RFID系统中畅销类标签识别算法的研究

发布时间：2018-02-15 13:23

本文关键词： 射频识别技术畅销类标签时间有效性能量有效性　出处：《太原理工大学》2015年硕士论文　论文类型：学位论文

【摘要】：最早的射频识别技术（Radio Frequency Identification，RFID）源于20世纪90年代，它是人类在科技发展道路上的重大进展，改变了人类的消费方式与习惯。随着射频识别技术的逐渐成熟，该技术越来越多地被人们应用于物流业、智能门禁系统、目标定位、追踪和识别等关键应用，且其所具备的优越性已日益受到全国的重视与应用，它的发展状况成为各界瞩目的焦点。所谓畅销类产品就是指该类别的产品数量超过了一定的阈值，其具有鲜明的季节性特点。在商品的销售过程中，商家往往希望了解顾客的喜好，找出比较畅销的几类产品，来决定下一步的营销策略。由于用户需求和喜好的不同，再加上其他等等因素的影响，畅销类产品是在实时变化的，而并不是一成不变的。因此，随时对产品进行不断调整并对销售状况进行实时跟踪变得越来越重要。而RFID技术的出现，，很好的满足了这种实时性的需求，只需在待识别的物品上附着RFID电子标签，经过相应的算法便能及时查找出畅销类产品，便于商家日后更好地进行销售。现有的关于识别畅销类标签的算法都必须扫描范围内的所有标签来进行识别，且这些算法都只关注于时间的研究，并没有对能量进行研究。针对这些不足，本文提出了反向阈值（Reserve Threshold-Based Scheme，RTBS）畅销类标签识别算法和正向阈值（Positive Threshold-Based Scheme，PTBS）畅销类标签识别算法，这两种算法的主要目的是在众多标签中以高效、节能的方式识别出畅销类标签。RTBS和PTBS算法不仅能够对阅读器识别范围内的一个标签子集进行畅销类标签的识别，而且还首次考虑到了识别畅销类标签过程中的能量问题。首先，RTBS和PTBS两种算法都是从所有标签中找出指定集合中的标签，然后，通过Hash函数选取样本标签并进行映射，其次，通过阅读器和标签之间的通信获取时隙的状态并对其进行分析和处理，从而识别出畅销类标签。不同的是，RTBS采用的是反向思维方式，而PTBS采用的是正向思维方式。且在搜索阶段，RTBS算法采用的是基础的点名‖机制，即广播标签的类别ID；而PTBS算法采用的是双布鲁姆滤波器取交集的方法。仿真结果表明，RTBS和PTBS两种算法都够识别出来畅销类标签，并都具有时间有效性和能量有效性。
[Abstract]:Radio Frequency Identification (RFID), the earliest RFID technology, originated in 1990s. It is a great progress in the development of science and technology, and has changed human consumption patterns and habits. This technology has been used more and more in the logistics industry, intelligent access control system, target positioning, tracking and identification and other key applications, and its advantages have been paid more and more attention and application. Its development status has become the focus of attention from all walks of life. The so-called best-selling products mean that the number of products in this category exceeds a certain threshold and has distinctive seasonal characteristics. In the process of selling goods, merchants often want to know the preferences of customers and find out some of the best-selling products. To determine the next marketing strategy. Because of different user needs and preferences, and other factors, the best-selling products are changing in real time, not inflexible. It is becoming more and more important to constantly adjust the product and track the sales status in real time. However, the appearance of RFID technology can meet the requirement of real time, just attach RFID tag to the object to be identified. After the corresponding algorithm can find out the best-selling products in time, so that merchants can sell better in the future. Existing algorithms for identifying best-selling class tags must scan all tags in range, and these algorithms focus only on time, not on energy. In this paper, we propose a reverse threshold Threshold-Based Threshold-Based Schema) best-selling class label recognition algorithm and a forward threshold Positive Threshold-Based Schema best-selling class label recognition algorithm. The main purpose of these two algorithms is to achieve high efficiency in a large number of tags. The best selling class tags. RTBS and PTBS algorithm can not only identify a subset of the best selling class tags in the recognition range of readers, but also consider the energy problem in the process of identifying the best selling class labels for the first time. First, the two algorithms of PTBS and RTBS are to find out the tags in the specified collection from all the tags, then, the sample labels are selected and mapped through the Hash function. Secondly, Through the communication between readers and tags, the status of time slots is obtained, analyzed and processed to identify the best-selling class tags. The difference is that RTBS uses reverse thinking. PTBS adopts a positive thinking mode, and in the search phase, it uses the basic naming mechanism. The PTBS algorithm uses a double Bloom filter to select the intersection method. The simulation results show that both the two algorithms can identify the best-selling class labels, and both have time-efficient and energy-efficient.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP391.44

【参考文献】