229 research outputs found

    FRAMEWORK FOR IMPROVING PERFORMANCE OF PROTOCOLS FOR READING RADIO FREQUENCY IDENTIFICATION TAGS

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    Radio-frequency Identification (RFID) is a highly sought-after wireless technology used to track and manage inventory in the supply chain industry. It has varied applications ranging from automated toll collection and security access management to supply chain logistics. Miniaturization and low tag costs of RFID tags have lead to item-level tagging, where not just the pallet holding products is tagged but each product inside has a tag attached to it. Item-level tagging of goods improves the accuracy of the supply chain but it significantly increases the number of tags that an RFID reader must identify and track. Faster identification is crucial to cutting cost and improving efficiency. Existing RFID protocols were designed to primarily handle static scenarios with both RFID tags and readers not being in motion. This research addresses the problem of inventory tracking within a warehouse in multitude of scenarios that involves mobile tags, multiple readers and high density environments. Mobility models are presented and frameworks are developed for the following scenarios: a) mobile tags on a conveyor belt with multiple fixed readers; b) mobile reader in a warehouse with stationary tags in shelves; and c) high density tag population with Near-Field (NF) communication. The proposed frameworks use information sharing among readers to facilitate protocol state handoff and segregation of tags into virtual zones to improve tag reading rates in mobile tag and mobile reader scenarios respectively. Further, a tag’s ability to listen to its Near-Field neighboring tags transmissions is exploited to assist the reader in resolving collisions and hence enhancing throughput. The frameworks discussed in this research are mathematically modeled with a probabilistic analysis of protocols employed in conjunction with framework. With an increased number of tags to be identified, mathematically understanding the performance of the protocol in these large-scale RFID systems becomes essential. Typically, this analysis is performed using Markov-chain models. However, these analyses suffer from the common state-space explosion problem. Hence, it is essential to come up with a scalable analysis, whose computation model is insensitive to the number of tags. The following research analyzes the performance of tag identification protocols in highly dense tag scenarios, and proposes an empirical formula to estimate the approximate time required to read all the tags in a readers range without requiring protocol execution

    Intelligent Sensor Networks

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    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

    RFID in Supply Chains

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    A critical factor in increasing the widespread adoption of Radio Frequency Identification (RFID) technology for different supply chain applications is the ability to achieve a high level of read accuracy. The read accuracy is dependent on the size of the region that receives sufficient power from the reader. While most current research considers the powering region of a reader to be determined only by its read range, in reality read accuracy can be complicated by such issues as polarizations and the relative orientations of reader antennas and tags. In particular, when tag positions are not fixed, the specific placement of reader antennas and their interaction with the polarization and the orientation of the tags can have a significant effect on the success of the interrogation processes. This research uses Friis' equation for both the forward link and the backward link to explicitly consider orientations and polarizations while addressing the problem of optimizing the locations of a set of reader antennas at a scanning portal. The objective is to maximize the size of the powering region satisfying a particular read accuracy requirement. This research develops different methodologies and provides results for obtaining the best antenna locations to address different scenarios in supply chain applications. It addresses the case where items are static within a read portal, as well as when they might be moving on some type of material handling equipment. Various scenarios are considered for the tag orientations, including item-level applications where any orientation might be possible and case-level and pallet-level scenarios where the number of possible tag orientations might be limited

    Neighborhood Localization Method for Locating Construction Resources Based on RFID and BIM

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    Construction sites are changing every day, which brings some difficulties for different contractors to do their tasks properly. One of the key points for all entities who work on the same site is the location of resources including materials, tools, and equipment. Therefore, the lack of an integrated localization system leads to increase the time wasted on searching for resources. In this research, a localization method which does not need infrastructure is proposed to overcome this problem. Radio Frequency Identification (RFID) as a localization technology is integrated with Building Information Modeling (BIM) as a method of creating, sharing, exchanging and managing the building information throughout the lifecycle among all stakeholders. In the first stage, a requirements’ gathering and conceptual design are performed to add new entities, data types, and properties to the BIM, and relationships between RFID tags and building assets are identified. Secondly, it is proposed to distribute fixed tags with known positions as reference tags for the RFID localization approach. Then, a clustering method chooses the appropriate reference tags to provide them to an Artificial Neural Network (ANN) for further computations. Additionally, Virtual Reference Tags (VRTs) are added to the system to increase the resolution of localization while limiting the cost of the system deployment. Finally, different case studies and simulations are implemented and tested to explore the technical feasibility of the proposed approach

    Investigation into Swarm-based Cooperative Behaviour in Execution of Open Field Agricultural Tasks

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    Because of the significant drop in the number of farmers and increase in the earth population, the use of autonomous farming units including unmanned tractors is becoming more and more popular. However, relying on a single autonomous farming unit to carry out the entire task on a large field is inefficient. Using multiple autonomous tractors bring more efficiency, however, without cooperation this attempt will fail (Mataric et al., 1995). This cooperation can be achieved by an appropriate task allocation and coordination mechanism between the participating units. The current trend in this field is to use direct forms of communication in any form of directional or broadcasting meaningful messages among the group. The messages assist the group to identify the state of the task, assigned workload, collision and congestion avoidance, and etc. These forms of approaches are fast and efficient when units are within the communicating signal range. In this thesis, we aim to investigate the feasibility of cooperative execution of open field farming task including spraying and ploughing while inter-team interaction is other than direct communication methods. For every task, an algorithm is suggested and an appropriate mathematical model is presented. Then, using ROS Stage simulation environment, each algorithm is implemented and multiple tests are conducted. Finally, the simulation results and the correspondent mathematical results are compared and appropriate modifications are suggested

    RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

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    Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization
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