VPI-FP: an integrative information system for factory planning

Nowadays, one of the main challenges in factory planning is the consistent and coherent information modelling along planning processes. Despite the current efforts in the fields of virtual production as well as digital and virtual factory, planning and simulation applications mostly support only the analysis and the optimisation of single planning aspects. However, to match nowadays challenges, planners require solutions that provide an integrated view to evaluate planning scenarios in advance and to achieve increasing production quality and efficiency. The concept of virtual production intelligence (VPI) provides a basic concept for such an integrative information system that enables planners to integrate, to aggregate and to analyse data gathered during one planning project as well as to compare different projects. In this study, we present such an information system for factory planning using the concept of the VPI. The focus lies in particular on the information modelling as well as the information integration and evaluation. Therefore, the study presents theoretical basics and implementations of the VPI platform within a precise application scenario in factory planning. This is to process and provide a consolidated information base along the whole planning process to support factory planning projects.     

An Internet of Energy Things Based on Wireless LPWAN

Under intense environmental pressure, the global energy sector is promoting the integration of renewable energy into interconnected energy systems. The demand-side management (DSM) of energy systems has drawn considerable industrial and academic attention in attempts to form new flexibilities to respond to variations in renewable energy inputs to the system. However, many DSM concepts are still in the experimental demonstration phase. One of the obstacles to DSM usage is that the current information infrastructure was mainly designed for centralized systems, and does not meet DSM requirements. To overcome this barrier, this paper proposes a novel information infrastructure named the Internet of Energy Things (IoET) in order to make DSM practicable by basing it on the latest wireless communication technology: the low-power wide-area network (LPWAN). The primary advantage of LPWAN over general packet radio service (GPRS) and area Internet of Things (IoT) is its wide-area coverage, which comes with minimum power consumption and maintenance costs. Against this background, this paper briefly reviews the representative LPWAN technologies of narrow-band Internet of Things (NB-IoT) and Long Range (LoRa) technology, and compares them with GPRS and area IoT technology. Next, a wireless-to-cloud architecture is proposed for the IoET, based on the main technical features of LPWAN. Finally, this paper looks forward to the potential of IoET in various DSM application scenarios.     

A Cost-Effective Approach for NDN-Based Internet of Medical Things Deployment

Nowadays, healthcare has become an important area for the Internet of Things (IoT) to automate healthcare facilities to share and use patient data anytime and anywhere with Internet services. At present, the host-based Internet paradigm is used for sharing and accessing healthcare-related data. However, due to the location-dependent nature, it suffers from latency, mobility, and security. For this purpose, Named Data Networking (NDN) has been recommended as the future Internet paradigm to cover the shortcomings of the traditional host-based Internet paradigm. Unfortunately, the novel breed lacks a secure framework for healthcare. This article constructs an NDN-Based Internet of Medical Things (NDN-IoMT) framework using a lightweight certificateless (CLC) signature. We adopt the Hyperelliptic Curve Cryptosystem (HCC) to reduce cost, which provides strong security using a smaller key size compared to Elliptic Curve Cryptosystem (ECC). Furthermore, we validate the safety of the proposed scheme through AVISPA. For cost-efficiency, we compare the designed scheme with relevant certificateless signature schemes. The final result shows that our proposed scheme uses minimal network resources. Lastly, we deploy the given framework on NDN-IoMT.     

