Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

This paper presents a comprehensive review of emerging technologies for the internet of things(IoT)-based smart agriculture.We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT,such as unmanned aerial vehicles,wireless technologies,open-source IoT platforms,software defined networking(SDN),network function virtualization(NFV)technologies,cloud/fog computing,and middleware platforms.We also provide a classification of IoT applications for smart agriculture into seven categories:including smart monitoring,smart water management,agrochemicals applications,disease management,smart harvesting,supply chain management,and smart agricultural practices.Moreover,we provide a taxonomy and a side-by-side comparison of the state-ofthe-art methods toward supply chain management based on the blockchain technology for agricultural IoTs.Furthermore,we present real projects that use most of the aforementioned technologies,which demonstrate their great performance in the field of smart agriculture.Finally,we highlight open research challenges and discuss possible future research directions for agricultural IoTs.     

基于物联网与互联网的电动车充电系统设计

为了提高电动车充电的安全性与稳定性,该文设计了一种基于物联网互联网的电动车充电系统,系统主要由网络层、控制层与使用层构成,具有电路监控、过载保护及插座防拔功能。系统选用STM32F407作为主控芯片,利用ESP8266进行TCP网络通讯,用户通过APP(用户终端),可以实时获取充电系统的功率值且可对充电系统下达通电、断电及开锁指令,主控芯片STM32F407通过ESP8266接收到指令后,根据指令内容完成相关操作。系统具有网络化、智能化的特点,且可扩展预约、视频监控等功能。     

基于区块链的分布式物联网信任管理方法研究

随着物联网(Internet of things, IoT)技术的发展,在不同的物联网之间逐渐形成了大规模、异构化、动态化的分布式物联网环境.分布式物联网内的设备间与物联网管理机构间存在着广泛的合作需求,为此需要在其中建立信任机制以促进合作.然而,现有的信任机制研究大部分脱离于物联网环境,没有考虑物联网设备计算与存储能力有限且差异较大这一特点,造成抽象信任机制研究无法直接应用于物联网中;另一方面,现有的物联网信任问题研究都依赖于额外的可信第三方或域间信任假设,这在实际中是难以实现的.为了解决上述问题,借助区块链与风险理论,提出一种适用于分布式物联网的信任管理方法.具体地,将信任量化为对期望信用与风险的考察,并借助区块链实现信任数据的有效共享与安全性.实验与分析表明:该方案能够有效量化信任,保护数据不被篡改,且能够以较低的存储开销维护系统的正常运行.     

Implementation path and reference framework for Industrial Internet Platform (IIP) in product service system using industrial practice investigation method

With the development of intelligent sensing, edge computing, fog computing, cloud computing, parallel computing, smart grid, big data, block chain, 5G, cyber-physical systems, digital twins, machine learning and other technologies, the industrial internet has undergone control network stage, sensor network stage, internet stage, Internet of Things (IoT) stage, Industrial Internet of Things (IIoT) stage, and Industrial Internet (II) stage, etc. In the existing research, scholars focus on a local dot, such as: technology, function, elements and application based on industrial internet. However, there is a lack of an overall framework to study the top-level planning of Industrial Internet Platform (IIP) from a systematic perspective. On the other hand, there are few studies on the detailed path and steps for implementing IIP in a specific enterprise in a specific industry. The objective of this paper is to study a reference framework and industrial implementation path for IIP in product service system using industrial practice investigation method, which meets the needs of industry on the basis of existing theory and industrial practice, and to provide reference for government and industry planning, design, implementation and promotion of IIP. In addition, the proposed reference framework and industrial implementation for IIP in product service system can enhance the core value of the enterprise and increase benefits.     

RFID-based Production Data Analysis in an IoT-enabled Smart Job-shop

Under industry 4.0, internet of things (IoT), especially radio frequency identification (RFID) technology, has been widely applied in manufacturing environment. This technology can bring convenience to production control and production transparency. Meanwhile, it generates increasing production data that are sometimes discrete, uncorrelated, and hard-to-use. Thus, an efficient analysis method is needed to utilize the invaluable data. This work provides an RFID-based production data analysis method for production control in IoT-enabled smart job-shops. The physical configuration and operation logic of IoT-enabled smart job-shop production are firstly described. Based on that, an RFID-based production data model is built to formalize and correlate the heterogeneous production data. Then, an eventdriven RFID-based production data analysis method is proposed to construct the RFID events and judge the process command execution. Furthermore, a near big data approach is used to excavate hidden information and knowledge from the historical production data. A demonstrative case is studied to verify the feasibility of the proposed model and methods. It is expected that our work will provide a different insight into the RFIDbased production data analysis.      

