plants and detect disease.[3]
- A range of military applications is anticipated, raising increasingly complex ethical questions. If terrorist organizations and non-state armed groups have access to this technology, it will increase the complexity of conflict.[6]
- The automotive and transportation sector will move towards increasing production and use of ‘Autonomous vehicles’, made possible by advances in robotics and other emerging technologies (see ‘5G’).[4] The carsharing company Uber, for example, is currently expanding its driverless-car programme. This may lead to a reduction in private car ownership and use.[5]
As robots increase in power, their applications are likely to grow. Computing for robots is now possible in the Cloud, increasing their processing power and speed.[7] Advances in sensors, speech-recognition technology and computer vision will all contribute to more advanced robotics products, including robots that are able to operate in uncontrolled settings – known as ‘open-world autonomy’.[3]
Related trends
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- Robotics — Test methods for exoskeleton-type walking RACA robot
- Robotics — Collaborative applications — Test methods for measuring forces and pressures in human-robot contacts
- Robotics — Vocabulary
- ISO 10218-1 [В настоящее время на стадии разработки]Robotics — Safety requirementsPart 1: Industrial robots
- ISO 10218-2 [В настоящее время на стадии разработки]Robotics — Safety requirementsPart 2: Industrial robot applications and robot cells
- Robots for industrial environments — Automatic end effector exchange systems — Vocabulary
- ISO/DIS 13482 [В настоящее время на стадии разработки]Robotics — Safety requirements for service robots
- Robots and robotic devices — Collaborative robots
- ISO/CD 21423 [В настоящее время на стадии разработки]Robotics — Autonomous mobile robots for industrial environments — Communications and interoperability
- Robotics — Application services provided by service robots — Safety management systems requirements
Autonomous vehicle technology is not a one-size-fits-all concept, as there are different considerations and implications for road, ship, or rail transport. The degree of automation can vary as well, and classified in ranges from Level 0 (fully manual) to Level 5 (driverless). The following discussion explores autonomous vehicles as a high-level trend only, where autonomous vehicles are understood as all forms of driverless transport systems.
Autonomous vehicles are already used in industrial settings, in some public transport systems (e.g. driverless trains), and automation technology is increasingly integrated in our cars (e.g. cruise control, self-parking technology or traffic jam pilot).[8,9] While the autonomous vehicle market is growing as a whole, with an expected CAGR of over 39% from 2019 to 2026, the deployment of fully automated (driverless) vehicles on public roads is still years away.[10,11] The impact of more autonomous vehicles is likely to be double-sided. They may eliminate the need for drivers of vehicles of all kinds: trucks, taxis, and public transport vehicles, representing a significant labour force impact in the coming decades.[1] At the same time, they may create opportunities for more efficient transport of goods and people to regional areas.[9] Indeed, a significant, expected benefit to society is improved population mobility due to use of autonomous vehicles for public transport, particularly in rural areas.[12]
Existing data on use of autonomous vehicles suggests they can reduce both safety incidents and fuel expenditure.[8] Autonomous vehicles are expected to make trade corridors significantly more efficient and, when combined with the energy efficiency of electric vehicles, increase the competitiveness of road transport against rail for the delivery of goods.[9]
Technology is also developing for autonomous vehicles beyond the road. Future innovations could include autonomous cargo ships and planes leading to more efficient supply chains in international trade.[8]
Related trends
News stories
- Опубликовано 4 | Проекты на стандии разработки 1
- Road traffic safety (RTS) — Guidance on ethical considerations relating to safety for autonomous vehicles
- Опубликовано 443 | Проекты на стандии разработки 78
- ISO/AWI 20682 [В настоящее время на стадии разработки]Autonomous Underwater Vehicles — Risk and Reliability
- Ships and marine technology — Vocabulary related to autonomous ship systems
- Опубликовано 128 | Проекты на стандии разработки 25