生物液晶传感材料在物联网中的应用前景

生物液晶材料具有高分子生物材料和液晶的双重特性,可望研制出一批新颖的用于物联网中的传感器。分析了物联网和生物液晶材料的特性,对液晶分子作为"敏感元件"的检测方法和可行性进行了讨论。生物液晶材料在发展快速、简单的生物传感器,以及进一步应用于物联网方面有可预见的良好前景。     

Blockchain-Enabled EHR Framework for Internet of Medical Things

The Internet of Medical Things (IoMT) offers an infrastructure made of smart medical equipment and software applications for healthcare services. Through the internet, the IoMT is capable of providing remote medical diagnosis and timely health services. The patients can use their smart devices to create, store and share their electronic health records (EHR) with a variety of medical personnel including medical doctors and nurses. However, unless the underlying commination within IoMT is secured, malicious users can intercept, modify and even delete the sensitive EHR data of patients. Patients also lose full control of their EHR since most healthcare services within IoMT are constructed under a centralized platform outsourced in the cloud. Therefore, it is appealing to design a decentralized, auditable and secure EHR system that guarantees absolute access control for the patients while ensuring privacy and security. Using the features of blockchain including decentralization, auditability and immutability, we propose a secure EHR framework which is mainly maintained by the medical centers. In this framework, the patients’ EHR data are encrypted and stored in the servers of medical institutions while the corresponding hash values are kept on the blockchain. We make use of security primitives to offer authentication, integrity and confidentiality of EHR data while access control and immutability is guaranteed by the blockchain technology. The security analysis and performance evaluation of the proposed framework confirms its efficiency.     

Anomaly Detection for Internet of Things Cyberattacks

The Internet of Things (IoT) has been deployed in diverse critical sectors with the aim of improving quality of service and facilitating human lives. The IoT revolution has redefined digital services in different domains by improving efficiency, productivity, and cost-effectiveness. Many service providers have adapted IoT systems or plan to integrate them as integral parts of their systems’ operation; however, IoT security issues remain a significant challenge. To minimize the risk of cyberattacks on IoT networks, anomaly detection based on machine learning can be an effective security solution to overcome a wide range of IoT cyberattacks. Although various detection techniques have been proposed in the literature, existing detection methods address limited cyberattacks and utilize outdated datasets for evaluations. In this paper, we propose an intelligent, effective, and lightweight detection approach to detect several IoT attacks. Our proposed model includes a collaborative feature selection method that selects the best distinctive features and eliminates unnecessary features to build an effective and efficient detection model. In the detection phase, we also proposed an ensemble of learning techniques to improve classification for predicting several different types of IoT attacks. The experimental results show that our proposed method can effectively and efficiently predict several IoT attacks with a higher accuracy rate of 99.984%, a precision rate of 99.982%, a recall rate of 99.984%, and an F1-score of 99.983%.     

物联网技术在物流包装应用中的问题及对策

目的研究物联网技术在物流包装中的应用进展,提出待解决问题的对策。方法运用物联网和包装管理的基本原理,采用探究性、描述性和因果性研究方法系统阐释其工作机理。结果应提高芯片技术研发和生产能力,创建可视化智能管理系统,加强物流包装EDI技术的开发和应用,提高包装信息响应,加强电子产品代码(EPC)网络管理,提高网络安全技术水平,从而加强物联网技术在物流包装领域中的推广和应用。结论物流包装领域可通过实施物联网技术实现持续改进的目标。     

天津市农业物联网标准体系研究

近年来,随着物联网技术在农业生产中的广泛应用,农业物联网技术的标准问题已引起了社会的普遍关注。为了保证此项技术在天津市农业生产中运用得当,开展农业物联网标准化工作势在必行。本文针对目前这种情况,构建了一整套科学完整的农业物联网标准体系,用于强化标准实施监督,夯实标准化技术基础,促进农业物联网有序发展,为天津在农业现代化产业发展方面提供重要的标准技术支撑。     

Mitigating and Monitoring Smart City Using Internet of Things

The present trends in smart world reflects the extensive use of limited resources through information and communication technology. The limited resources like space, mobility, energy, etc., have been consumed rigorously towards creating optimized but smart instances. Thus, a new concept of IoT integrated smart city vision is yet to be proposed which includes a combination of systems like noise and air loss monitoring, web monitoring and fire detection systems, smart waste bin systems, etc., that have not been clearly addressed in the previous researches. This paper focuses on developing an effective system for possible monitoring of losses, traffic management, thus innovating smart city at large with digitalized and integrated systems and software for fast and effective implementations. In our proposed system, a real time data analysis is performed. These data are collected by various sensors to analyze different factors that are responsible for such losses. The proposed work is validated on a real case study.     