ResIoT: An IoT Social Framework Resilient to Malicious Activities

The purpose of the next internet of things (IoT) is that of making available myriad of services to people by high sensing intelligent devices capable of reasoning and real time acting. The convergence of IoT and multi-agent systems (MAS) provides the opportunity to benefit from the social attitude of agents in order to perform machine-to-machine (M2M) coopera-tion among smart entities. However, the selection of reliable partners for cooperation represents a hard task in a mobile and federated context, especially because the trustworthiness of devices is largely unreferenced. The issues discussed above can be synthesized by recalling the well known concept of social resilience in IoT systems, i.e., the capability of an IoT network to resist to possible attacks by malicious agent that potentially could infect large areas of the network, spamming unreliable infor-mation and/or assuming unfair behaviors. In this sense, social resilience is devoted to face malicious activities of software agents in their social interactions, and do not deal with the correct working of the sensors and other information devices. In this setting, the use of a reputation model can be a practicable and effective solution to form local communities of agents on the basis of their social capabilities. In this paper, we propose a framework for agents operating in an IoT environment, called ResIoT, where the formation of communities for collaborative purposes is performed on the basis of agent reputation. In order to validate our approach, we performed an experimental campaign by means of a simulated framework, which allowed us to verify that, by our approach, devices have not any economic convenience to performs misleading behaviors. Moreover, further experimental results have shown that our approach is able to detect the nature of the active agents in the systems (i.e., honest and malicious), with an accuracy of not less than 11% compared to the best competitor tested and highlighting a high resilience with respect to some malicious activities.      

Security challenges in internet of things: Distributed denial of service attack detection using support vector machine-based expert systems

The rapid development of internet of things (IoT) is to be the next generation of the IoT devices are a simple target for attackers due to the lack of security. Attackers can easily hack the IoT devices that can be used to form botnets, which can be used to launch distributed denial of service (DDoS) attack against networks. Botnets are the most dangerous threat to the security systems. Software-defined networking (SDN) is one of the developing filed, which introduce the capacity of dynamic program to the network. Use the flexibility and multidimensional characteristics of SDN used to prevent DDoS attacks. The DDoS attack is the major attack to the network, which makes the entire network down, so that normal users might not avail the services from the server. In this article, we proposed the DDoS attack detection model based on SDN environment by combining support vector machine classification algorithm is used to collect flow table values in sampling time periods. From the flow table values, the five-tuple characteristic values extracted and based on it the DDoS attack can be detected. Based on the experimental results, we found the average accuracy rate is 96.23% with a normal amount of traffic flow. Proposed research offers a better DDoS detection rate on SDN.     

医院物联网体系结构和关键技术研究

医院物联网是物联网技术在医疗行业应用的集中体现。在简单介绍医院物联网基本概念的基础上,结合物联网机制和医院的实际特点,探讨了适用于医院物联网的体系结构,并分析了构建中的关键技术,包括医院物联网的标准建设、中间件技术及嵌入式电子病历的研究与设计等。     

移动医疗的建设与发展

通过物联网,移动与传统互联网,在生物医学领域产生了大数据.移动医疗云就是通过移动云计算的形式打造医学大数据信息处理平台,分析了移动查房,移动护理,远程监护及医疗设备、物资与医护人员跟踪与管理等多个移动医疗领域的应用,最后针对移动医疗发展中存在的问题及目前国际发展状况,提出了移动医疗最终的发展方向-无边界健康医疗服务模式的新概念.     