- Road vehicles — Test object monitoring and control for active safety and automated/autonomous vehicle testing — Functional requirements, specifications and communication protocol
- Опубликовано 58 | Проекты на стандии разработки 13
- Agricultural machinery and tractors — Safety of partially automated, semi-autonomous and autonomous machineryPart 1: Machine design principles and vocabulary
- Agricultural machinery and tractors — Safety of partially automated, semi-autonomous and autonomous machineryPart 2: Design principles for obstacle protection systems
- Agricultural machinery and tractors — Safety of partially automated, semi-autonomous and autonomous machineryPart 3: Autonomous operating zones
- Agricultural machinery and tractors — Safety of partially automated, semi-autonomous and autonomous machineryPart 4: Verification methods and validation principles
- Опубликовано 185 | Проекты на стандии разработки 20
- Earth-moving machinery and mining — Autonomous and semi-autonomous machine system safety
- Опубликовано 350 | Проекты на стандии разработки 70
- Intelligent transport systems — Low-speed automated driving system (LSADS) servicePart 1: Role and functional model
- Intelligent transport systems — Low-speed automated driving system (LSADS) servicePart 2: Gap analysis
- Intelligent transport systemsPartially-automated parking systems (PAPS) — Performance requirements and test procedures
- Intelligent transport systems — Performance testing for connectivity and safety functions of automated driving buses in public transportPart 1: General framework
- Intelligent transport systems — Performance testing for connectivity and safety functions of automated driving buses in public transportPart 3: Service framework and use cases
- Intelligent transport systems — Dynamic data and map database specification for connected and automated driving system applicationsPart 1: Architecture and logical data model for harmonization of static map data
- ISO/TS 22726-2 [В настоящее время на стадии разработки]Intelligent transport systems — Dynamic data and map database specification for connected and automated driving system applicationsPart 2: Logical data model of dynamic data
- Intelligent transport systems — Low-speed automated driving (LSAD) systems for predefined routes — Performance requirements, system requirements and performance test procedures
- Intelligent transport systems — Automated valet parking systems (AVPS)Part 1: System framework, requirements for automated driving and for communications interface
- Intelligent transport systems — Automated valet parking systems (AVPS)Part 2: Security integration for type 3 AVP
- Опубликовано 18 | Проекты на стандии разработки 7
- Smart community infrastructures — Guidance on smart transportation by Electric, Connected and Autonomous Vehicles (eCAVs) and its application to on-demand responsive passenger services with shared vehicles
- Smart community infrastructures — Smart transportation by autonomous vehicles on public roads
The Internet of Things (IoT) refers to a system of interconnected devices embedded with software, sensors, and other technologies (such as digital twin, cloud computing, big data and ‘Artificial intelligence’), which allows them to exchange data over the Internet for the purpose of improving functionality and monitoring. IoT systems are software and data-intensive, as well as network centric. They can be quite complex, ranging from simple architecture to systems which are multi-tiered, distributed, and ‘Cyber-physical systems’. IoT systems are key enablers of ‘smart everything’, including smart homes and buildings, ‘Smart manufacturing’, ‘Smart cities’, and smart farming, but also wearable technologies, medical devices, and vehicles.[11] Currently, there are twice as many devices connected to the Internet as people, and IoT connections are still expected grow at 17% per year.[4,11] Experts predict that, by 2025, an average Internet user will be interacting with IoT devices nearly 4,900 times each day.[4]
This increased device connectivity will result in massive amounts of data, creating growing needs for data storage, analytical capacity, and data protection. The data gathered by these devices can contribute to improved strategies to reduce poverty in some contexts, as well as increased sustainability and environmental protection. However, the IoT could also pose risks, if data are not sufficiently protected, or if it is used for unethical purposes.[2]
