WSN and RFID integration to support intelligent monitoring in smart buildings using hybrid intelligent decision support systems

The real time monitoring of environment context aware activities is becoming a standard in the service delivery in a wide range of domains (child and elderly care and supervision, logistics, circulation, and other). The safety of people, goods and premises depends on the prompt reaction to potential hazards identified at an early stage to engage appropriate control actions. This requires capturing real time data to process locally at the device level or communicate to backend systems for real time decision making. This research examines the wireless sensor network and radio frequency identification technology integration in smart homes to support advanced safety systems deployed upstream to safety and emergency response. These systems are based on the use of hybrid intelligent decision support systems configured in a multi-distributed architecture enabled by the wireless communication of detection and tracking data to support intelligent real-time monitoring in smart buildings. This paper introduces first the concept of wireless sensor network and radio frequency identification technology integration showing the various options for the task distribution between radio frequency identification and hybrid intelligent decision support systems. This integration is then illustrated in a multi-distributed system architecture to identify motion and control access in a smart building using a room capacity model for occupancy and evacuation, access rights and a navigation map automatically generated by the system. The solution shown in the case study is based on a virtual layout of the smart building which is implemented using the capabilities of the building information model and hybrid intelligent decision support system.The Saudi High Education Ministry and Brunel University (UK

Agents enabling cyber-physical production systems

In order to be prepared for future challenges facing the industrial production domain, Cyber-Physical Production Systems (CPPS) consisting of intelligent entities which collaborate and exchange information globally are being proclaimed recently as part of Industrie 4.0. In this article the requirements of CPPS and abilities of agents as enabling technology are discussed. The applicability of agents for realizing CPPS is exemplarily shown based on three selected use cases with different requirements regarding real-time and dependability. The paper finally concludes with opportunities and open research issues that need to be faced in order to achieve agent-based CPPSs.info:eu-repo/semantics/publishedVersio

Evaluating applications of the unmanned aerial system in construction project management

Using unmanned aerial vehicle systems (UAS) or drones in project management (PM) is a novel methodology aimed at enhancing the performance of the PM system. This technology is still in its infancy, and some serious progress is required to cover and advance in this field. UAS is used in various applications ranging from site mapping, surveying, traffic surveillance, bushfire monitoring and aerial photography. Despite the multiple functions offered by UAS, which are well covered in various sources, industry practitioners still have little confidence and knowledge on this technology. The value of the data collected using UAS technology is still poorly utilised and understood. This project aims to explore areas in PM that can be enhanced while using UAS and understand the added value of adopting this new technology. This research will utilise Unmanned Aerial Vehicle (UAV) with high- definition (HD) cameras to collect real time imageries of construction sites. The collected data, with the aid of a photogrammetric software Pix4D, is used to develop a detailed UAS system to determine the accuracy of performed work, the generation of the corresponding progress payment reports, and referencing and tracking information in real time for a residential project. This study also discusses combining the UAS and 5D Building Information Modelling (BIM) data to develop smart construction sites. The UAS–BIM combination enables the project stakeholders to be fully informed of the work’s progress and quality to prevent mistakes that could lead to additional costs and delays. The paper identified the primary obstacles to applying the UAS via interviews with the project managers and tradespersons involved in the selected project. Assuredly, digital culture is essential for an intelligent construction site to shift the project team from a passive data user to a more proactive analyser to improve performance and site safety. This research is aimed at building a holistic digital system which will be applied and utilised in Construction Project Management (CPM) fields to improve the performance of site management and the quality of work performed. Other obstacles include ethical reservations, legal requirements, liability risks, weather conditions and the continuation of using a UAS in non-open-air construction environments

Industrial cyber physical systems supported by distributed advanced data analytics

The industry digitization is transforming its business models, organizational structures and operations, mainly promoted by the advances and the mass utilization of smart methods, devices and products, being leveraged by initiatives like Industrie 4.0. In this context, the data is a valuable asset that can support the smart factory features through the use of Big Data and advanced analytics approaches. In order to address such requirements and related challenges, Cyber Physical Systems (CPS) promote the development of more intelligent, adaptable and responsiveness supervisory and control systems capable to overcome the inherent complexity and dynamics of industrial environments. In this context, this work presents an agent-based industrial CPS, where agents are endowed with data analysis capabilities for distributed, collaborative and adaptive process supervision and control. Additionally, to address the different industrial levels’ requirements, this work combines two main data analysis scopes: at operational level, applying distributed data stream analysis for rapid response monitoring and control, and at supervisory level, applying big data analysis for decision-making, planning and optimization. Some experiments have been performed in the context of an electric micro grid where agents were able to perform distributed data analysis to predict the renewable energy production.info:eu-repo/semantics/publishedVersio

