A novel communication method for semi-passive RFID based sensors

This paper presents a novel communication method for semi-passive RFID based sensors. The new method uses a digitally reconfigurable UHF RFID tag antenna to modulate sensed information at an RFID tag on to the received signal strength indicator (RSSI) response perceived at an RFID reader. This technique is completely compatible with the existing class 1 generation 2 UHF air interface protocol thereby enabling the use of existing RFID reader infrastructure to decode the additional sensed information. The effect of read distance, environment and bit duration on the performance of the communication method is examined through measurements obtained from a prototype. Through experimental verification, it is demonstrated that error free transmission of sensor information can be achieved up to 3.5 meters in different environments with a bit duration of 500 ms. Prospective future research directions are also discussed

On a Pair of Diophantine Equations

For relatively prime natural numbers $a$ and $b$, we study the two equations $ax+by = (a-1)(b-1)/2$ and $ax+by+1= (a-1)(b-1)/2$, which arise from the study of cyclotomic polynomials. Previous work showed that exactly one equation has a nonnegative solution, and the solution is unique. Our first result gives criteria to determine which equation is used for a given pair $(a,b)$. We then use the criteria to study the sequence of equations used by the pair $(a_n/\gcd{(a_n, a_{n+1})}, a_{n+1}/\gcd{(a_n, a_{n+1})})$ from several special sequences $(a_n)_{n\geq 1}$. Finally, fixing $k \in \mathbb{N}$, we investigate the periodicity of the sequence of equations used by the pair $(k/\gcd{(k, n)}, n/\gcd{(k, n)})$ as $n$ increases.Comment: 21 pages, 2 figure

Data mining techniques to identify frauds in water bottle delivery and predict the future demand for sales trends

Data mining is a subset of databases management and it mainly applicable to large and complex databases to eliminate the randomness and discover the hidden pattern. Fraud detection in data mining is the process of identifying fraudulent acts by analyzing the dataset. Research is based on identifying fraudulent acts of water bottle delivery process. The research study focusses on to manage the invoicing process with the water delivery process. Due inefficacies in the water delivering process bottle lost cost in the last six months is Rs 213,070.00 approx. Through detecting fraudulent acts, the institutes can save resources and cost [3], for this study a sample data set has been used to identify how the fraudulent activities are occurring. Sample dataset has been selected from where data entry person had found physical evidence that the bottle had been sold for outsiders. Data mining tools which used to detect frauds are Naïve Bayes, Decision Trees, and neural networks. By developing predictive models can be generated to estimate things such as the probability of fraudulent behavior. ROC curves have deployed for model assessment to provide a more intuitive analysis of the models and confusion matrix is has used to describe the performance of a classification model on the test data for which the true values are known

Development of an under frequency load shedding algorithm

In overload conditions caused by sudden outages in a Generator or a Transmission line in a Power System, loads have to be shed at selected feeders in the distribution system, to maintain system stability, namely frequency.// Different load shedding schemes can result in quite different performance, in recovery of system frequency.// In this research project, initially the existing load shedding scheme employed in the Sri Lankan Power System was studied. Improvements to the existing scheme using the rate of change of frequency (df/dt),is proposed.// A typical network was modelled using MATLAB/Simulink software package and a Load Shedding Scheme was simulated with this model. Improved performance was observed when the combination of Frequency (f) and Rate of change of Frequency (df/dt)were employed in the Load Shedding Schem

Signal processing methods for chipless RFID

Radio frequency identification (RFID) is a technology that automates routine procedures of data extraction, identification, tracking and surveillance in applications such as inventory control and logistics. The unit cost of conventional RFID tags is too high for them to be used in large item level tagging applications. This is because of the expensive electronic integrated circuits (ICs) used in the tags. As a solution to further reduce the cost of RFID tags, chipless RFID tags have been developed. A chipless RFID tag does not require an IC for its operation. Current research on chipless RFID technology has been focused on, the development of tag designs with enhanced data capacity, the development of tags with sensing capabilities, and the development of RFID reader architectures and signal processing algorithms. Despite current research efforts, further work is required in the area of signal processing for chipless RFID. For this purpose, three novel signal processing methods are introduced in this thesis, (i) development of a robust multidimensional detection algorithm for detecting data bits encoded in a chipless RFID tag, (ii) time and frequency domain analysis of backscattered tag signals for the removal of interference, and (iii) a new systematic calibration procedure for single antenna RFID readers. These methods enhance the performance of chipless RFID systems in terms of the data bit detection and reading range. Existing algorithms used for detecting data bits encoded in a frequency signature of a chipless RFID tag use a one dimensional approach to detection. The one dimensional approach to detection does not consider all the characteristics of the spectral features that encode data bits in a frequency signature. Therefore, the detection performance achieved is suboptimal. In order to enhance the detection performance, a new multidimensional detection method is introduced. The new method utilizes a set of orthonormal basis functions to fully describe the characteristics of a frequency signature. Using these orthonormal basis functions a frequency signature is represented as a signal point in a multidimensional signal space. The detection of data bits contained in an unknown frequency signature is performed using minimum distance detection. It is shown that the performance achieved by the new method exceeds the performance of existing one dimensional threshold based detection of tag data bits. The second method proposed in the thesis focuses on improving the reading range of an RFID reader beyond proximity based reading. For this purpose, the total received signal at an RFID reader is analysed in the time domain as well as the frequency domain to identify the essential signal component that contains the tag data. It is shown that the useful data is contained in the antenna mode of the backscattered tag response. The antenna mode backscatter is separated from the rest of the received signal using a time window. The separated antenna mode is then analysed in the frequency domain to estimate the tag’s frequency signature. Through this time and frequency domain analysis, non-proximity based reading is achieved. It is shown that the tag can be read in non-proximity reading conditions using simulation results and measurements taken in an anechoic chamber environment. The final method introduced in the thesis is a systematic calibration procedure for single antenna based chipless RFID readers. The calibration procedure takes into account practical conditions prevailing in a real world application environment. The calibration allows the RFID reader to accurately estimate the frequency signature of a chipless RFID tag in a cluttered environment. It also addresses the limitations of existing calibration methods used for chipless RFID systems such as the need for repeated calibration and antenna alignment

