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In the crowd intelligence networking era, the smart connections of human, machines and things enable point-to-point trustable transactions and distributed efficient collaboration; the smart connections among government, enterprises, organizations and the public would enable active participation of the public in society management and decision-making and improve the efficiency of government management and services. All interactions among various agents can be viewed as the transaction activity. The social division of labor system drives the evolution of transaction. The transaction mode also differentiated into different patterns with the development of human society. What will be the intelligent transaction in the crowd intelligence networking era? What will be the transactions modes and rules in the crowd intelligence networking era? The answers to these questions are of great importance to the future development of transactions.

The authors review the evolution of traditional transaction and transaction modes and analyze the driving forces of it. They attempt to give the definitions of intelligent transaction and intelligent transaction mode. They also review the traditional transaction modes and rules, analyze the characteristics of the intelligent transaction and classify the intelligent transaction modes.

The authors find the intelligent transaction is mainly reflected in the intellectualization of transaction subject, transaction object and transaction process. They summarize the characteristics of intelligent transaction and develop four modes for the intelligent transactions based on the modularization level of the transaction objects and the quantity of transaction subjects, including the demand side and the supply side. The authors also show representative examples to further illustrate rules and features of these transaction modes and point out the potential research directions.

This study is among the first to analyze the characteristics of the intelligent transaction, and the proposed division framework of the intelligent transaction modes could not only add value to the future research of intelligent transaction modes and rules but also help to guide the transactions in the crowd intelligence network.

The synthetic application and interaction of/between the internet, Internet of Things, cloud computing, big data, Industry 4.0 and other new patterns and new technologies shall breed future Web-based industrial operation system and social operation management patterns, manifesting as a crowd cyber eco-system composed of multiple interconnected intelligent agents (enterprises, individuals and governmental agencies) and its dynamic behaviors. This paper aims to explore the basic principles and laws of such a system and its behavior.

The authors propose the concepts of crowd science and engineering (CSE) and expound its main content, thus forming a research framework of theories and methodologies of crowd science.

CSE is expected to substantially promote the formation and development of crowd science and thus lay a foundation for the advancement of Web-based industrial operation system and social operation management patterns.

This paper is the first one to propose the concepts of CSE, which lights the beacon for the future research in this area.

This study presents a structured investigation of the most important causes for delay in commercial real estate transactions. It assesses the potential of digital technologies such as “Blockchain”, “Property Passports” or “Automated Valuation Models” to make transactions faster and cheaper.

The authors conduct a focus group interview to identify the individual steps and the parties involved in real estate transactions. Subsequently, the authors discuss the prospects of digital technologies based on semi-structured interviews with real estate professionals and PropTech executives, and a comprehensive screening of technological solutions offered by PropTech firms.

The lack of an up-to-date, single pool of standardised property information turns out to be the most critical cause for delay in real estate transactions. However, the most promising technologies to mitigate this problem, in particular digital property passports summarising all relevant building information, face substantial barriers to adoption. The real estate industry has so far not been willing to more openly share data, which is a pre-requiste for the successful introduction of property passports. In addition, the principle of caveat emptor makes a lengthy due diligence process essential for buyers.

The authors conclude that industry-wide collaborations are necessary to help major efficiency gaining technologies to break through. Insurance products should accompany property data log books to guarantee the quality of data provided.

This study considers the potential impact of technologies in the wider context of the complete real estate transaction process. It identifies the major phases of that process and the associated bottlenecks. The authors gather evidence both from industry experts and PropTech executives and contrast their views regarding the potential of digital technologies to remove those bottlenecks.

The purpose of this paper is to systematically study the research and development history of suspicious transaction reporting (STR) system in China, and introduce the core elements in constructing an intelligent surveillance system which could provide a solution to the situation of low effectiveness and efficiency in Chinese Financial Institutions (FIs) STR procedure nowadays. The solution outputs those falling out of the normal customer behavior profiles instead of only extracting data by the rules issued by authorities.

This paper reviews the latest literature, regulations and guidelines of STR gathered domestically and overseas, and hands out questionnaire surveys to hundreds of software vendors, regulators and FIs, details the current situation of poor deployment of intelligent in China and tells the difficulties of subjective STR decision procedures.

Few Chinese FIs have deployed real intelligent STR systems, most are using rule-based filtering systems conformed to the objective STR supervisory regulations. To change the embarrassing situation, the regulators have tried to introduce self-regulatory mode which allows the FIs to define STR decision procedures themselves. Limited by the FIs’ ability of information sharing and investigation scope, FIs could hardly unveil the whole schema of a money laundering organization. The pursuant objective FIs can reach is to construct a system that could tell what the normal customer behaviors look like and extract all those falling out of the system’s expectations as suspicious activities.

Only the core elements of the total intelligent STR system are discussed, that is, what, why and how about the customer behavior pattern recognition system. Besides this, a total solution should also use a watch list, reporting decision, cases management, risk control, etc.

