Radio Frequency Identification (RFID) is considered one of the pioneering technologies of the Internet of Things (IoT). It allows to bind physical environments to information processing systems, adding new capabilities like automatic inventorying, location, or sensing with batteryless tags. Indeed, many data flows of physical objects can be tracked using this technology, and it is common to find heterogeneous traffics present in the same facility, each managed by different sets of readers. For example, in a grocery store, typically we have two kinds of readers: those carrying out a continuous inventory, whose goal is knowing the contents of the shelves as accurately as possible; and a set of checking-out readers at exit gates for the billing process that has to minimize the waiting time of customers. Another example of multiclass traffic is a hospital, where new families of sensing tags allow staff to wirelessly monitor patients-which obviously must be done as a priority-and coexist with other readers aimed at precisely knowing the location of equipment or drugs. Even with the same goal, there could be readers requiring different setups, for example in the hospital case, readers located at doors for inventorying purposes have a short time available to identify passing-by objects or people, and thus they have to work with a higher priority than regular readers performing inventorying tasks. In this work, we investigate a modification of the standard listen-before-talk (LBT) protocol for RFID networks which can support this kind of multipriority environment, by offering different qualities of service to each traffic. Results demonstrate that by tuning the protocol setup, it is possible to establish a trade-off between the performance of each traffic. This is shown for the two cited examples, the grocery shop and the hospital, using a simulation tool allowing us to implement a full-scale RFID model. In addition, we present a greedy mechanism for online reader setup. Instead of selecting offline a hard priority level, this greedy algorithm is able to adapt the priority to achieve the required quality-of-service (QoS) level.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219259 | PMC |
http://dx.doi.org/10.3390/s20082313 | DOI Listing |
Heliyon
December 2024
Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah, 52571, Saudi Arabia.
In this study, a multi-slotted antenna is designed and characterized that can be used for wearable applications by utilizing a flexible, durable silicone rubber substrate. Flexible material has become increasingly popular among researchers in recent years for the development of wearable antennas for body area networks (BAN). The flexible device should be small in size so that it can be easily worn on the human body by integrating with wearables for transmitting and receiving signals over a sufficiently long distance.
View Article and Find Full Text PDFSci Rep
November 2024
Networks and Communication Engineering Department, Al Ain University, 112612, Abu Dhabi, United Arab Emirates.
The development of contemporary electronic components, particularly antennas, places significant emphasis on miniaturization. This trend is driven by the emergence of technologies such as mobile communications, the internet of things, radio-frequency identification, and implantable devices. The need for small size is accompanied by heightened demands on electrical and field properties, posing a considerable challenge for antenna design.
View Article and Find Full Text PDFSensors (Basel)
October 2024
College of Engineering and Computer Science, Jazan University, Jazan 45142, Saudi Arabia.
Sensors (Basel)
July 2024
School of Computer Science, Civil Aviation Flight University of China, Guanghan 618307, China.
This study presents a novel approach to indoor positioning leveraging radio frequency identification (RFID) technology based on received signal strength indication (RSSI). The proposed methodology integrates Gaussian Kalman filtering for effective signal preprocessing and a time-distributed auto encoder-gated recurrent unit (TAE-GRU) model for precise location prediction. Addressing the prevalent challenges of low accuracy and extended localization times in current systems, the proposed method significantly enhances the preprocessing of RSSI data and effectively captures the temporal relationships inherent in the data.
View Article and Find Full Text PDFSensors (Basel)
July 2024
School of Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, Scotland, UK.
Safe drinking water is essential to a healthy lifestyle and has been recognised as a human right by numerous countries. However, the realisation of this right remains largely aspirational, particularly in impoverished nations that lack adequate resources for water quality testing. Kenya, a Sub-Saharan country, bears the brunt of this challenge.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!