New tag estimator for the dynamic framed slotted Aloha anti-collision algorithm in RFID systems

Radio frequency identification (RFID) technology is a wireless identification technique that has been used in many fields. This paper investigates the use of this technology for traffic monitoring which is the backbone of any intelligent transportation system. One of the main issues that face this technology is tag collisions. This study examines the performance of two known anti-collisions protocols: the Basic Framed Slotted Aloha (BFSA) and the Dynamic Framed Slotted Aloha (DFSA). For such application, it was found that the DFSA method outperforms the BFSA method. However, the DFSA method requires the use of tag estimator. For this reason, the study compares also the performance of three tag estimators associated with the DFSA: Vogt, Zhen and Schoute. It is observed that the Vogt method is the best if the number of tags is low, while the Schoute approach is superior for higher value. The study proposes a new hybrid tag estimator that combines the strength of the Vogt and Schoute approaches

Tag anti-collision algorithms in RFID systems - a new trend

RFID is a wireless communication technology that provides automatic identification or tracking and data collection from any tagged object. Due to the shared communication channel between the reader and the tags during the identification process in RFID systems, many tags may communicate with the reader at the same time, which causes collisions. The problem of tag collision has to be addressed to have fast multiple tag identification process. There are two main approaches to the tag collision problem: ALOHA based algorithms and tree based algorithms. Although these methods reduce the collision and solve the problem to some extent, they are not fast and efficient enough in real applications. A new trend emerged recently which takes the advantages of both ALOHA and tree based approaches. This paper describes the process and performance of the tag anti-collision algorithms of the tree-ALOHA trend

Modeling and simulation of an IoT enabled cold Chain Logistics management system

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Dünya ekonomisinin etkileyici bir şekilde büyümesi, soğuk zincirde izlenmesi ve yönetilmesi gereken özellikle sıcaklık duyarlı ürünler için belirsizlik durumları karşısında etkin, esnek ve duyarlı olabilmek amacıyla lojistik hizmetleri talep eden tedarik zincirinde artış sağlamıştır. Bunun gerçekleştirilebilmesi için Lojistik şirketerinin uygun bilişim teknolojileri ile desteklenmesi gerekmektedir. İnternet kullanımı ile müşteri ve lojistik sağlayıcı arasında etkili bir bilgi akışı ortamı sağlanmaktadır; ancak lojistik hizmetindeki bilgi ve ürün akışı arasındaki mevcut açıklık, sıcaklık duyarlı nesneler hakkında gerçek zamanlı bilginin elde edilmesinde karar vericiler için lojistik yönetimini daha zor duruma getiren bir problem oluşturmaktadır. Nesnelerin İnterneti alanındaki gelişmeler soğuk zincir sanayilerinde izleme, yönetme ve gerçek zamanlı görünürlük sağlama ve uygun zeka seviyesi ile bilgi paylaşımı alanında potensiyel çözümler sunmaktadır. Bu çalışmada soğuk zincirin gerçek zamanlı ortam sıcaklığını izleme, yönetme ve soğuk zincir içerisindeki sıcaklık duyarlı ürünlerin raf ömrünün tahmin edilmesi aracılığıyla tüm karar vericilerin karar desteklerini geliştirmeye yardımcı olan IoT erişimli soğuk zincir lojistiği gösterilemektedir. Çalışma içerisinde, gerçek zamanlı ortam verileri IEEE 802.15.4 kablosuz algılayıcı ağ yapısı kullanılarak elde edilmiş ve toplanan veriler bir ağ geçidi aracılığıyla sunucuya, ürünlerin raf ömürlerinin geliştirilen karar destek sistemi yardıyla tahmin edilebilmesini sağlamak üzere, gönderilmiştir. Ayrıca, soğuk zincir içerisindeki bozulabilir ürünlerin tespiti için Radyo Frekanslı Tanıma (Radio Frequency Identification-RFID) kullanılmıştır. Çalışma içerisinde kullanılan tüm cihazlar ve protokoller olay-güdümlü Riverbed Modeler yazılımıyla modellenerek benzetimleri yapılmıştır.The Dramatic growth of world economy results growth in the supply chain which demands logistics service to be agile, flexible and responsive in the face of uncertainty, especially for temperature sensitive products that need to be monitored and managed in the cold chain. To achieve this, Logistics companies must be supported by appropriate information technologies. Internet provides an effective means of driving information between customer and logistics provider, however, existing gap between products flow and information flow in logistic service has created a problem in getting real-time information about temperature sensitive items which make logistics management more challenging for decision makers. The growth of internet of things (IoT) gives a potential solution for monitoring, managing, and achieving real-time visibility and sharing information with the appropriate level of intelligence in cold chain industries. This paper demonstrates IoT enabled cold chain logistics that helps to enhance the decision support of all actors through managing, monitoring the real-time ambient temperature of the cold chain and predicting the shelf-life of temperature sensitive products inside the cold chain. In the study, real-time data of ambient parameters are gathered using IEEE 802.15.4 based wireless sensor networks and sent to the remote server through a gateway so that the shelf life of the products can be predicted by the decision support system developed. Radio Frequency Identification (RFID) is also used for identification of perishable goods inside the cold chain. All the devices and protocols employed in the study are modeled and simulated using event-driven Riverbed Modeler software

An adaptive RFID anti-collision algorithm based on dynamic framed ALOHA

The collision of ID signals from a large number of co-located passive RFID tags is a serious problem; to realize a practical RFID systems we need an effective anti-collision algorithm. This letter presents an adaptive algorithm to minimize the total time slots and the number of rounds required for identifying the tags within the RFID reader's interrogation zone. The proposed algorithm is based on the framed ALOHA protocol, and the frame size is adaptively updated each round. Simulation results show that our proposed algorithm is more efficient than the conventional algorithms based on the framed ALOHA.open1114sciescopu

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts