Sensing Platform and Object Motion Detection Based on Passive UHF RFID Tags Using a Hidden Markov Model-based Classifier PDF Download

Author: Young Ho Lee
Publisher:
ISBN:
Category : Detectors
Languages : en
Pages : 90

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Book Description
For context-aware systems in indoor work settings, several types of sensors have been applied to capture work activities. We introduce and present a sensing platform and object motion detection system using a hidden Markov Classifier based on a UHF RFID system. Backscattered signal strength of passive UHF RFID tags as a sensor is used for providing information on the movement and identity of work objects. As the read range of passive UHF RFID broadens up to 12 meters compared to 1-meter range of HF RFID, passive tags have been used for many applications such as tracking medical devices and objects of daily living. The RF communication link between the reader antenna and tags for indoors exhibits intermittent loss of signal reception due to antenna orientation mismatch and breakpoints within the antenna coverage area. We propose a design of a sensing platform for tracking objects using a UHF RFID system with passive tags that provides continuous signal reception over the coverage area. We first investigated causes of power loss for passive tags and then designed a sensing platform solution using antenna diversity. The causes of tag's power loss were eliminated with angle and spatial diversity methods that can cover an arbitrary area of interest. We implemented this design in an indoor setting of a trauma resuscitation room and evaluated it by experimental measurement of signal strength at different points and angles in the area of interest. Our sensing platform supported complete coverage and uninterrupted interrogation of tags as they moved in the area of interest. We conclude that this sensing platform will be suitable for uninterrupted object tracking with UHF RFID technology in generic indoor spaces. In addition to the sensing platform, we design an object motion detection system using passive UHF RFID tags attached on medical objects. To use the signal strength for accurate detection of object movement we propose a novel hidden Markov model with continuous observations, RSSI preprocessor, frame-based data segmentation, and motion-transition finder. We use the change in backscattered signal strength caused by tag's relocation to reliably detect movement of tagged objects. To maximize the accuracy of movement detection, an HMM-based classifier is designed and trained with dynamic settings, and different object types. We deployed an RFID system in a hospital trauma bay and evaluated our approach with data recorded in the trauma room during 28 simulated resuscitations performed by trauma teams. Our motion detection system shows 89.5% accuracy in this domain.

Author: Jinsong Han
Publisher: Springer
ISBN: 3319126466
Category : Computers
Languages : en
Pages : 66

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Book Description
This SpringerBrief examines the use of cheap commercial passive RFID tags to achieve accurate device-free object-tracking. It presents a sensitive detector, named Twins, which uses a pair of adjacent passive tags to detect uncooperative targets (such as intruders). Twins leverages a newly observed phenomenon called critical state that is caused by interference among passive tags. The author expands on the previous object tracking methods, which are mostly device-based, and reveals a new interference model and their extensive experiments for validation. A prototype implementation of the Twins-based intrusion detection scheme with commercial off-the-shelf reader and tags is also covered in this SpringerBrief. Device-Free Object Tracking Using Passive Tags is designed for researchers and professionals interested in smart sensing, localization, RFID and Internet of Things applications. The content is also useful for advanced-level students studying electrical engineering and computer science.

Author: Rahul Bhattacharyya
Publisher:
ISBN:
Category :
Languages : en
Pages : 170

