Controlling in-plant logistics by deploying RFID system in the item-level manufacturing : a case study

RFID systems are being used in the industries to follow the manufacturing environment by tagging objects where keeping track has a value. The recent research about RFID systems mainly focused on monitoring assets to control shop floor operations in real time. This case study has focused on deployment and improvement of an RFID system with a purpose of choose optimum system installation. The investigation of the production area, collecting item flow data and developing the relational database. The data that has been attained from the system can be used to control internal plant logistics and provide support in order to improve shop floor operations. This kind of RFID system used in industry can be very useful in order to increase the speed of production and regulate the work flow

The Application of RFID System in Water Level Monitoring

In tropical country like Malaysia water tank is very common in every buildings and houses. Water from tank will be used when there is a problem with the direct water supply. It is so important where at some government buildings the water level in the tank is being inspected daily to ensure the water level is above the required threshold. However this task consumes time and energy as the tank is located at the top of the building that cannot be easily accessible. Therefore there is need to implement automatic system that can monitor the level of the water in the tank. If the level is decreasing below the required threshold, the intended personnel will be informed immediately via a smartphone for example. The decrease could indicate a failure in the mechanical system to pump the water into the tank. Results from the experiments show that Radio Frequency Identification (RFID) technology has the potential to be used in monitoring the tank water level although there is drawback such implementation cost due to hardware requirements

An Approach for Removing Redundant Data from RFID Data Streams

Radio frequency identification (RFID) systems are emerging as the primary object identification mechanism, especially in supply chain management. However, RFID naturally generates a large amount of duplicate readings. Removing these duplicates from the RFID data stream is paramount as it does not contribute new information to the system and wastes system resources. Existing approaches to deal with this problem cannot fulfill the real time demands to process the massive RFID data stream. We propose a data filtering approach that efficiently detects and removes duplicate readings from RFID data streams. Experimental results show that the proposed approach offers a significant improvement as compared to the existing approaches

CROSS-DISCIPLINARY COLLABORATIONS IN DATA QUALITY RESEARCH

Data Quality has been the target of research and development for over four decades, and due to its cross-disciplinary nature has been approached by business analysts, solution architects, database experts and statisticians to name a few. As data quality increases in importance and complexity, there is a need to motivate the exploitation of synergies across diverse research communities in order to form holistic solutions that span across its organizational, architectural and computational aspects. As a first step towards bridging gaps between the various research communities, we undertook a comprehensive literature study of data quality research published in the last two decades. In this study we considered a broad range of Information System (IS) and Computer Science (CS) publication outlets. The main aims of the study were to understand the current landscape of data quality research, create better awareness of (lack of) synergies between various research communities, and, subsequently, direct attention towards holistic solutions. In this paper, we present a summary of the findings from the study that outline the overlaps and distinctions between the two communities from various points of view, including publication outlets, topics and themes of research, highly cited or influential contributors and strength and nature of co-authorship networks

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

Spatial and Temporal Analysis on the Distribution of Active Radio-Frequency Identification (RFID) Tracking Accuracy with the Kriging Method

Radio frequency identification (RFID) technology has already been applied in a number of areas to facilitate the tracking process. However, the insufficient tracking accuracy of RFID is one of the problems that impedes its wider application. Previous studies focus on examining the accuracy of discrete points RFID, thereby leaving the tracking accuracy of the areas between the observed points unpredictable. In this study, spatial and temporal analysis is applied to interpolate the continuous distribution of RFID tracking accuracy based on the Kriging method. An implementation trial has been conducted in the loading and docking area in front of a warehouse to validate this approach. The results show that the weak signal area can be easily identified by the approach developed in the study. The optimum distance between two RFID readers and the effect of the sudden removal of readers are also presented by analysing the spatial and temporal variation of RFID tracking accuracy. This study reveals the correlation between the testing time and the stability of RFID tracking accuracy. Experimental results show that the proposed approach can be used to assist the RFID system setup process to increase tracking accuracy

Outlier-Aware Data Aggregation in Sensor Networks

Abstract- In this paper we discuss a robust aggregation framework that can detect spurious measurements and refrain from incorporating them in the computed aggregate values. Our framework can consider different definitions of an outlier node, based on a specified minimum support. Our experimental evaluation demonstrates the benefits of our approach. I

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