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Many transportation companies struggle to effectively utilize the information provided by tracking technology for performing operational control. The research as presented in this paper aims to identify the problems underlying the inability to utilize tracking technology within this context. Moreover, this paper aims to contribute to solving these problems by proposing a set of design principles based on the concept of intelligent products.

The study as described in this paper adopts a design science research methodology consisting of three phases. First, a case study in a transportation company has been performed to identify the problems faced when utilizing tracking technology. Second, to overcome these problems, a set of design principles has been formulated. Finally, a prototype system based on the design principles has been developed and subjected to experimental and observational evaluation.

This paper identifies the problems associated with the utilization of tracking technology for the control of transport operations. Moreover, the proposed design principles support the development of information systems which overcome the identified problems and thereby enhance the utilization of tracking technology in a transportation context.

The commonly held perception that tracking technology will improve the ability to perform operational control does not unequivocally stand up to empirical scrutiny. While it is widely demonstrated that tracking technology is able to accurately capture the detailed operational information, it remains a fundamental challenge to transform this abundance of information into accurate and timely control decisions. This research provides a valuable contribution with respect to tackling this challenge, by identifying problems and providing solutions related to the utilization of readily available tracking technology.

With the application and development of intelligent clothing and wearable technology, the term “micro-interaction” has gradually entered people’s lives. The paper aims to discuss this issue.

The paper takes the concept of “micro-interaction” as the design principle, starting from the consumer demand, combing the realization mode of the intelligent safety clothing in recent years, and finds out the existing problems in the design of the intelligent safety clothing.

Under the concept of micro-interaction, a new theoretical model has been proposed to study intelligent safety clothing. Finally, the paper also emphasizes the importance of the industrialization of the proposed model.

The paper proposes a new research and development mode for intelligent clothing in safety protection area which is a pioneering study and can be valuable for safety clothing manufacturers to produce more functional and attractive products.

The purpose of this paper is to develop an intelligent system for fashion style selection for non-standard female body shapes.

With the goal of creating natural aesthetic relationship between the body shape and the shape of clothing, garments designed for the upper and lower body are combined to fit different female body shapes, which are classified as V, A, H and O-shapes. The proposed intelligent system combines genetic algorithm (GA) with a neural network classifier, which is trained using the particle swarm optimization (PSO). The former, called genetic search, is used to find the optimal design parameters corresponding to a best fit for the desired target, while the task of the latter, called neural classification, is to evaluate fitness (goodness) of each evolved new fashion style.

The experimental results are fashion styling recommendations for the four female body shapes, drawn from 260 possible combinations, based on variations from 15 attributes. These results are considered to be a strong indication of the potential benefits of the application of intelligent systems to fashion styling.

The proposed intelligent system combines the effective searching capabilities of two approaches. The first approach uses the GA for identifying best fits to the target shape of the body in the solution space. The second is the PSO for finding optimal (with respect to training mean-squared error) weight and threshold parameters of the neural classifier, which is able to evaluate the fitness of successively evolved fashion styles.

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence (AI) will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of AI techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different AI techniques to be considered and then shows how these AI techniques are used for the components of IMS.

Outlines the current research work on intelligent sensors and intelligent transducers which will be required in complex systems. Discusses the elements of an intelligent sensor and concludes that these require analogue filtering, data conversion and compensation, and a digital communication link to a common signal bus. Explains what is meant by a systems approach to intelligent sensors with layered information processing. Concludes that unless a deeper understanding of the basics of sensor systems is acquired new intelligent sensor design will be very difficult.

An intelligent building incorporates two key components: automated building control systems and information management control systems. Automated building control systems include energy management systems, automated security and fire systems, and network life‐support systems. Information management control systems include telecommunications, data networking, local area networks, and other short and long haul networks. When these systems are linked together with common wiring and central controls, the building becomes intelligent. The integration of these components in Infomart, a high‐tech facility located in Dallas, Texas, is described. The usage of these components by tenants, and their possible application to library buildings are discussed.

The implied assembly constraints of a computer-aided design (CAD) model (e.g. hierarchical constraints, geometric constraints and topological constraints) represent an important basis for product assembly sequence intelligent planning. Assembly prior knowledge contains factual assembly knowledge and experience assembly knowledge, which are important factors for assembly sequence intelligent planning. This paper aims to improve monotonous assembly sequence planning for a rigid product, intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge is proposed.