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Book Description
In the future, large-scale sensor deployment would enable many areas such as infrastructure condition monitoring and supply chain management. However, many of today's wireless sensor technologies are still too expensive to meet this need. Radio Frequency IDentification (RFID) offers good potential for the development of pervasive sensors: RFID tags have a proven track record of large-scale, highly integrated deployment for object identification in the retail and consumer goods industry. Furthermore, the last decade has seen much progress in making RFID a reliable, standardized wireless communication medium with the ability to mass produce low-cost RFID tags. My thesis introduces the concept of RFID Tag Antenna-Based Sensing (RFID TABS). In this approach, a change in the sensed parameter of interest induces a controlled change in the geometry or boundary conditions of an RFID tag's antenna. The resultant change in the tag's response signal can then be detected by an RFID reader. My approach builds upon current developments in RFID technology. For instance, the manufacturing techniques for the mass production of low-cost RFID tags can be used for pervasive tag-sensor development. My thesis examines TABS in a two-pronged approach: First, I demonstrate how three fundamental tag and reader signal properties can be used for sensing and propose three classes of TABS: -- Amplitude Modifying (AM) TABS use RFID reader transmitted power and tag response power for sensing. I illustrate proof of concept using a displacement sensor. I demonstrate that both these power metrics can be used to reliably measure structural displacement to a precision of 2.5 mm using commercial RFID tags. -- Frequency Modifying (FM) TABS relate changes in the sensed parameter to a shift in the tag's optimal operating frequency - the carrier frequency for which the tag is best tuned to respond to the reader. I demonstrate proof of concept using a temperature threshold sensor - the crossing of a design temperature threshold results in a shift in the sensor's optimal operating frequency. I demonstrate that the sensor works reliably over a 3 m read range and in different environmental conditions. -- Phase Modifying (PM) TABS use tag backscatter phase for sensing. I provide a brief summary of the factors influencing RF phase and outline the design for a PM TABS fluid level sensor that uses RFID tag response phase to detect the presence or absence of fluid in a beverage glass. I highlight the challenges in the practical implementation of this approach by demonstrating the sensitivity of RFID tag phase to three extraneous factors. Second, I introduce the concept of Non-Electric Memory to record short timescale threshold crossovers in the sensed parameter that may occur when the tag-sensor is unpowered. When information about, rather than the exact time of, the threshold occurrence is sufficient, non-electric memory provides a solution. I demonstrate how non-electric memory can be integrated into sensor design at minimal added cost. In the proof of concept of a temperature threshold sensor, I design a thermally actuated shape memory polymer switch to permanently change the electrical properties of an RFID tag when the temperature threshold is crossed. I demonstrate that the design works reliably over a read range of 3 m and is independent of the material on which the sensor is deployed. In summary, this thesis demonstrates how an RFID tag can be adapted for low cost, pervasive sensing. Sensor prototypes illustrate proof of concept in three application areas. Extensions to two other applications are also discussed.

Author: Tzu Hao Li
Publisher:
ISBN:
Category : Radio frequency identification systems
Languages : en
Pages :

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Book Description
Radio frequency identi cation (RFID) is a rapidly emerging technology that enables au- tomatic remote identi cation of objects. Passive and semi-passive RFID systems can be distinguished from other forms of wireless systems, because the RFID tags (transponders) communicate by way of backscatter. In addition, passive tags derive their energy from the RF energy emitted by the reader. RFID technology can provide a fully automated data capture and analysis system. Compared to a passive RFID system, an open platform semi-passive UHF RFID tag can provide identi cation, security, low-power (compared to a wireless sensor net- work(WSN)), medium range and medium processing speed. However, the eld of semi- passive RFID is still under development, and has yet there are no open development platforms available. This thesis develops a prototype of a semi-passive UHF RFID tag that is compatible with the leading UHF RFID standard EPCglobal Gen 2 Class 1. I alsot has the exible I2C and analog digital converter(ADC) interface, which allows the additional of external analog and digital sensors. The sensor data can be read by microcontroller and stored at memory. Standard reader can get sensor data by sending QUERY and READ command to tag. Test results of our open platform semi-passive UHF RFID tag demonstrated that it can achieve a read rate above 50% when an open platform semi-passive UHF RFID tag is placed four meters from the reader antenna and the reader output power is set to 21 dBm. In addition, the proposed semi-passive open platform RFID tag consumes very little power (4.9 mA in 2V with system frequency set to 8MHz).