The rollout of emerging communications and networking technologies such as ‘5G‘ and satellite IoT will increase the reach, efficiency, and capacity of IoT devices, further growing the demand for these products.[3,11] For example, improved IoT technology and increased connectivity are already fostering the development of remote surgery technologies, which will “bring previously inaccessible healthcare to worldwide populations.”[3]
Related trends
News stories
- Опубликовано 49 | Проекты на стандии разработки 13
- Internet of Things (IoT) and digital twin — Vocabulary
- Internet of things (IoT) — Interoperability for IoT systemsPart 1: Framework
- Internet of things (IoT) — Interoperability for IoT systemsPart 2: Transport interoperability
- Internet of things (IoT) — Interoperability for IoT systemsPart 3: Semantic interoperability
- Internet of things (IoT) — Interoperability for IoT systemsPart 4: Syntactic interoperability
- Information technology — Internet of things (IoT) use cases
- Internet of Things (IoT) — Reference architecture
- Information technology — Internet of things — Methodology for trustworthiness of IoT system/service
- Internet of Things (IoT) — Trustworthiness principles
- Internet of Things (IoT) — Compatibility requirements and model for devices within industrial IoT systems
- Internet of Things (IoT) — Real-time IoT framework
- Internet of Things (IoT) — Generic trust anchor application programming interface for industrial IoT devices
- Internet of Things (IoT) — IoT applications for electronic label system (ELS)
- ISO/IEC CD 30177 [В настоящее время на стадии разработки]Internet of Things (IoT) — Underwater network management system (U-NMS) interworking
- ISO/IEC CD 30178 [В настоящее время на стадии разработки]Internet of Things (IoT) — Data format, value and coding
- Internet of Things (IoT) — Overview and general requirements of IoT system for ecological environment monitoring
- ISO/IEC DIS 30180 [В настоящее время на стадии разработки]Internet of Things (IoT) — Functional requirements to determine the status of self-quarantine through Internet of Things data interfaces
- Internet of Things (IoT) — Functional architecture for resource identifier interoperability
- Internet of Things (IoT) — Autonomous IoT object identification in connected home — Requirements and framework
- ISO/IEC CD 30187 [В настоящее время на стадии разработки]Internet of Things (IoT) — Evaluation indicators for IoT systems
- ISO/IEC AWI 30189-1 [В настоящее время на стадии разработки]Internet of Things (IoT) — IoT-based management of tangible cultural heritage assetsPart 1: Framework
- Internet of things (IoT) and digital twin — Best practices for use case projects
- ISO/IEC AWI 30195 [В настоящее время на стадии разработки]Internet of Things (IoT) — IoT applications for long-distance oil and gas pipeline
- ISO/IEC AWI 30196 [В настоящее время на стадии разработки]Internet of Things (IoT) — IoT applications for natural gas distribution system
- Опубликовано 252 | Проекты на стандии разработки 68
- ISO/IEC FDIS 27701 [В настоящее время на стадии разработки]Information security, cybersecurity and privacy protection — Privacy information management systems — Requirements and guidance
- Опубликовано 613 | Проекты на стандии разработки 100
- ISO/IEC DIS 23093-1 [В настоящее время на стадии разработки]Information technology — Internet of media thingsPart 1: Architecture
- ISO/IEC DIS 23093-2 [В настоящее время на стадии разработки]Information technology — Internet of media thingsPart 2: Discovery and communication API
- ISO/IEC DIS 23093-3 [В настоящее время на стадии разработки]Information technology — Internet of media thingsPart 3: Media data formats and APIs
- Information technology — Internet of media thingsPart 4: Reference software and conformance
- ISO/IEC FDIS 23093-5 [В настоящее время на стадии разработки]Information technology — Internet of media thingsPart 5: IoMT autonomous collaboration
- ISO/IEC DIS 23093-6 [В настоящее время на стадии разработки]Information technology — Internet of media thingsPart 6: IoMT Media data formats and API for distributed AI processing
Cities are the future of human organization, with over two-thirds of the global population expected to live in urban areas by 2030. This raises significant challenges, including the allocation of resources to growing populations and the management of their consumption and waste. Smart cities are rising to address these challenges by integrating smart technologies to address citizens’ needs more safely, sustainably, and efficiently, from goods and services to transport and logistics management. The World Economic Forum predicts that the technological tipping point for smart cities – that is, when they move from being novel entities to representing the norm – could occur as early as 2026.[13]