An IoT-Aware System for Managing Patients’ Waiting Time Using Bluetooth Low-Energy Technology

It is a common observation that whenever patients arrives at the front desk of a hospital, outpatient clinic, or other health-associated centers, they have to first queue up in a line and wait to fill in their registration form to get admitted. The long waiting time without any status updates is the most common complaint, concerning health officials. In this paper, UrNext, a location-aware mobile-based solution using Bluetooth low-energy (BLE) technology is presented to solve the problem. Recently, a technology-oriented method, the Internet of Things (IoT), has been gaining popularity in helping to solve some of the healthcare sector’s problems. The implementation of this solution could be illustrated through a simple example of when a patient arrives at a clinic for a consultation. Instead of having to wait in long lines, that patient will be greeted automatically, receive a push notification of an admittance along with an estimated waiting time for a consultation session. This will not only provide the patients with a sense of freedom but would also reduce the uncertainty levels that are generally observed, thus saving both time and money. This work aims to improve the clinics’ quality of services, organize queues and minimize waiting times, leading to patients’ comfort while reducing the burden on nurses and receptionists. The results demonstrate that the presented system is successful in its performance and helps achieves a pleasant and conducive clinic visitation process with higher productivity.     

基于物联网技术的材料实验加热炉测控系统的设计

材料实验加热炉是实现材料加热工艺过程非常重要的热工设备,为改变传统加热实验长时间现场值守带来的劳动强度大,排放气体危害科研人员身体健康不利的状况,该文根据物联网测量与控制的基本理论,设计包含感知执行层、网络传输层、控制服务层、移动应用层等4层结构的物联网测控系统,并对各层的设计组成与功能进行了详细的论述。该文重点讲解了控制服务层、移动应用层中软件各模块组成,最后讨论了该物联网系统中数据采集数字滤波算法、加热炉数字增量型PID控制算法以及系统上下层通信算法设计。     

复杂软件系统的不确定性

复杂软件系统(如信息物理系统CPS、物联网IoT以及自适应软件系统等)在其开发和运行过程中会遇到各种类型的不确定性问题.针对这些不确定性问题,研究人员开展了大量的研究工作,提出了一系列的方法,取得了诸多成果.然而,由于此类系统本身固有的复杂性和其内在与外在不确定性的共同作用,截止目前研究人员针对该研究领域仍然缺乏系统性...     

物联网中RFID位匹配防碰撞算法*

在对现有的二进制搜索算法、4线树形查询算法及混合查询树算法进行理论分析的基础上,提出了一种基于碰撞位匹配的自适应混合树防碰撞算法。新算法是根据检测标签EPC编码最高碰撞位连续个数的匹配信息,在二叉树和四叉树中进行动态自适应地选择分叉数,引入堆栈和后退策略,使得搜索性能进一步改善。通过对算法的分析和仿真实验结果,新算法有效地减少了识别总次数,缩短了识别时间,大幅提高了搜索效率和吞吐率。     

Petri网的水产品溯源系统模型

提出了一种基于射频识别(RFID)的Petri网在水产品全程质量追踪和溯源系统应用的方法,以构建高效的基于物联网技术的水产品溯源与安全预警平台.根据实际水产品业务流和信息流,利用Petri网进行建模,然后在CPN Tools环境进行仿真.仿真结果表明:该建模方法简单、可行,能够验证工作流模型的有效性,而且便于计算机形式化表达和优化分析,有利于工作流管理系统的实现和性能提高,一定程度上提高了供应链的效率,从而降低了流通的成本和质量风险.     

一种面向物联网应用的通用网关平台的设计

通信网络的多样性导致的信息割裂是物联网物与物互联互通目标的一个障碍,物联网网关正是为解决异构网络之间互联互通而提出的,是物联网应用系统中重要的基础设备.该文介绍了一个采用面向对象思想设计的与异构网络无关的可移植、易扩展、松耦合的通用物联网网关平台G2W,旨在解决传统网关面对新的应用场景和需求适应性差的问题.G2的软件架构按照网关数据处理流程分通信抽象、数据编解码和应用服务3层,文中详细介绍了每一层的功能目标和实现方式.最后给出一个基于G2w设计的Z-GateWay网关实例和基于Z-GateWay实现的数采系统.     