IDARTS – Towards intelligent data analysis and real-time supervision for industry 4.0

The manufacturing industry represents a data rich environment, in which larger and larger volumes of data are constantly being generated by its processes. However, only a relatively small portion of it is actually taken advantage of by manufacturers. As such, the proposed Intelligent Data Analysis and Real-Time Supervision (IDARTS) framework presents the guidelines for the implementation of scalable, flexible and pluggable data analysis and real-time supervision systems for manufacturing environments. IDARTS is aligned with the current Industry 4.0 trend, being aimed at allowing manufacturers to translate their data into a business advantage through the integration of a Cyber-Physical System at the edge with cloud computing. It combines distributed data acquisition, machine learning and run-time reasoning to assist in fields such as predictive maintenance and quality control, reducing the impact of disruptive events in production.info:eu-repo/semantics/publishedVersio

Digital Twins for Industry 4.0 in the 6G Era

Having the Fifth Generation (5G) mobile communication system recently rolled out in many countries, the wireless community is now setting its eyes on the next era of Sixth Generation (6G). Inheriting from 5G its focus on industrial use cases, 6G is envisaged to become the infrastructural backbone of future intelligent industry. Especially, a combination of 6G and the emerging technologies of Digital Twins (DT) will give impetus to the next evolution of Industry 4.0 (I4.0) systems. This article provides a survey in the research area of 6G-empowered industrial DT system. With a novel vision of 6G industrial DT ecosystem, this survey discusses the ambitions and potential applications of industrial DT in the 6G era, identifying the emerging challenges as well as the key enabling technologies. The introduced ecosystem is supposed to bridge the gaps between humans, machines, and the data infrastructure, and therewith enable numerous novel application scenarios.Comment: Accepted for publication in IEEE Open Journal of Vehicular Technolog

Reefer logistics and cool chain transport

Reefer logistics is an important part of the cool chain in which reefer containers are involved as the packaging for transporting perishable goods. Reefer logistics is challenging, as it deals with cost and time constraints as well as the product quality and sustainability requirements. In many situations, there is a trade-off between these factors (e.g., between transportation time and the quality of fresh products). Furthermore, considering the high value of reefers, the efficient logistics of is as important as the efficient cargo flows. This causes technical complications and the conflict of interests between actors, especially, between cargo owners (or shippers) and the asset owners (or transport/terminal operators). Improving the efficiency of reefer logistics calls for a thorough understanding of the trade-offs and complexities. This paper aims to help develop such an understanding using a systematic literature review and a socio-technical system analysis. The results can be used to provide managerial insights for actors involved in a cool chain to design tailored solutions for reefer

Context-based and human-centred information fusion in diagnostics

Maintenance management and engineering practice has progressed to adopt approaches which aim to reach maintenance decisions not by means of pre-specified plans and recommendations but increasingly on the basis of best contextually relevant available information and knowledge, all considered against stated objectives. Different methods for automating event detection, diagnostics and prognostics have been proposed, which may achieve very high performance when appropriately adapted and tuned to serve the needs of well defined tasks. However, the scope of such solutions is often narrow and without a mechanism to include human contributed intervention and knowledge contribution. This paper presents a conceptual framework of integrating automated detection and diagnostics and human contributed knowledge in a single architecture. This is instantiated by an e-maintenance platform comprising tools for both lower level information fusion as well as for handling higher level knowledge. Well structured maintenance relationships, such as those present in a typical FMECA study, as well as on the job human contributed compact knowledge are exploited to this end. A case study presenting the actual workflow of the process in an industrial setting is employed to pilot test the approach

An integrated core competence evaluation framework for portfolio management in the oil industry

Drawing upon resource-based theory, this paper presents a core competence evaluation framework for managing the competence portfolio of an oil company. It introduces a network typology to illustrate how to form different types of strategic alliance relations with partnering firms to manage and grow the competence portfolio. A framework is tested using a case study approach involving face-to-face structured interviews. We identified purchasing, refining and sales and marketing as strong candidates to be the core competencies. However, despite the company's core business of refining oil, the core competencies were identified to be their research and development and performance management (PM) capabilities. We further provide a procedure to determine different kinds of physical, intellectual and cultural resources making a dominant impact on company's competence portfolio. In addition, we provide a comprehensive set of guidelines on how to develop core competence further by forging a partnership alliance choosing an appropriate network topology