‘Smart’ can mean different things to different people. In ISO, a ‘smart city’ is considered to be one with “effective integration of physical, digital and human systems in the built environment to deliver a sustainable, prosperous and inclusive future for its citizens” (ISO/IEC 30182:2017, 2.14). Another helpful way to understand it is to look at smart as having three pillars: digital, physical, and economic. Digitally smart refers to the effective deployment of digital and communication technologies for city management. Physically smart refers to the adjustment and construction of sustainable infrastructures and processes that enhance the city’s resilience and the residents’ quality of life. Finally, economically smart refers to the effective collaboration between citizens and local businesses to share assets and resources to build a resilient community.[14] The evolution of smart cities is closely linked to innovation in ‘Internet of Things’, ‘5G‘ and DARQ technologies, ‘Distributed ledger‘, ‘Artificial intelligence’, ‘Extended reality’, ‘Quantum computing’, which are essential in supporting the deployment of smart cities around the globe.[3]
Smart cities can both improve the living conditions of residents and support more sustainable living arrangements. They do this by integrating smart grids (see ‘Energy’), energy-saving construction materials and buildings, efficient digital management systems for waste and other logistical needs and services to citizens.[8] This results in a more efficient use of resources and resilient, better-connected systems. However, with this increased connectivity also brings risks related to privacy and big-data sharing. Because a smart city depends on a highly interdependent connected network, this increases the risk that a security breach, hacking or technical issue such as a power cut could affect the entire system, with repercussions in all sectors.[15,16] There is also a concern about the ‘Big Brother’ dilemma – for smart technology to efficiently relay information and adapt systems to residents’ needs, big data must be collected using things like cameras, sensors, and IoT tools.[17]
To maintain citizens’ trust in the smart city concept, effective policies and regulations will be needed to protect residents’ privacy and personal information. Standardization plays an important role towards bringing trust amongst citizens, thanks to transparency and open processes, which is key for citizens acceptance and confidence.
Related trends
News stories
- Опубликовано 56 | Проекты на стандии разработки 20
- Smart community infrastructures – Disaster risk reduction – Survey results and gap analysis
- ISO/CD 37100 [В настоящее время на стадии разработки]Sustainable cities and communities — Vocabulary
- Sustainable cities and communities — Guidance on establishing smart city operating models for sustainable communities
- Sustainable cities and communities — Management requirements and recommendations for open data for smart cities and communities — Overview and general principles
- Sustainable cities and communities — Case studies in how smart city operating models support an effective public-health emergency response
- Sustainable cities and communities — Guidance for managing a public-health emergency response in smart city operating models
- ISO/DIS 37114 [В настоящее время на стадии разработки]Sustainable cities and communities — Appraisal framework for datasets and data processing methods that create urban management information
- ISO/WD TR 37115 [В настоящее время на стадии разработки]Sustainable cities and communities — Use Cases on Net Zero Carbon Cities Pathways
- ISO/CD 37116 [В настоящее время на стадии разработки]Sustainable cities and communities — Disaster risk finance — Principles and general requirements for financing ex-ante investment in risk reduction
- Sustainable cities and communities — Indicators for smart cities
- Sustainable cities and communities — Indicators for resilient cities
- Sustainable cities and communities — Environmental, social and governance (ESG) indicators for cities
- Smart community infrastructures — Maturity model for assessment and improvement
- Smart community infrastructures — Smart transportation for newly developing areas
- Smart community infrastructures — Urban data integration framework for smart city planning (SCP)
- Smart community infrastructures — Guidance on smart transportation by Electric, Connected and Autonomous Vehicles (eCAVs) and its application to on-demand responsive passenger services with shared vehicles