Dynamic performance modelling and measuring for machine tools with continuous-state wear processes

In this paper, we consider the problem of using empirical continuous-state wear data of machine tools to estimate the dynamic lifetime distribution and to measure the performance of a machining process subject to stochastic tool-wear evolution. Machining systems are dynamic processes whose performance variable is usually characterised by the amount of tool wear that advances gradually with a continuous range of values. To accurately capture the performance of these continuous-state wear processes, neither traditional models such as the binary-state models nor multi-state models are suitable. In this paper, an exponential mixed-effects (EME) model is first developed. The EME model is subsequently transformed into a linear mixed-effects (LME) model to enhance the fit and predictability of the wear process data. The LME models take into consideration the correlations among repeated wear measurements collected at different time points within each subject. We then implement the expectation-maximisation (EM) algorithm to obtain the full maximum likelihood estimates (MLEs) of the parameters of the LME models whose asymptotic normal distributions can be used to acquire approximate confidence intervals and a testing hypothesis for the parameters. In addition, to measure the dynamic performance of tools, the amount of wear over time estimated from LME models is compared with a given tool-failure threshold. Consequently, we obtain the reliability of the tool and the estimation of its residual-lifetime distribution, which is critical information for the tool replacement or maintenance strategy. Finally, the lower and upper wear prediction limits of the 95% confidence level are presented. A practical application of the proposed methodology is illustrated throughout the paper.     

Review of operational management in intelligent agriculture based on the Internet of Things

This review aims to gain insight into the current research and application of operational management in the area of intelligent agriculture based on the Internet of Things (IoT), and consequently, identify existing shortcomings and potential issues. First, we use the Java application CiteSpace to analyze co-citation networks in the literature related to the operational management of IoT-based intelligent agriculture. From the literature analysis results, we identify three major fields: (1) the development of agricultural IoT (Agri-IoT) technology, (2) the precision management of agricultural production, and (3) the traceability management of agricultural products. Second, we review research in the three fields separately in detail. Third, on the basis of the research gaps identified in the review and from the perspective of integrating and upgrading the entire agricultural industry chain, additional research directions are recommended from the following aspects: The operational management of agricultural production, product processing, and product sale and after-sale service based on Agri-IoT. The theoretical research and practical application of combining operational management theories and IoT-based intelligent agriculture will provide informed decision support for stakeholders and drive the further development of the entire agriculture industry chain.     

Performance measurement and management: a system of systems perspective

Despite changes in tools and practices, the conceptual foundations of performance measurement and management (PMM) are still predominantly rooted in control systems research. While PMM approaches have delivered significant organisational benefits, including creating alignment, supporting monitoring and control, and enabling prediction and optimisation of resource allocation, this paper argues that this paradigm is not capable of responding to increasingly complex and highly uncertain organisational environments. Drawing on ideas emerging in the literature on systems engineering and complex systems, we propose a novel perspective that considers PMM from a ‘system of systems’ (SoS) point of view, whose essential characteristics are autonomy, belonging, connectivity, diversity and emergence. After identifying the assumptions underpinning existing PMM approaches, we outline a SoS-based paradigm to PMM and conclude by articulating the main implications for the practice of PMM and setting out a research agenda.     

Intelligent Tunicate Swarm-Optimization-Algorithm-Based Lightweight Security Mechanism in Internet of Health Things

Fog computing in the Internet of Health Things (IoHT) is promising owing to the increasing need for energy- and latency-optimized health sector provisioning. Additionally, clinical data (particularly, medical image data) are a delicate, highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs. Herein, we propose an energy-effi- cient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server. The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize the deterioration of quality between the original and reconstructed (decrypted) images. In this study, the decrypted image quality is preserved by the peak signal-to-noise ratio (PSNR) such that consumers can generate precise medical reports from IoHT devices at the application level. Moreover, a lightweight encryption step is implemented in the fog to improve energy efficiency and reduce additional computations at the cloud server. Experimental results indicate that the TSO-Simon model achieved a high PSNR of 61.37 dB and a pixel change rate of 95.31.     