This paper for the first time argues that the orientation of regulatory rules in China has actually hindered the spreading of really effective intelligent system for these years. The author creatively puts forward a solution to the difficult problem for FIs to spot criminal schema directly, instead the FIs should only be required to determine whether the transactions carrying out currently are falling within the expected behavior pattern scopes, which is under the FIs’ capabilities due to the internationally accepted obligations of “Know Your Customer”.

The purpose of this paper is to build cyber-physical-psychological ternary fusion crowd intelligence network and realize comprehensive, real, correct and synchronous projection in cyber–physical–psychological ternary fusion system. Since the network of crowd intelligence is the future interconnected network system that takes on the features of large scale, openness and self-organization. The Digital-selfs in the network of crowd intelligence interact and cooperate with each other to finish transactions and achieve co-evolution eventually.

To realize comprehensive, real, correct and synchronous projection between cyber–physical–psychological ternary fusion system, the authors propose the rules and methods of projection from real world to the CrowdIntell Network. They build the mental model of the Digital-self including structure model and behavior model in four aspects: identity, provision, demand and connection, thus forming a theoretical mental model framework of Digital-self.

The mental model is excepted to lay a foundation for the theory of modeling and simulation in the research of crowd science and engineering.

This paper is the first one to propose the mental model framework and projection rules and methods of Digital-selfs in network of crowd intelligence, which lays a solid foundation for the theory of modeling, simulation, intelligent transactions, evolution and stability of CrowdIntell Network system, thus promoting the development of crowd science and engineering.

This paper aims to propose a robust and efficient method for vanishing point detection in unstructured road scenes.

The proposed method includes two main stages: drivable region estimation and vanishing point detection. In drivable region estimation stage, the road image is segmented into a set of patches; then the drivable region is estimated by the patch-wise manifold ranking. In vanishing point detection stage, the LSD method is used to extract the straight lines; then a series of principles are proposed to remove the noise lines. Finally, the vanishing point is detected by a novel voting strategy.

The proposed method is validated on various unstructured road images collected from the real world. It is more robust and more efficient than the state-of-the-art method and the other three recent methods. Experimental results demonstrate that the detected vanishing point is practical for vision-sensor-based navigation in complex unstructured road scenes.

This paper proposes a patch-wise manifold ranking method to estimate the drivable region that contains most of the informative clues for vanishing point detection. Based on the removal of the noise lines through a series of principles, a novel voting strategy is proposed to detect the vanishing point.

The purpose of this paper is to study the architecture of holographic personalized portal, user modeling, commodity modeling and intelligent interaction.

In this paper, the authors propose crowd-science industrial ecological system based on holographic personalized portal and its interaction. The holographic personality portal is based on holographic enterprises, commodities and consumers, and the personalized portal consists of accurate ontology, reliable supply, intelligent demand and smart cyberspace.

The personalized portal can realize the information acquisition, characteristic analysis and holographic presentation. Then, the intelligent interaction, e.g. demand decomposition, personalized search, personalized presentation and demand prediction, will be implemented within the personalized portal.

The authors believe that their work on intelligent interaction based on holographic personalized portal, which has been first proposed in this paper, is innovation focusing on the interaction between intelligence and convenience.

The purpose of this paper is to develop a better understanding of supply chain management in the financial services industry by examining information flow in improving efficiencies (i.e. material, information, capital, etc.) via intelligent matching.

The objective was to address the issues specific to financial services organizations in intelligent matching, examining organizational, technological and application aspects. In order to address these issues, we have utilized an exploratory research methodology, based on a literature review and some initial case studies.

Drivers for intelligent matching solutions have been suggested in this research to include the ability to link financial matching activities to other supply chain activities. Further integration of business processes, both within and between enterprises, will require both human and computational intelligence to approach efficiencies in automation.

Supply chain efficiencies enabled by financial products and information give organizations greater visibility over their receivables, working capital needs, and overall financial position. Limitations of this research include a small sampling of case studies; future research will include a wider scope of cases as to test the findings.

Interoperability of information between the physical movement of goods and financial information within supply chains is key to realizing cost‐reduction and revenue‐enhancement advantages.

This paper discusses a potential area for extending our understanding of supply chains and the role of information flow in improving efficiencies, especially in the financial services industry.

This article aims to reveal the factors influencing the sustainable development of mobile e-commerce from both user and operational perspectives. It fills the gap in qualitative research on the sustainable development of artificial intelligence (AI) technology in mobile e-commerce based on the grounded theory. This study provides valuable insights and inspiration for sustainable development in this field and lays the theoretical foundation and research reference for future studies.

Based on the grounded theory (GT), interview method was used to conduct the study.

The impact of AI applications on mobile e-commerce is mainly reflected in three stages of the customer shopping process. They are pre-shopping, mid-shopping and after-shopping AI services and each of the three stages has its own separate dimensions that need attention. The study and its persistence aspects are discussed.

The results of this study can provide forward-looking suggestions and paths for the construction and optimization of future e-commerce platforms, contribute to the sustainable development of e-commerce and contribute to the sustainable and healthy growth of the social economy.

This study proposes sustainable development measures for the application of AI in mobile e-commerce, from operation to supervision, which is an important reference for promoting coordinated and rapid socio-economic development.

Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.

Instead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.

The mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.

The fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.