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Traditional supply chains deal with uncertainty, cost, complexity, and vulnerability problems. In order to overcome these problems, supply chain operations need to be innovative in business process management. Establishing a large-scale smart infrastructure to merge data, information, products, physical objects, and all supply chain processes needs to automate intelligently in supply chain management (SCM) through building secure operational decision support systems. Information technology (IT) and information and communication technology (ICT) are essential in business process automation. In recent decades, Internet of things (IoT) applications have played an essential role in automating supply chain management's regular business processes and their operations-related decisions. The vast adoption of wireless sensor networks (WANs) with IoT technology provides access to sensor nodes and sensing ability in Internet-connected devices. This way, the IoT provides access to a vast amount of data gathering by the WSNs, over the wide-area data communication networks. For example, sensing enterprise (SE) is an attribute of an enterprise or a network that allows it to react to business stimuli originating on the IoT-based infrastructure. This paper reviews some of the essential characteristics of IoT technology for designing SEs in supply chain management. [ABSTRACT FROM AUTHOR]

Group awareness is playing a major role in the efficiency of mission planning and decision-making processes, particularly those involving spatially distributed collaborative entities. The performance of this concept has remarkably increased with the advent of the Internet of Things (IoT). Indeed, a myriad of innovative devices are being extensively deployed to collaboratively recognize and track events, objects, and activities of interest. A wide range of IoT-based approaches have focused on representing and managing shared information through formal operators for group awareness. However, despite their proven results, these approaches are still refrained by the inaccuracy of information being shared between the collaborating distributed entities. In order to address this issue, we propose in this paper a new belief-management-based model for a collaborative Internet of Drones (IoD). The proposed model allows drones to decide the most appropriate operators to apply in order to manage the uncertainty of perceived or received information in different situations. This model uses Hierarchical Analysis Process (AHP) with Subjective Logic (SL) to represent and combine opinions of different sources. We focus on purely collaborative drone networks where the group awareness will also be provided as service to collaborating entities. [ABSTRACT FROM AUTHOR]

The rapid development of the Internet of Things (IoT) and the huge growth of valuable data produced by decentralising information processing along global apparel supply chain have led to a persuasive appeal for a semantic approach to integrating distributed data facilities in the field of self-determining collaborating logistics services. This paper describes a framework, Apparel Business Decentralised Data Integration (ABDDI), which exploits knowledge representation techniques and languages (e.g. Description Logics – DLs) to annotate relevant business activities, movements of products within the manufacturing network to provide value-added services. More specifically the paper discusses the DLs formalisms, which are used for knowledge representation in a decidable fragment of First Order Logic; and ALN (D) (Attributive Language with unqualified Number restrictions and concrete Domains) related issues. The paper presents an algorithm to demonstrate the DLs based entity concept similarity assessment to facilitate semantic web service. Finally, a business scenario is used to present some of the knowledge representation formalisms and concept similarity assessment in ABDDI. [ABSTRACT FROM AUTHOR]

The rapid changes in textile and clothing industry's operational environment in which apparel businesses are collaborating with their suppliers and customers have recognized interoperability of information systems as an important factor. The need to address this challenge becomes vital in the context of new paradigms such as the Internet of Things (IoT), and its ability to capture realtime information from different parts of textile and cloth manufacturing value chain by using Radio Frequency Identification (RFID) tags and sensors-based data communication networks. In this process, enterprise information system architecture plays an important role in storing, processing, and distributing data. Despite contributing to the rapid development of IoT applications, the current IoT-centric architecture has led to a myriad of isolated data silos. This paper presents a blockchain-based architecture for the IoT applications, which brings distributed data management to support transactions services within a multi-party apparel business supply chain network. [ABSTRACT FROM AUTHOR]

This study aims to relate organizational characteristics on preferences for project delivery methods (PDMs) in construction industry of Pakistan. Artificial Neural Network (ANN) based model is developed for predicting proportion of projects done by different types of organizations under various PDMs. It is found that ANN model give satisfactory accuracy in predicting these proportions for test and training datasets. It is found that client organizations are more inclined towards traditional methods, especially Design-Bid-Build (DBB). Consultant organizations had relatively higher proportion of projects done by Design-Build (DB) and other non-traditional methods. Most of the construction organizations belong to the private sector which showed an inclination towards DBB and DB methods. The non-traditional PDMs had relatively higher preference for organizations who are involved in infrastructure or other specialized projects. Organizations who have more projects showed more tendency towards non-traditional PDMs. [ABSTRACT FROM AUTHOR]

This paper proposes a modified architecture of the Long-Term Evolution (LTE) mobile network to provide services for the Internet of Things (IoT). This is achieved by allocating a narrow bandwidth and transferring the scheduling functions from the eNodeB base station to an NB-IoT controller. A method for allocating uplink and downlink resources of the LTE/NB-IoT hybrid technology is applied to ensure the Quality of Service (QoS) from end-to-end. This method considers scheduling traffic/resources on the NB-IoT controller, which allows eNodeB planning to remain unchanged. This paper also proposes a prioritization approach within the IoT traffic to provide End-to-End (E2E) QoS in the integrated LTE/NB-IoT network. Further, we develop "smart queue" management algorithms for the IoT traffic prioritization. To demonstrate the feasibility of our approach, we performed a number of experiments using simulations. We concluded that our proposed approach ensures high end-to-end QoS of the real-time traffic by reducing the average end-to-end transmission delay. [ABSTRACT FROM AUTHOR]