Ruiqi Li’s research while affiliated with China National Institute of Standardization and other places
What is this page?
This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.
The world's ever-growing digital economy demands better ways to build products that meet the varied needs of a diverse set of users. Through the work of the IEEE Computer Society Smart Manufacturing Standards Committee, a new series of standards defining, describing, and solving problems in smart manufacturing is slated for completion in the very near future.
Artificial intelligence is currently attracting considerable interest and attention from industry, researchers, governments as well as investors, who are pouring record amounts of money into the development of new machine learning technologies and applications. Increasingly sophisticated algorithms are being employed to support human activity, not only in forecasting tasks but also in making actual decisions that impact society, businesses and individuals. Whether in the manufacturing sector, where robots are adapting their behaviour to work alongside humans, or in the home environment, where refrigerators order food supplies based on the homeowner’s preferences, artificial intelligence is continuously making inroads into domains previously reserved to human skills, judgment or decision-making.While artificial intelligence has the potential to help address some of humanity’s most pressing challenges, such as the depletion of environmental resources, the growth and aging of the world’s population, or the fight against poverty, the increasing use of machines to help humans make adequate decisions is also generating a number of risks and threats that businesses, governments and policy makers need to understand and tackle carefully. New concerns related to safety, security, privacy, trust, and ethical considerations in general are definitely emerging together with the technological innovations enabled by artificial intelligence. These challenges are common to all societies across the globe and will need to be dealt with at the international level.
The present White Paper provides a framework for understanding where artificial intelligence stands today and what could be the outlook for its development in the next 5 to 10 years. Based on an explanation of current technological capabilities, it describes the main systems, techniques and algorithms that are in use today and indicates what kinds of problems they typically help to solve. Adopting an industrial perspective, the White Paper discusses in greater detail four application domains offering extensive opportunities for the deployment of artificial intelligence technologies: smart homes, intelligent manufacturing, smart transportation and self-driving vehicles, and the energy sector.The analysis of various specific use cases pertaining to these four domains provides clear evidence that artificial intelligence can be implemented across and benefit a wide set of industries. This potential is paving the way for artificial intelligence to become an essential part of the equation in resolving issues generated by today’s and tomorrow’s megatrends. Building upon this analysis, the White Paper provides a detailed description of some of the major existing and future challenges that artificial intelligence will have to address. While industry and the research community constitute the principal drivers for developing initiatives to tackle technical challenges related to data, algorithms, hardware and computing infrastructures, governments and regulators urgently need to elaborate new policies to deal with some of the most critical ethical and social issues foreseen to be the by-products of artificial intelligence.
Standardization and conformity assessment are expected to play an essential role not only in driving market adoption of artificial intelligence but also in mitigating some of the most pressing challenges related to decision-making by machines. As a leading organization providing a unique mix of standardization and conformity assessment capabilities for industrial and information technology systems, the IEC is ideally positioned to address some of these challenges at the international level.
... The adoption of smart manufacturing provides industrialists with new tools to further improve their manufacturing processes. Smart manufacturing is a "method that improves its performance with the integrated and intelligent use of processes and resources in cyber, physical, and human spheres to create and deliver products and services, while also collaborating with other domains within an enterprise's value chains" [2]. ...
... AI helps to develop efficient systems, while robotics is necessary for better accuracy [14], [18], [19]. The widespread impact and benefits of AI and robotics on green industrialization can be seen in Fig. 3 [20]. ...
... In the era of the Internet of Everything, positions have gradually evolved into highly intelligent and complex work functions. As artificial intelligence is being applied in the sphere of intelligent manufacturing more and more, the system implementation form of intelligent manufacturing has been widely studied based on the definition of enterprise key performance indicators (KPI) [19]. The main role of artificial intelligence technology in intelligent manufacturing has been reflected through typical application scenarios, and its application map has been proposed from the life cycle dimension, and common technologies have been summarized. ...
... Additionally, AI can be understood from the perspective of the (theoretical) ability of an intelligent machine situated on a continuum, from specific to general intelligence or from basic to super intelligence. Some forms of AI within this continuum can be distinguished by names, such as Narrow AI, General AI, Weak AI, Strong AI [35]. ...