Author: Emran Md Amin
Publisher:
ISBN:
Category :
Languages : en
Pages : 450

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Book Description
In recent years, radio frequency identification (RFID) technology has been employed in mainstream applications for asset management, storage of goods, security, transportation and logistics. The RFID sensor has features which can revolutionize the field of automated object identification in conjunction with condition monitoring. In this research, a novel chipless RFID sensor platform is proposed for wireless sensing of tagged objects. Since the proposed chipless RFID sensor does not require any on-board micro-chip and power source, it has great potential for low-cost, maintenance-free, automated and robust applications. The aim of this research is to develop single node multi-parameter sensing chipless RFID sensors in versatile RF sensing applications. This PhD thesis involves developing novel multi-resonator chipless RFID sensor platforms for three potential RF sensing applications: (i) non-invasive radiometric partial discharge (PD) detection and localization of faulty power apparatus, (ii) electromagnetic (EM) sensors for real time environment monitoring, and finally, (iii) RF memory sensors for event detection. Each development involves the problem identification, research hypothesis, physical layer design of the sensor tag, prototype fabrication and experimentation. Finally, a chipless RFID sensor for multiple parameter sensing is proposed for both real-time environment monitoring and event detection. In the first phase of this research, a passive radio frequency (RF) sensor has been developed for non-invasive radiometric detection of simultaneous PD signals in high voltage (HV) apparatus such as transformers, overhead lines, capacitor banks and circuit breakers. The sensor comprises passive multi-resonator circuit and an antenna for capturing PD as well as providing ID of faulty equipment. The low-cost RF sensor is installed in individual HV apparatus for monitoring their PD events. The chipless RFID based PD sensor addresses PD monitoring, PD detection and faulty source identification.In the second phase, a low-cost, printable chipless RFID tag sensor is developed for real-time environment monitoring. The chipless RFID tag sensor provides identification data and monitors a number of physical parameters of tagged objects and the surrounding environment. The RF sensor measures physical parameters such as temperature, humidity, light intensity and pH level of tagged objects. The RFID sensor is based on planar, single-sided resonant scatterers for generating data ID and carrying sensing information in the frequency spectrum. Environment sensing is incorporated using smart polymer materials, which exhibit dielectric change to particular physical parameters. Our proposed chipless RFID sensor comprises a planar multi-slot resonator as an ID generation circuit and an electric field coupled LC (ELC) resonator coated with a smart material layer as a sensing circuit on a compact planar layout. A novel feature of the developed sensor is its ability to combine multiple physical parameter sensing in the same chipless RFID platform for ubiquitous condition monitoring. In this research firstly, a humidity sensor is proposed, as it is one of the most critical physical parameters for environment monitoring. Next, a chipless RFID memory sensor is developed for violation of temperature threshold. The memory sensor uses a smart material which exhibit permanent dielectric change when certain temperature threshold is reached. The sensor operates as a memory device to store occurrence of a particular event. The temperature threshold sensor can also incorporate real time humidity sensing within the same chipless RFID tag platform. Hence a chipless RFID sensor for multiple parameters sensing capability is developed.Reading of chipless RFID sensor is a non-trivial task. A chipless RFID sensor tag is a minute radar target for the reader. New reader architecture to read the tag is proposed in this thesis. The reader comprises RF, digital and power control modules to interrogate the tag sensor, captures backscattered RF response and performs necessary signal processing for data decoding.Finally, the thesis summarizes the major challenges in realizing a fully-printable chipless sensor on flexible substrates. Potential future research directions in sensor fabrication, chipless RFID reader development, and sensor calibration methods are discussed. With its simultaneous identification and sensing capabilities, the low cost fully printable chipless RFID sensor will revolutionise emerging fields such as internet of thing (IoT) and smart cities.