A spatio-temporal semantic assembly information model is established. The internal data of the CAD model are accessed to extract spatio-temporal semantic assembly information. The knowledge system for assembly sequence intelligent planning is built using an ontology model. The assembly sequence for the sub-assembly and assembly is generated via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge. The optimal assembly sequence is achieved via a fuzzy comprehensive evaluation.

The proposed spatio-temporal semantic information model and knowledge system can simultaneously express CAD model knowledge and prior knowledge for intelligent planning of product assembly sequences. Attribute retrieval and rule reasoning of spatio-temporal semantic knowledge can be used to generate product assembly sequences.

The assembly sequence intelligent planning example of linear motor highlights the validity of intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge.

The spatio-temporal semantic information model and knowledge system are built to simultaneously express CAD model knowledge and assembly prior knowledge. The generation algorithm via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge is given for intelligent planning of product assembly sequences in this paper. The proposed method is efficient because of the small search space.

Within the building sector a lack of clarity in terminology does not help designers, clients or researchers. Non-domestic buildings have shown rapid increases in the use of advanced technology and control systems with varying drivers, many of which are labelled as intelligent. The term smart has been used interchangeably with intelligent without any clear distinction between the two. If the term Smart Buildings represented a separate, more advanced grouping, it would provide an opportunity to focus the future progress of non-domestic building development. The paper aims to discuss these issues.

Drawing upon academic and industrial literature and experience, this paper reviews the scope of Intelligent Buildings and the current available definitions of Smart Buildings to form a clear definition of both smart and Intelligent Buildings.

These definitions define the border between the intelligent and the (more advanced) Smart Building. The upper bound of the Smart Building is defined by (the future development of) the predictive building.

This work provides a clear focus which will allow the progression of the non-domestic building sector by providing guidance and aspiration, as well as providing a platform upon which a large amount of technical work can be based.

The purpose of this paper is the analysis of a methodology for the buildings' intelligence assessment through the development of a matrix tool. Techniques and technologies for use in designing, constructing and operating intelligent buildings are well known or available on the market and many intelligent buildings have been built. However, just how intelligent these buildings actually are in comparison to conventional buildings is often a question. Due to the lack of commonly accepted methods and pertinent supporting data, the assessment of the overall performance of intelligent buildings cannot be carried out. It remains difficult, if not impossible, to carry out a fair comparison between different buildings in term of intelligence. As a result, the construction industry proceeds without adequate knowledge about the best practice in intelligent building.

For the purpose of the present assessment, the definition of an intelligent building has been reviewed and refined. Based on the adopted definition, a matrix tool is developed. The objective of this tool is to provide facilities managers with an effective methodology for improving the energy and indoor environmental performance of their building stock. With appropriate development, the methodology could also form the basis of voluntary or regulatory methodology for building intelligence accreditation.

The paper describes the matrix tool's global performance indicators and specific performance indicators for the intelligent buildings' assessment. Moreover the application of the matrix tool in assessing two buildings is described.

The paper encourages a deeper analysis of the buildings' intelligence providing the initial framework.

The present paper proposes an innovative methodology for intelligent buildings assessment.

This paper reviews literature on the application of intelligent systems in the libraries with a special issue on the ES/AI and Robot. Also, it introduces the potential of libraries to use intelligent systems, especially ES/AI and robots.

Descriptive and content review methods are applied, and the researchers critically reviewed the articles related to library ESs and robots from Web of Science as a general database and Emerald as a specific database in library and information science from 2007–2017. Four scopes considered to classify the articles as technology, service, user and resource. It is found that published researches on the intelligent systems have contributed to many librarian purposes like library technical services like the organization of information resources, storage and retrieval of information resources, library public services as reference services, information desk and other purposes.

A review of the previous studies shows that ESs are a useable intelligent system in library and information science that mimic librarian expert’s behaviors to support decision making and management. Also, it is shown that the current information systems have a high potential to be improved by integration with AI technologies. In this researches, librarian robots mostly designed for detection and replacing books on the shelf. Improving the technology of gripping, localizing and human-robot interaction are the main concern in recent librarian robot research. Our conclusion is that we need to develop research in the area of smart resources.

This study has a new approach to the literature review in this area. We compared the published papers in the field of ES/AI and robot and library from two databases, general and specific.