- Smart community infrastructures — Data framework for infrastructure governance based on digital technology in smart cities
- Smart community infrastructures — Data exchange and sharing for community infrastructures based on geographic information
- Smart community infrastructure — Guidance for the development of smart building information systems
- Smart community infrastructure — Responsiveness assessment and maturity model
- Smart community infrastructures — Data exchange and sharing for the lamppost network in smart community
- Smart community infrastructures — Disaster risk reduction — Basic framework for implementation
- Smart community infrastructures — Smart transportation by autonomous vehicles on public roads
- Smart community infrastructures — Smart transportation for fuel efficiency and pollution emission reduction in bus transportation services
- ISO/CD 37187 [В настоящее время на стадии разработки]Smart community infrastructures — Guidelines on data exchange and sharing of city information modelling platform
- ISO/CD 37194 [В настоящее время на стадии разработки]Smart community infrastructures — Disaster risk reduction — Guidance for the process of selecting seismometer systems suitable for specific purposes
- IEC/AWI 63205 [В настоящее время на стадии разработки]Smart Cities Reference Architecture (SCRA)
- Опубликовано 3555 | Проекты на стандии разработки 526
- Information technology — Computer graphics, image processing and environmental data representation — Guidelines for representation and visualization of smart cities
- ISO/IEC CD TR 25005-2 [В настоящее время на стадии разработки]Information technology — Data use in smart citiesPart 2: Use case analysis and common considerations
- Smart cities — Guidance to establishing a decision-making framework for sharing data and information services
- ISO/IEC AWI TR 20169 [В настоящее время на стадии разработки]Information technology — Overview of information technology standards for smart cities
- ISO/IEC AWI 20538 [В настоящее время на стадии разработки]Human Information Data Model for 3D Virtual Smart Cities
- Information technology — Smart city digital platform reference architecture — Data and service
- Smart city concept model — Guidance for establishing a model for data interoperability
- Опубликовано 13 | Проекты на стандии разработки 1
- Sustainability in buildings and civil engineering works — Indicators and benchmarks — Principles, requirements and guidelines
- Опубликовано 350 | Проекты на стандии разработки 70
- Intelligent transportation systems — Energy-based green ITS services for smart city mobility applications via nomadic and mobile devicesPart 1: General information and use case definitions
- ISO/AWI TS 17748-2 [В настоящее время на стадии разработки]Intelligent transport systems — Nomadic and mobile devices — Energy-based green ITS services for smart city mobility applicationsPart 2: Functional requirements of data platform
- ISO/CD 17748-3.2 [В настоящее время на стадии разработки]Intelligent transport systems — Energy-based green ITS services for smart city mobility applications via nomadic and mobile devicesPart 3: Data exchange requirements for electric vehicles (EV)-based demand response charging services
- Опубликовано 49 | Проекты на стандии разработки 9
- Facility smart grid information model
- Опубликовано 68 | Проекты на стандии разработки 11
ISO/TMBG/JSCTF-TF 19 ISO, IEC and ITU Joint Smart Cities Task Force
References
- Global trends. Paradox of progress (US National Intelligence Council, 2017)
- Foresight Africa. Top priorities for the continent 2020-2030 (Brookings Institution, 2020)
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- Global risks 2035 update. Decline or new renaissance? (Atlantic Council, 2019)
- 20 New technology trends we will see in the 2020s (BBC Science Focus Magazine, 2020)
- AGCS trend compass (Allianz, 2019)
- Global connectivity outlook to 2030 (World Bank, 2019)
- What are the levels of automated driving? (Aptiv, 2020)
- Future possibilities report 2020 (UAE Government, 2020)
- Global strategic trends. The future starts today (UK Ministry of Defence, 2018)
- Global trends to 2030. Challenges and choices for Europe (European Strategy and Policy Analysis System, 2019)
- Technology outlook 2030. Technology & society (Det Norske Veritas, 2021)
- Beyond the noise. The megatrends of tomorrow's world (Deloitte, 2017)
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- Digital megatrends. A perspective on the coming decade of digital disruption (Commonwealth Scientific and Industrial Research Organisation, 2019)