Flexible, Fully Printable, and Inexpensive Paper-Based Chipless Arabic Alphabet-Based RFID Tags

This work presents the design and analysis of newly developed reconfigurable, flexible, inexpensive, optically-controlled, and fully printable chipless Arabic alphabet-based radio frequency identification (RFID) tags. The etching of the metallic copper tag strip is performed on a flexible simple thin paper substrate (ϵr = 2.31) backed by a metallic ground plane. The analysis of investigated tags is performed in CST MWS in the frequency range of 1–12 GHz for the determination of the unique signature resonance characteristics of each tag in terms of its back-scattered horizontal and vertical mono-static radar cross section (RCS). The analysis reflects that each tag has its own unique electromagnetic signature (EMS) due to the changing current distribution of metallic resonator. This EMS of each tag could be used for the robust detection and recognition of all realized 28 Arabic alphabet tags. The study also discusses, for the first time, the effect of the change in font type and size of realized tags on their EMS. The robustness and reliability of the obtained EMS of letter tags is confirmed by comparing the RCS results for selective letter tags using FDTD and MoM numerical methods, which shows very good agreement. The proposed tags could be used for smart internet of things (IoT) and product marketing applications.

ERP Systems Enhanced with RFID Technology in Furniture Industry

RFID technology is being widely used in most areas that are supported by ERP systems. With the help of RFID tags and readers placed at various locations throughout a furniture company, the presence of various objects in the factory can be monitored in real time. Readers receiving information from RFID tags can transmit it directly into the system and create databases or initiate business processes. The basic resources that can be tracked using RFID are human and machine resources as well as warehoused inventories, spare parts, tools, semi-finished and finished products. The only condition that must be met by the tracked object is that it can be tagged. The furniture industry is continuously growing. With factories expanding to tens of thousands of square metres and employing thousands of workers, knowledge of who or what is where at any given time is very important for optimising plant operations. Being able to gain this knowledge in real time is very useful and saves a lot of resources over the long term. Monitoring of resources in an ERP system using RFID technology is very popular nowadays. The improvement of the implemented solution leads to an ever increasing degree of control. However, it is important to maintain it at an optimal level, because otherwise it may unnecessarily disturb employees in their daily duties or generate more work for them without returning a measurable benefit.

The Relationship between Drone Speed and the Number of Flights in RFID Tag Reading for Plant Inventory

Accurate inventory allows for more precise forecasting, including profit projections, easier monitoring, shorter outages, and fewer delivery interruptions. Moreover, the long hours of physical labor involved over such a broad area and the effect of inefficiencies could lead to less accurate inventory. Unreliable data and predictions, unannounced stoppages in operations, production delays and delivery, and a considerable loss of profit can all arise from inaccurate inventory. This paper extends our previous work with drones and RFID by evaluating: the number of flights needed to read all tags deployed in the field, the number of scans per pass, and the optimum drone speed for reading tags. The drone flight plan was divided into eight passes from southwest to northwest and back at a horizontal speed of 2.2, 1.7, and 1.1 m per second (m/s) at a vertically fixed altitude. The results showed that speed did not affect the number of new tags scanned (p-value > 0.05). Results showed that 90% of the tags were scanned in less than four trips (eight passes) at 1.7 m/s. Based on these results, the system can be used for large-scale nursery inventory and other industries that use RFID tags in outdoor environments. We presented two novel measurements on evaluating RFID reader efficiency by measuring how fast the reader can read and the shortest distance traveled by the RFID reader over tag.

A MIMO Radar Signal Processing Algorithm for Identifying Chipless RFID Tags

In this paper, the multiple-input, multiple-output (MIMO) radar signal processing algorithm is efficiently employed as an anticollision methodology for the identification of multiple chipless radio-frequency identification (RFID) tags. Tag-identifying methods for conventional chipped RFID tags rely mostly on the processing capabilities of application-specific integrated circuits (ASICs). In cases where more than one chipless tag exists in the same area, traditional methods are not sufficient to successfully read and distinguish the IDs, while the direction of each chipless tag can be obtained by applying MIMO technology to the backscattering signal. In order to read the IDs of the tags, beamforming is used to change the main beam direction of the antenna array and to receive the tag backscattered signal. On this basis, the RCS of the tags can be retrieved, and associated IDs can be identified. In the simulation, two tags with different IDs were placed away from each other. The IDs of the tags were successfully identified using the presented algorithm. The simulation result shows that tags with a distance of 0.88 m in azimuth can be read by a MIMO reader with eight antennas from 3 m away.