Antecedents of effective performance measurement system implementation: an empirical study of UK manufacturing firms

This paper examines the antecedents to effective performance measurement system (PMS) implementation. There have been only a few studies which have investigated this topic, and to-date there is no consensus about what factors are significant. Using empirical data collected from 349 UK manufacturing firms, we identify six potential factors from an item pool derived from an extensive literature review. Subsequent regression analysis reveals that all six factors have a significant influence on PMS implementation effectiveness. We characterise these factors into two sub-sets, with the technical sub-set accounting for most of the variance in the dependent variable. We also demonstrate that ‘softer’ social factors additionally have a significant, albeit comparatively small, effect. These, we argue, are essential in order to bind an organisation’s approach to performance measurement into one cohesive whole. Our findings provide managers with a clearer view of the factors which may influence the effectiveness of their PMS implementation. Moreover, we anticipate that the findings should provide empirical stimulation of an important debate about how to ensure that organisations can implement PMSs that are adequate for their purposes. As such, while the findings have current utility, their additional value is in providing a platform for subsequent research.     

Internet of Things Based Solutions for Transport Network Vulnerability Assessment in Intelligent Transportation Systems

Intelligent Transportation System (ITS) is essential for effective identification of vulnerable units in the transport network and its stable operation. Also, it is necessary to establish an urban transport network vulnerability assessment model with solutions based on Internet of Things (IoT). Previous research on vulnerability has no congestion effect on the peak time of urban road network. The cascading failure of links or nodes is presented by IoT monitoring system, which can collect data from a wireless sensor network in the transport environment. The IoT monitoring system collects wireless data via Vehicle-to-Infrastructure (V2I) channels to simulate key segments and their failure probability. Finally, the topological structure vulnerability index and the traffic function vulnerability index of road network are extracted from the vulnerability factors. The two indices are standardized by calculating the relative change rate, and the comprehensive index of the consequence after road network unit is in a failure state. Therefore, by calculating the failure probability of road network unit and comprehensive index of road network unit in failure state, the comprehensive vulnerability of road network can be evaluated by a risk calculation formula. In short, the IoT-based solutions to the new vulnerability assessment can help road network planning and traffic management departments to achieve the ITS goals.     

Exploring self-organization and self-adaption for smart manufacturing complex networks

Trends toward the globalization of the manufacturing industry and the increasing demands for small-batch, short-cycle, and highly customized products result in complexities and fluctuations in both external and internal manufacturing environments, which poses great challenges to manufacturing enterprises. Fortunately, recent advances in the Industrial Internet of Things (IIoT) and the widespread use of embedded processors and sensors in factories enable collecting real-time manufacturing status data and building cyber–physical systems for smart, flexible, and resilient manufacturing systems. In this context, this paper investigates the mechanisms and methodology of self-organization and self-adaption to tackle exceptions and disturbances in discrete manufacturing processes. Specifically, a general model of smart manufacturing complex networks is constructed using scale-free networks to interconnect heterogeneous manufacturing resources represented by network vertices at multiple levels. Moreover, the capabilities of physical manufacturing resources are encapsulated into virtual manufacturing services using cloud technology, which can be added to or removed from the networks in a plug-and-play manner. Materials, information, and financial assets are passed through interactive links across the networks. Subsequently, analytical target cascading is used to formulate the processes of self-organizing optimal configuration and self-adaptive collaborative control for multilevel key manufacturing resources while particle swarm optimization is used to solve local problems on network vertices. Consequently, an industrial case based on a Chinese engine factory demonstrates the feasibility and efficiency of the proposed model and method in handling typical exceptions. The simulation results show that the proposed mechanism and method outperform the event-triggered rescheduling method, reducing manufacturing cost, manufacturing time, waiting time, and energy consumption, with reasonable computational time. This work potentially enables managers and practitioners to implement active perception, active response, self-organization, and self-adaption solutions in discrete manufacturing enterprises.     