Signal processing methods for chipless RFID

Radio frequency identification (RFID) is a technology that automates routine procedures of data extraction, identification, tracking and surveillance in applications such as inventory control and logistics. The unit cost of conventional RFID tags is too high for them to be used in large item level tagging applications. This is because of the expensive electronic integrated circuits (ICs) used in the tags. As a solution to further reduce the cost of RFID tags, chipless RFID tags have been developed. A chipless RFID tag does not require an IC for its operation. Current research on chipless RFID technology has been focused on, the development of tag designs with enhanced data capacity, the development of tags with sensing capabilities, and the development of RFID reader architectures and signal processing algorithms. Despite current research efforts, further work is required in the area of signal processing for chipless RFID. For this purpose, three novel signal processing methods are introduced in this thesis, (i) development of a robust multidimensional detection algorithm for detecting data bits encoded in a chipless RFID tag, (ii) time and frequency domain analysis of backscattered tag signals for the removal of interference, and (iii) a new systematic calibration procedure for single antenna RFID readers. These methods enhance the performance of chipless RFID systems in terms of the data bit detection and reading range. Existing algorithms used for detecting data bits encoded in a frequency signature of a chipless RFID tag use a one dimensional approach to detection. The one dimensional approach to detection does not consider all the characteristics of the spectral features that encode data bits in a frequency signature. Therefore, the detection performance achieved is suboptimal. In order to enhance the detection performance, a new multidimensional detection method is introduced. The new method utilizes a set of orthonormal basis functions to fully describe the characteristics of a frequency signature. Using these orthonormal basis functions a frequency signature is represented as a signal point in a multidimensional signal space. The detection of data bits contained in an unknown frequency signature is performed using minimum distance detection. It is shown that the performance achieved by the new method exceeds the performance of existing one dimensional threshold based detection of tag data bits. The second method proposed in the thesis focuses on improving the reading range of an RFID reader beyond proximity based reading. For this purpose, the total received signal at an RFID reader is analysed in the time domain as well as the frequency domain to identify the essential signal component that contains the tag data. It is shown that the useful data is contained in the antenna mode of the backscattered tag response. The antenna mode backscatter is separated from the rest of the received signal using a time window. The separated antenna mode is then analysed in the frequency domain to estimate the tag’s frequency signature. Through this time and frequency domain analysis, non-proximity based reading is achieved. It is shown that the tag can be read in non-proximity reading conditions using simulation results and measurements taken in an anechoic chamber environment. The final method introduced in the thesis is a systematic calibration procedure for single antenna based chipless RFID readers. The calibration procedure takes into account practical conditions prevailing in a real world application environment. The calibration allows the RFID reader to accurately estimate the frequency signature of a chipless RFID tag in a cluttered environment. It also addresses the limitations of existing calibration methods used for chipless RFID systems such as the need for repeated calibration and antenna alignment

Investigation on neutralizing agents for palm oil mill effluent (POME)

Proper treatment of palm oil mill effluent (POME) is necessary to sustain the progress of palm oil industry in Sri Lanka. A case study was conducted to improve existing wastewater treatment system in a palm oil factory located in Galle district. The system consists of a neutralization tank, anaerobic ponds followed by anaerobic biogas digesters. Lime has been used to neutralize before sending to ponds for biological treatment. However, this treatment did not bring optimum pH for microbial action in anaerobic ponds. Therefore, performance of lime, caustic soda, iron lathe shavings and boiler ash from the same factory were studied for pH adjustment. A lab scale leaching bed with boiler ash was tested as it is freely available. Total carbon and total nitrogen in effluent were also measured. It was found that the Ca(OH)2 availability in commercially available lime was 31% and less effective. The effective dosage of caustic soda to obtain neutral pH was 5 kg/m3 thus lead to high cost. Iron lathe shavings and boiler ash of palm oil mill were effective and economically feasible in balancing pH. The boiler ash has shown significant effect in pH neutralization with the rate of 60 g/l with 4 days hydraulic retention time. Leaching bed with an ash layer shows an acceptable performance