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.
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.
- 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, 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.
- 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.
- 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.
- 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’). 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.
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. 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’.
- Published 29 Standards | Developing 10 Projects
- ISO/DIS 5363 [Under development]RoboticsTest methods for exoskeleton-type walking RACA robot
- RoboticsCollaborative applicationsTest methods for measuring forces and pressures in human-robot contacts
- ISO/FDIS 10218-1 [Under development]RoboticsSafety requirementsPart 1: Industrial robots
- ISO/FDIS 10218-2 [Under development]RoboticsSafety requirementsPart 2: Industrial robot applications and robot cells
- Robots for industrial environmentsAutomatic end effector exchange systemsVocabulary
- ISO/CD 13482 [Under development]RoboticsSafety requirements for service robots
- Robots and robotic devicesCollaborative robots
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. At the same time, they may create opportunities for more efficient transport of goods and people to regional areas. Indeed, a significant, expected benefit to society is improved population mobility due to use of autonomous vehicles for public transport, particularly in rural areas.
Existing data on use of autonomous vehicles suggests they can reduce both safety incidents and fuel expenditure. 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.
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.
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. 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.
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.
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.”
- Published 45 Standards | Developing 1 Projects
- Information technologyInternet of Things (IoT)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 technologyInternet of things (IoT) use cases
- Internet of Things (IoT)Reference Architecture
- Information technologyInternet of thingsMethodology for trustworthiness of IoT system/service
- ISO/IEC AWI 30149 [Under development]Internet of things (IoT)Trustworthiness framework
- Internet of Things (IoT)Compatibility requirements and model for devices within industrial IoT systems
- Internet of Things (IoT)Real-time IoT framework
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.
‘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. 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.
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. 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.
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.
- Published 45 Standards | Developing 20 Projects
- ISO/WD 37100 [Under development]Sustainable cities and communitiesVocabulary
- Sustainable cities and communitiesGuidance on establishing smart city operating models for sustainable communities
- Sustainable cities and communitiesManagement requirements and recommendations for open data for smart cities and communitiesOverview and general principles
- Sustainable cities and communitiesIndicators for smart cities
- Sustainable cities and communitiesIndicators for resilient cities
- IEC/AWI 63205 [Under development]Smart Cities Reference Architecture (SCRA)
- Global trends. Paradox of progress (US National Intelligence Council, 2017)
- Foresight Africa. Top priorities for the continent 2020-2030 (Brookings Institution, 2020)
- Technology vision 2020. We, the post-digital people (Accenture, 2020)
- Digital economy report 2019. Value creation and capture: implications for developing countries (UN Conference on Trade and Development, 2019)
- Global Trends and the future of Latin America. Why and how Latin America should think about the future (Inter-American Development Bank, Inter-American Dialogue, 2016)
- 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)
- Emerging technologies and smart cities (Forbes, 2021)
- Digital megatrends. A perspective on the coming decade of digital disruption (Commonwealth Scientific and Industrial Research Organisation, 2019)