Intelligent Intrusion Detection for Industrial Internet of Things Using Clustering Techniques

The rapid growth of the Internet of Things (IoT) in the industrial sector has given rise to a new term: the Industrial Internet of Things (IIoT). The IIoT is a collection of devices, apps, and services that connect physical and virtual worlds to create smart, cost-effective, and scalable systems. Although the IIoT has been implemented and incorporated into a wide range of industrial control systems, maintaining its security and privacy remains a significant concern. In the IIoT contexts, an intrusion detection system (IDS) can be an effective security solution for ensuring data confidentiality, integrity, and availability. In this paper, we propose an intelligent intrusion detection technique that uses principal components analysis (PCA) as a feature engineering method to choose the most significant features, minimize data dimensionality, and enhance detection performance. In the classification phase, we use clustering algorithms such as K-medoids and K-means to determine whether a given flow of IIoT traffic is normal or attack for binary classification and identify the group of cyberattacks according to its specific type for multi-class classification. To validate the effectiveness and robustness of our proposed model, we validate the detection method on a new driven IIoT dataset called X-IIoTID. The performance results showed our proposed detection model obtained a higher accuracy rate of 99.79% and reduced error rate of 0.21% when compared to existing techniques.     

An enhanced MSU-TSCH scheduling algorithms for industrial wireless sensor networks

The reliability and latency requirements of wireless sensor network-based smart grid communications are met in large part by MAC protocols. Developed by IEEE, time slotted channel hopping (TSCH), a method that is effective, dependable, and predictable. However, the TSCH standard does not enable mobility and does not offer any solution for scheduling, especially in IEEE 802.15.4 TSCH, the most recent generation of extremely dependable and low-power MAC protocols. Recently, MSU-TSCH a time-frequency communication schedule was proposed to provide mobility to TSCH. Despite its distinctive qualities, MSU-TSCH has the drawback of computing the TSCH schedule at each node independently of its traffic load, which can significantly increase the communication delay. Due to this limitation, MSU-TSCH is not suitable for some delay-sensitive smart grid applications. In this article, we provide an improved MSU-TSCH-based TSCH protocol, called Mobility-TSCH, that dynamically adjusts time slot assignments based on traffic volume and latency requirement. Moreover, the protocol Mobility-TSCH adapts to topology changes and supports mobility. Additionally, it optimizes time slot allocation by prioritizing nodes closest to the sink. The performance and evaluation analysis of Mobility-TSCH compared to the original MSU-TSCH, reveal that the communication delay is greatly reduced, decreases the average end-to-end latency, the high packet delivery ratio (PDR), Increase the performance of both metrics, parent connectivity ratio (PCR) and convergence time (CT), while maintaining a minimal overhead signaling.     

物联网技术在医疗领域的研究进展*

从药品领域、远程监护、医疗信息化、医疗设备管理等多个方面详细讨论了物联网技术在医疗领域的应用现状,并在医疗物联网、物联网医学和健康物联网等概念的基础上,分析了目前物联网技术在医疗领域的研究现状。最后指出了医疗领域下物联网研究中有待解决的关键问题,包括面向医疗行业的物联网系统标准、电子病历的相关问题,以及病人数据安全和隐私保护问题等。     

基于集群架构的物联网终端动态认证仿真

为有效提高物联网终端认证的安全性,基于集群架构对物联网终端动态进行认证仿真。设计的认证策略主要基于双注册因子和对应认证结构,包括常数量和编码特征密匙,在此基础上设定集群架构下物联网双因子注册流程,第一认证因子与服务器达成一致,通过用户初始注册信息终端服务器生成注册凭证,第二因子通过SAS服务器认证,并生成注册会话密匙,完成最终双因子注册,根据注册因子,以X.509V3作为核心签发结构,构造认证数字证书,搭配公共密匙基础设置(PKI),确定身份认证协议,采用"挑战-应答"的形式完成物联网移动终端的认证实现集群架构下,当前物联网终端的整体认证工作。实验数据表明,在标准内核攻击下,设计的物联网终端认证方法可以有效保证自身数据的完整性,提高认证安全和可信性。     

微弱能量收集电路技术的研究现状与发展趋势

随着物联网的发展和无线传感器网络的广泛使用,以电池为主的供能方式弊端日渐显露,微弱能量收集因其诸多优点而得到了极大重视.介绍了目前微弱能量收集电路技术研究的现状,对目前的微弱能量收集电路技术进行了分析,阐述了多种微弱能量的收集,介绍了目前高效率的微弱能量收集电路的设计模式.结合目前微弱能量收集电路的优缺点,展望了能量收集电路技术未来的研究趋势和方向.