A Review on Missing Tags Detection Approaches in RFID System

Radio Frequency Identification (RFID) system can provides automatic detection on very large number of tagged objects within short time. With this advantage, it is been using in many areas especially in the supply chain management, manufacturing and many others. It has the ability to track individual object all away from the manufacturing factory until it reach the retailer store. However, due to its nature that depends on radio signal to do the detection, reading on tagged objects can be missing due to the signal lost. The signal lost can be caused by weak signal, interference and unknown source. Missing tag detection in RFID system is truly significant problem, because it makes system reporting becoming useless, due to the misleading information generated from the inaccurate readings. The missing detection also can invoke fake alarm on theft, or object left undetected and unattended for some period. This paper provides review regarding this issue and compares some of the proposed approaches including Window Sub-range Transition Detection (WSTD), Efficient Missing-Tag Detection Protocol (EMD) and Multi-hashing based Missing Tag Identification (MMTI) protocol. Based on the reviews it will give insight on the current challenges and open up for a new solution in solving the problem of missing tag detection

Building efficient wireless infrastructures for pervasive computing environments

Pervasive computing is an emerging concept that thoroughly brings computing devices and the consequent technology into people\u27s daily life and activities. Most of these computing devices are very small, sometimes even invisible , and often embedded into the objects surrounding people. In addition, these devices usually are not isolated, but networked with each other through wireless channels so that people can easily control and access them. In the architecture of pervasive computing systems, these small and networked computing devices form a wireless infrastructure layer to support various functionalities in the upper application layer.;In practical applications, the wireless infrastructure often plays a role of data provider in a query/reply model, i.e., applications issue a query requesting certain data and the underlying wireless infrastructure is responsible for replying to the query. This dissertation has focused on the most critical issue of efficiency in designing such a wireless infrastructure. In particular, our problem resides in two domains depending on different definitions of efficiency. The first definition is time efficiency, i.e., how quickly a query can be replied. Many applications, especially real-time applications, require prompt response to a query as the consequent operations may be affected by the prior delay. The second definition is energy efficiency which is extremely important for the pervasive computing devices powered by batteries. Above all, our design goal is to reply to a query from applications quickly and with low energy cost.;This dissertation has investigated two representative wireless infrastructures, sensor networks and RFID systems, both of which can serve applications with useful information about the environments. We have comprehensively explored various important and representative problems from both algorithmic and experimental perspectives including efficient network architecture design and efficient protocols for basic queries and complicated data mining queries. The major design challenges of achieving efficiency are the massive amount of data involved in a query and the extremely limited resources and capability each small device possesses. We have proposed novel and efficient solutions with intensive evaluation. Compared to the prior work, this dissertation has identified a few important new problems and the proposed solutions significantly improve the performance in terms of time efficiency and energy efficiency. Our work also provides referrable insights and appropriate methodology to other similar problems in the research community

Enhancing RFID data quality and reliability

This thesis addressed the problem of data quality, reliability and energy consumption of networked Radio Frequency Identification systems for business intelligence applications decision making processes. The outcome of the research substantially improved the accuracy and reliability of RFID generated data as well as energy depletion thus prolonging RFID system lifetime

Batch study on COD and ammonia nitrogen removal using granular activated carbon and cockle shells

Landfills generate leachate that contains elevated concentration of contaminants and is hazardous to human health and the ecosystem. In this study, the mixture of granular activated carbon and cockle shells was investigated for remediation of COD and ammonia from stabilized landfill leachate. All adsorbent media were sieved to a particle size between 2.00 and 3.35 mm. The optimum mixing ratio, shaking speed, shaking time, pH, and dosage were determined. Characterization results show that the leachate had a high concentration of COD (1763 mg/L), ammonia nitrogen (573 mg/L), and BOD5/COD ratio (0.09). The optimum mixing ratio of granular activated carbon and cockle shells was 20:20, shaking speed 150 rpm, pH level 6, shaking time 120 min, and dosage 32 g. The adsorption isotherm analysis reveals that the Langmuir isotherm yielded the best fit to experimental data as compared with the Freundlich isotherm. The media produce encouraging results and can be used as a good and economical adsorbent

An efficient missing tag identification approach in RFID collisions

Radio frequency identification technology has been widely used to verify the presence of items in many applications such as warehouse management and supply chain logistics. In these applications, the challenge of how to timely identify the missing tags (namely tag searching or missing tag identification) is a key focus. Existing missing tag identification solutions have not achieved their full potentials because collision slots have not been well explored. In this paper, we propose an approach named collision resolving based missing tag identification (CR-MTI) to break through the performance bottleneck of existing missing tag identification protocols. In CR-MTI, multiple tags are allowed to respond with different binary strings in a collision slot. Then, the reader can verify them together by using the bit tracking technology and particularly designed string, thereby significantly improve the time efficiency. CR-MTI also reduces the number of messages transmitted by the reader using customized coding. We further explore the optimal parameter settings to maximize the performance of our proposed CR-MTI. Extensive simulation results show that our proposed CR-MTI outperforms prior art in terms of time efficiency, total executive time and communication complexity

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

Smart Monitoring and Control in the Future Internet of Things

The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things

Fast RFID counting under unreliable radio channels.

Sze, Wai Kit.Thesis (M.Phil.)--Chinese University of Hong Kong, 2009.Includes bibliographical references (leaves 77-83).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.viChapter 1 --- Introduction --- p.1Chapter 2 --- Background and Related Work --- p.8Chapter 3 --- RFID Tag-set Cardinality estimation based on a Two-parameter implicit Channel Model --- p.13Chapter 3.1 --- System Model --- p.14Chapter 3.2 --- Number of Empty Slots Observed by the Reader --- p.16Chapter 3.3 --- Estimator Accuracy and Performance Analysis --- p.25Chapter 3.4 --- Results and Discussions --- p.32Chapter 3.5 --- Chapter Summary --- p.41Chapter 4 --- RFID Tag-set Cardinality estimation over Unknown Channel --- p.42Chapter 4.1 --- System Model --- p.43Chapter 4.2 --- Baseline: The Union-based approach --- p.45Chapter 4.2.1 --- Motivation --- p.46Chapter 4.2.2 --- Union Algorithm --- p.46Chapter 4.2.3 --- Analysis of the Union algorithm --- p.47Chapter 4.3 --- "Probabilistic Tag-counting over Lossy, Unknown channels via the Mh model" --- p.52Chapter 4.3.1 --- "Novel Interpretation of Mh for RFID Counting over Lossy, Unknown Channels" --- p.52Chapter 4.3.2 --- The Moment Estimator --- p.55Chapter 4.3.3 --- Sample Coverage Estimator --- p.57Chapter 4.3.4 --- Estimating the overall Tag population t --- p.59Chapter 4.4 --- Performance Validation and Comparison --- p.62Chapter 4.5 --- Chapter Summary --- p.65Chapter 5 --- Conclusions and Future Work --- p.73Chapter A --- Proof of Equation (3.6) in Chapter 3 --- p.75Bibliography --- p.7