物联网语境下现代物流与运输包装设计

目的 本文研究物联网语境下,现代物流的发展与运输包装设计的关系以及未来运输包装设计的新特征和发展趋势。方法 通过分析研究国内外优秀销售包装和运输包装案例以及现代物流系统智能化技术,用互联网设计思维,思考新语境下现代物流行业的发展趋势、对现代包装设计在空间、结构、材料等方面的创新应用,以及运输包装设计的现状和未来发展趋势。结果 为了满足现代物流智能化要求,现代运输包装不仅日益趋向智能化与标准化,而且未来运输包装在结构设计、智能技术与环境保护和资源再生领域也有了新特征。结论 在物联网语境下,设计师应该熟悉运输包装设计新范式,更加注重现代包装设计与现代物流运输的关系,只有在现代运输包装设计发展过程中融合求变,包装创新设计和物流生态才能更加智能可持续。     

Energy-Efficient Transmission Range Optimization Model for WSN-Based Internet of Things

With the explosive advancements in wireless communications and digital electronics, some tiny devices, sensors, became a part of our daily life in numerous fields. Wireless sensor networks (WSNs) is composed of tiny sensor devices. WSNs have emerged as a key technology enabling the realization of the Internet of Things (IoT). In particular, the sensor-based revolution of WSN-based IoT has led to considerable technological growth in nearly all circles of our life such as smart cities, smart homes, smart healthcare, security applications, environmental monitoring, etc. However, the limitations of energy, communication range, and computational resources are bottlenecks to the widespread applications of this technology. In order to tackle these issues, in this paper, we propose an Energy-efficient Transmission Range Optimized Model for IoT (ETROMI), which can optimize the transmission range of the sensor nodes to curb the hot-spot problem occurring in multi-hop communication. In particular, we maximize the transmission range by employing linear programming to alleviate the sensor nodes’ energy consumption and considerably enhance the network longevity compared to that achievable using state-of-the-art algorithms. Through extensive simulation results, we demonstrate the superiority of the proposed model. ETROMI is expected to be extensively used for various smart city, smart home, and smart healthcare applications in which the transmission range of the sensor nodes is a key concern.     

Estimation and monitoring of key performance indicators of manufacturing systems using the multi-output Gaussian process

Recently, the estimation and monitoring of manufacturing key performance indicators (KPIs) have drawn significant attention. In this article, a KPI estimation and monitoring method using a multi-output Gaussian process (MGP) is proposed. The Gaussian process (GP) is an effective non-parametric flexible tool for data-driven statistical modelling for various systems. The unique features of the proposed method is that the MGP enjoys the high flexibility and desirable analytical properties of the GP while also capturing the correlation between different KPIs, thus providing better estimation accuracy and error quantification. The advantageous features of the proposed method are demonstrated through a numerical study as well as a case study with real world data in the estimation and monitoring of throughput for a multiclass production operation.     

电商平台下物联网智能快递箱现状及改进

目的 从实用角度对电商平台下物联网智能快递箱的现状进行研究。方法 根据市场调研情况,综合分析我国当前包装中信息标签隐患较多、外观造型设计品牌识别度较低、RFID芯片利用不够充分和快递箱需要特定条件的循环再利用等方面问题。结论 结合实例论述了未来物联网智能快递箱的改进策略,能为RFID芯片赋能包装安全升级、大数据助力提升包装用户黏性和体验定制个性化包装服务设计,能为物联网智能快递箱设计提供设计思路和切实可行的理论参考。