Energy Efficient In-network RFID Data Filtering Scheme in Wireless Sensor Networks

RFID (Radio frequency identification) and wireless sensor networks are backbone technologies for pervasive environments. In integration of RFID and WSN, RFID data uses WSN protocols for multi-hop communications. Energy is a critical issue in WSNs; however, RFID data contains a lot of duplication. These duplications can be eliminated at the base station, but unnecessary transmissions of duplicate data within the network still occurs, which consumes nodes’ energy and affects network lifetime. In this paper, we propose an in-network RFID data filtering scheme that efficiently eliminates the duplicate data. For this we use a clustering mechanism where cluster heads eliminate duplicate data and forward filtered data towards the base station. Simulation results prove that our approach saves considerable amounts of energy in terms of communication and computational cost, compared to existing filtering schemes

An approach to filtering RFID data streams

RFID is gaining significant thrust as the preferred choice of automatic identification and data collection system. However, there are various data processing and management problems such as missed readings and duplicate readings which hinder wide scale adoption of RFID systems. To this end we propose an approach that filters the captured data including both noise removal and duplicate elimination. Experimental results demonstrate that the proposed approach improves missed data restoration process when compared with the existing method.<br /

IGAA: An Efficient Optimization Technique for RFID Network Topology Design in Internet of Things

[[abstract]]Most RFID applications in the Internet of Things (IoTs) use multiple readers to read the IDs of multiple tags and form the RFID network. In such a network, unguarded reader deployment may generate over-crowded readers, cause interferences and, as a result, increases the deployment cost while degrading tag detection. Seeing that desirable reader deployment is crucial for RFID system performance, this paper introduces an optimization-based IGAA approach which outperforms existing RFID topology designs by turning up more favorable reader deployment and system performance. The new approach employs an advanced multi-objective fitness function and improved genetic annealing algorithms (GAA) to pursue a better RFID topology design. By involving an improved gene-stirring operation to help preserve good genes and locate optimal solutions for reader deployment, it is simple in operation but effective in practice. Experimental evaluation shows that when compared with related approaches, IGAA can yield better solution quality with less search time.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

The level of Marzano higher-order thinking skills among polytechnic students

This study aims to identify polytechnic students' level of Marzano Higher-Order Thinking Skills (HOTS) based on two dimensions, 'Extension and Refinement of Knowledge' and 'Meaningful Use of Knowledge,' and to analyze the difference in the students' level of Marzano HOTS based on these two dimensions depending on the students' demographic factors. This study design was a survey using quantitative methods. A total of 313 students were randomly selected as the survey sample. A questionnaire in the form of closed-ended questions was used as the research instrument. Data were analyzed using frequency percentage and MANOVA test. The findings showed no significant differences in the eight HOTS in the dimension of 'Extension and Refinement of Knowledge' with the gender and socio-economic status (SES) factors. However, there were significant differences in the eight HOTS with the academic achievement factor. Meanwhile, based on the dimension of 'Meaningful Use of Knowledge,' the findings showed no significant differences in the five HOTS in this dimension with the gender and academic achievement factors. The paper includes implications of the Higher-Order Thinking Skills (HOTS) for students to improve their academic performance. In future research, the authors can further identify university students' HOTS levels in the technical area

Strength, water absorption and thermal comfort of mortar bricks containing crushed ceramic waste

This present study investigated the crushed ceramic waste utilisation as sand replacement in solid mortar bricks. The percentage of crushed ceramic waste used were 0% (CW0), 10% (CW10), 20% (CW20) and 30% (CW30) from the total weight of sand. The dimension prescribed of mortar bricks are 215 mm x 102.5 mm x 65 mm as followed accordance to MS 2281:2010 and BS EN 771-1:2011+A1:2015. Four (4) tests were conducted on mortar bricks namely crushing strength, water absorption, compressive strength of masonry units and thermal comfort. The incorporation of ceramic waste in all designated mortar bricks showed the increment of crushing strength between 23% and 46% at 28 days of curing and decrement water absorption between 34% and 44% was recorded corresponding to control mortar bricks. The prism test of masonry units consists of mortar bricks containing ceramic waste indicated the high increment of compressive strength at about 200% as compared to mortar brick without ceramic waste. The thermal comfort test of ceramic mortar bricks were also showed the good insulation with low interior temperature. Therefore, the ceramic waste can be utilised as a material replacement to fine aggregate in mortar brick productions due to significant outcomes performed

Enchancing RFID data quality and reliability using approximate filtering techniques

Radio Frequency Identification (RFID) is an emerging auto-identification technology that uses radio waves to identify and track physical objects without the line of sight. While delivering significant improvements in various aspects, such as, stock management and inventory accuracy, there are serious data management issues that affect RFID data quality in preparing reliable solutions. The raw read rate in real world RFID deployments is often in the 60-70% range and naturally unreliable because of redundant and false readings. The redundant readings result in unnecessary storage and affect the efficiency of data processing. Furthermore, false readings that focused on false positive readings generated by cloned tag could be mistakenly considered as valid and affects the final results and decisions. Therefore, two approaches to enhance the RFID data quality and reliability were proposed. A redundant reading filtering approach based on modified Bloom Filter is presented as the existing Bloom Filter based approaches are quite intricate. Meanwhile, even though tag cloning has been identified as one of the serious RFID security issue, it only received little attention in the literature. Therefore we developed a lightweight anti-cloning approach based on modified Count- Min sketch vector and tag reading frequency from e-pedigree in observing identical Electronic Product Code (EPC) of the low cost tag in local site and distributed region in supply chain. Experimental results showed, that the first proposed approach, Duplicate Filtering Hash (DFH) achieved the lowest false positive rate of 0.06% and the highest true positive rate of 89.94% as compared to other baseline approaches. DFH is 71.1% faster than d-Left Time Bloom Filter (DLTBF) while reducing amount of hashing and achieved 100% true negative rate. The second proposed approach, Managing Counterfeit Hash (MCH) performs fastest and 25.7% faster than baseline protocol (BASE) and achieved 99% detection accuracy while DeClone 64% and BASE 77%. Thus, this study successfully proposed approaches that can enhance the RFID data quality and reliability

Robust modeling and planning of radio-frequency identification network in logistics under uncertainties

To realize higher coverage rate, lower reading interference, and cost efficiency of radio-frequency identification networkin logistics under uncertainties, a novel robust radio-frequency identification network planning model is built and arobust particle swarm optimization is proposed. In radio-frequency identification network planning model, coverage isestablished by referring the probabilistic sensing model of sensor with uncertain sensing range; reading interference iscalculated by concentric map–based Monte Carlo method; cost efficiency is described with the quantity of readers. Inrobust particle swarm optimization, a sampling method, the sampling size of which varies with iterations, is put forwardto improve the robustness of robust particle swarm optimization within limited sampling size. In particular, the exploita-tion speed in the prophase of robust particle swarm optimization is quickened by smaller expected sampling size; theexploitation precision in the anaphase of robust particle swarm optimization is ensured by larger expected sampling size.Simulation results show that, compared with the other three methods, the planning solution obtained by this work ismore conducive to enhance the coverage rate and reduce interference and cost.info:eu-repo/semantics/publishedVersio