Author: Alanson Sample
Publisher:
ISBN:
Category : Technology
Languages : en
Pages :

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Book Description
Development of Sensing and Computing Enhanced Passive RFID Tags Using the Wireless Identification and Sensing Platform.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Jerry Jolly Mannil
Publisher:
ISBN:
Category : Sensor networks
Languages : en
Pages : 162

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Book Description
We describe a body sensor system that detects human activities in real-time. The system consists of wearable computers known as sensor nodes (motes) that can sense information, process them and transmit the results to a Personal Device like Smart phone, PDA or Personal Computer. The motes are attached to different parts of the human body, namely waist and right thigh. To conserve power on the sensor motes, we send labels rather than the actual sensor data. The labels are a small set of alphabets that can completely represent the sensor data are generated by running Gaussian Mixture Model (GMM) clustering algorithm. The labels sent by the motes are analyzed by a HMM classifier to detect various actions performed by the subject. We will describe how various signal processing and statistical algorithms were adapted to run efficiently on the motes as well as on the PC, with minimal loss of precision. Motes lack floating point operations, therefore, signal processing techniques with floating point precision need to be adapted to execute with fixed-point operations. We also report the overall performance of the system in terms processing time for various modules and the action recognition accuracy. The thesis also explores mechanism to improve the robustness of the system by rejecting uninteresting movements.

Author: Angel Servent Abad
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Book Description
In this project we use the idea of RFID (Radio Frequency Identification), which is storage and information recuperation method. This method use devices called tags RFID for the identification. This RFID tags incorporate antennas to let to receive and to respond radiofrequency requests from a RFID transmitter-receiver. The fundamental purpose of the RFID technology is to transmit the identity of an object by means of radio waves. Essentially what we want to do is an antenna based sensing, which means use the antennas properties like a sensor. The proposal is a technique for using the changes in the response of the 2.4 GHz antenna as a sensing mechanism. We use the Wireless Identification and Sensing Platform (WISP), which is a computational sensing and programmable platform without battery designed to investigate in improving sensor RFID applications. WISP can operate using power transmitted from a (UHF) RFID reader located at long range and also communicate data in a single response packet. The objective of this project lies in analyzing the performance of a microwave antenna acting as occupancy sensor. How to determine when an object is positioned above the antenna has many applications in our society. One of the utilities is the detection of parking spaces available in the street, but there are so many others. To achieve these goals we first will make some voltage measurements of what is capture by the antenna by placing an envelope detector after it and then we will simulate its behavior with ADS and HFSS simulation. We will also use the MSP430 microchip to read the DC voltage after the antenna and finally we will create an application with the Microsoft Visual Studio to plot the results graphically and finally we draw our conclusions. Analyzing the results we can say that we have reached satisfactory conclusions.

Author: Ramprabhu Jayaraman
Publisher:
ISBN:
Category : Radio frequency identification systems
Languages : en
Pages : 70

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Book Description
Passive radio frequency identification (RFID) systems are revolutionizing the indoor positioning and tracking applications. There has been substantial research on practical applications of this technology and hospitals especially trauma care units are one such area where this capability can lead to improved workflow. Our system uses the Alien RFID reader and the "Squiggle" passive RFID tags to create an effective solution for tracking various medical items. Based on the Received Signal Strength Indication (RSSI) value of the tags, we developed a localization algorithm which uses a neural network estimator to estimate the distances of the tags. To reduce the effect of noise in the RSSI values received from the reader, we accumulate data over a period of time, remove the outliers and the average the remaining RSSI values. The RSSI based estimation algorithm provides very accurate estimation when the spatial density of tags is low (about 25 tags per square meter). To improve the localization accuracy at higher spatial densities we augmented the RSSI method of estimating distances by using the number of times the tags were read or the "read-count'. We also investigated how different types of occluding materials affect the localization accuracy. Metal and Humans also can cause complete occlusion when the positioned in direct line of sight between the antenna and the tag. To overcome human based occlusion, we placed an additional ceiling mounted antenna per 10 m2. This intervention makes possible the detection (but not localization) of tags when the vertical field of view is not occluded. We also studied the effect of the material to which the tags are attached and determined the effects on localization accuracy. The software system developed using Java is designed in a modular fashion and provides interfaces to tools like Matlab so that it is easy to experiment to various other localization algorithms. We also developed an intuitive User Interface to display the locations of tags and the associated items. Once a tag is identified its associated description can be looked up in a computer database and this also can be displayed in the user interface.