基于RFID智能感知摄像机的溯源系统

近年来,食品安全案件屡有发生,亟需采用透明、安全、可信的食品安全溯源系统。然而现有的溯源系统高额的视频监测储存和传输费用,限制了溯源平台的推广。设计基于RFID具备联动功能的智能感知摄像机,采用自修复机制改进基于RFID的LANDMARC定位算法,精准定位每一只牲畜的活动区域;利用联动摄像头定量采集牲畜活动信息,建立牲畜活动信息;通过GPRS将采集的照片上传到服务器,极大降低视频存储和传输成本。同时将摄像头的功耗降到最低,使其能在野外用太阳能板为系统供电。用户可以通过扫描二维码查询牲畜档案信息,极大降低绿色健康畜产品溯源成本,推动溯源系统的广泛应用。     

Ztreamy: A middleware for publishing semantic streams on the Web

In order to make the semantic sensor Web a reality, middleware for efficiently publishing semantically-annotated data streams on the Web is needed. Such middleware should be designed to allow third parties to reuse and mash-up data coming from streams. These third parties should even be able to publish their own value-added streams derived from other streams and static data. In this work we present Ztreamy, a scalable middleware platform for the distribution of semantic data streams through HTTP. The platform provides an API for both publishing and consuming streams, as well as built-in filtering services based on data semantics. A key contribution of our proposal with respect to other related systems in the state of the art is its scalability. Our experiments with Ztreamy show that a single server is able, in some configurations, to publish a real-time stream to up to 40 000 simultaneous clients with delivery delays of just a few seconds, largely outperforming other systems in the state of the art.     

A mobile crowd sensing ecosystem enabled by CUPUS: Cloud-based publish/subscribe middleware for the Internet of Things

Mobile crowd sensing (MCS) is a novel class of mobile Internet of Things (IoT) applications for community sensing where sensors and mobile devices jointly collect and share data of interest to observe phenomena over a large geographic area. The inherent device mobility and high sensing frequency has the capacity to produce dense and rich spatiotemporal information about our environment, but also creates new challenges due to device dynamicity and energy constraints, as well as large volumes of generated raw sensor data which need to be processed and analyzed to extract useful information for end users. The paper presents an ecosystem for mobile crowd sensing which relies on the CloUd-based PUblish/Subscribe middleware (CUPUS) to acquire sensor data from mobile devices in a flexible and energy-efficient manner and to perform near real-time processing of Big Data streams. CUPUS has unique features compared to other MCS platforms: It enables management of mobile sensor resources within the cloud, supports filtering and aggregation of sensor data on mobile devices prior to its transmission into the cloud based on global data requirements, and can push information of interest from the cloud to user devices in near real-time. We present our experience with implementation and deployment of an MCS application for air quality monitoring built on top of the CUPUS middleware. Our experimental evaluation shows that CUPUS offers scalable processing performance, both on mobile devices and within the cloud, while its data propagation delay is mainly affected by transmission delay on wireless links.     

Effect verification of external factor to readability of RFID transponder using least square method

RFID technology is currently one of the most progressively growing identification technologies. It provides a huge potential of use in various fields of industry. The positive impact of its implementation can be monitored also by the rationalization of processes and it became the main basis for the concept of Industry 4.0 for this reason. The article concerns the experimental verification of qualitative properties of the RFID transponder by using regression analysis and experiment in laboratory conditions of expert laboratory. On the basis of experimental measurements, they were created regression models of the impact of external factors acting on the readability of the RFID transponder. The main objective of this study is to present the results of mathematical and statistical approach for verification the declared properties of the RFID transponder are which intended to serve as a basis for implementation of the proposed system into real conditions of the practice.     

基于RFID技术的智能书架系统的总体架构设计

对智能书架系统的总体架构进行了设计,在RFID技术基础之上设计了高校图书馆智能书架三级层系结构,并对系统的应用进行初步测试,结果表明本系统能够对图书馆书架上的图书进行准确定位,实现了图书的智能管理.     

Deployment strategy for static chargers in WRSN

The traditional deployment strategy of static chargers in wireless rechargeable sensor networks (WRSN) covers all the area.The basic idea is to cover all the positions of nodes.A mathematical model of distance between a charger and the farthest node was established,the relationship between the number of nodes and the mathematical expectation of minimum radius of charging was analyzed,and deployment strategy for static chargers was proposed.The method based on the locations of all nodes that need to be charged in the area,used the smallest enclosing circle (SEC) algorithm and finds the optimal location of the charger through Euclidean delivery boy algorithm.It will decrease charging radius,reduce the minimum required transmitted power,thereby saving the average charging energy consumption.The experimental results demonstrated that the less the number locations that the nodes existed,the more energy will be saved.     

基于RFID高校运动会信息管理系统实现

为了便于高校运动会中信息的管理,提出了基于RFID高校运动会的信息管理系统。本文分析了高校运动会信息管理系统的需求,设计了基于RFID运动会信息管理的整体系统,并详细设计了识别系统即RFID系统。     

Adaptive hierarchical artificial immune system and its application in RFID reader collision avoidance

This paper proposes an efficient adaptive hierarchical artificial immune system (AHAIS) for complex global optimization problems. In the proposed AHAIS optimization, a hierarchy with top-bottom levels is used to construct the antibody population, where some antibodies with higher affinity become the top-level elitist antibodies and the other antibodies with lower affinity become the bottom-level common antibodies. The elitist antibodies experience different evolutionary operators from those common antibodies, and a well-designed dynamic updating strategy is used to guide the evolution and retrogradation of antibodies between two levels. In detail, the elitist antibodies focus on self-learning and local searching while the common antibodies emphasize elitist-learning and global searching. In addition, an adaptive searching step length adjustment mechanism is proposed to capture more accurate solutions. The suppression operator introduces an upper limit of the similarity-based threshold by considering the concentration of the candidate antibodies. To evaluate the effectiveness and the efficiency of algorithms, a series of comparative numerical simulations are arranged among the proposed AHAIS, DE, PSO, opt-aiNet and IA-AIS, where eight benchmark functions are selected as testbeds. The simulation results prove that the proposed AHAIS is an efficient method and outperforms DE, PSO, opt-aiNet and IA-AIS in convergence speed and solution accuracy. Moreover, an industrial application in RFID reader collision avoidance also demonstrates the searching capability and practical value of the proposed AHAIS optimization.     

Accounting for variability in the design of circuits with organic thin-film transistors

We experimentally verify that the methodology to account for local parameter variations and transistor mismatch known in Si CMOS technologies can be transposed to organic thin-film transistor technologies, and we present a design case that makes use of design for variability. Transistor parameter variation decreases with the square root of the transistor footprint. As a consequence, Monte Carlo simulations which take this effect into account can be executed to better predict the final circuit yield. The design case in this work is an 8-bit, organic RFID transponder chip. The yield prediction by simulations corresponds to the finally observed circuit yield.     

一种符合EPCCIG2协议的RFID反向链路数据解码技术的实现

针对物联网协议EPcc1G2中反向链路数据的解码技术，以精简硬件资源和提高解码效率为目标，给出了基于MCU硬件平台，并利用其中TIMER模块和ADC模块实现反向链路数据解码技术的设计分析和实现思路，同时以实际运用中对FM0解码实现为实例，对解码效果、关键技术点进行了分析；还在结论中将此解码技术与常用技术方案进行了扼要比较，阐明了相关技术特点，得出了本技术的比较优势。