Foraging dive frequency predicts body mass gain in the Adélie penguin

Quantifying food intake in wild animals is crucial to many ecological and evolutionary questions, yet it can be very challenging, especially in the marine environment. Because foraging behavior can be inferred from dive recordings in many marine creatures, we hypothesized that specific behavioral dive variables can indicate food intake. To test this hypothesis, we attached time-depth recorders to breeding Adélie penguins also implanted with RFID tags that crossed a weighbridge as they traveled to and from the ocean to feed their chicks. The weighbridge reported how much mass the penguin had gained during a foraging trip. The variables that explained a significant amount of the change in body mass while at sea were the number of foraging dives per hour (46%) and the number of undulations per hour (12%). Most importantly, every increment of 1 in the rate of foraging dives per hour equated to a penguin gaining an average 170 g of mass, over the course of a 6–60 h foraging trip. These results add to a growing understanding that different metrics of foraging success are likely appropriate for different species, and that assessing the types and frequencies of dives using time-depth recorders can yield valuable insights.

Stretchable Textile Yarn Based on UHF RFID Helical Tag

In the context of wearable technology, several techniques have been used for the fabrication of radio frequency identification (RFID) tags such as 3D printing, inkjet printing, and even embroidery. In contrast to these methods where the tag is attached to the object by using sewing or simple sticking, the E-Thread® technology is a novel assembling method allowing for the integration of the RFID tag into a textile yarn and thus makes it embeddable into the object at the fabrication stage. The current E-Thread® yarn uses a RFID tag in which the antenna is a straight half-wave dipole that makes the solution vulnerable to mechanical strains (i.e., elongation). In this paper, we propose an alternative to the current RFID yarn solution with the use of an antenna having a helical geometry that answers to the mechanical issues and keeps quite similar electrical and radiative properties with respect to the present solution. The RFID helical tag was designed and simulated taking into consideration the constraints of the manufacturing process. The helical RFID tag was then fabricated using the E-Thread® technology and experimental characterization showed that the obtained structure exhibited good performance with 10.6 m of read range in the ultra high frequency (UHF) RFID band and 10% of tolerance in terms of elongation.

Sistem Kontrol Pintu Ruang Kuliah Berbasis RFID dan Arduino Terintegrasi Aplikasi Web Presensi

Makalah ini membahas pengembangan sistem otomatisasi ruangan pada kontrol pintu dan presensi kuliah untuk menambah keamanan ruangan. Sistem ini terintegrasi dengan aplikasi web dan menggunakan papan Arduino Mega 2560 sebagai pusat kontrol sistem. Sistem ini menggunakan RFID MFRC522 sebagai alat komunikasi dua arah dengan kartu RFID dan pembaca, modul ethernet shield sebagai penghubung ke jaringan internet, solenoid sebagai pengunci pintu, LCD untuk penampil notifikasi, serta RTC DS3231 sebagai pewaktu. Hasil pengujian menunjukkan, sistem mampu mencocokkan kartu tag dosen dengan data jadwal pada basis data dan mencocokkan kartu tag mahasiswa dengan data mahasiswa di mata kuliah yang terjadwal pada basis data. Jadwal akses ruang sesuai dengan jadwal kuliah yang dapat diatur melalui aplikasi web. Selain dari itu, pada aplikasi web yang dibangun dapat mengolah data presensi, jadwal, mata kuliah, mahasiswa, dosen dan kelas. Berdasarkan hasil pengujian, pembacaan kartu RFID dapat dilakukan sampai jarak 4 cm. Penelitian ini menghasilkan sebuah sistem otomasi pintu berbasis RFID dan Arduino yang terintegrasi dengan sistem database berbasis web. This paper presenst an automation systems for controling the door’s room and lecture attendance which can enhance room security. This study build a college room control system integrated with a web application. This system uses the Arduino Mega 2560 board as the control center of the system. Furthermore, we used RFID MFRC522 as a two-way communication device with an RFID tag card and reader, an ethernet shield module that providing internet access to the network, a solenoid as a door lock, LCD for notification display, and RTC DS3231 as a timer. This system can control door access and attendance automation, and send the data to web application. The application can match the lecturer tag cards with his scheduled in the database and match students' tag cards with their data in scheduled courses. The room access schedule is in accordance to the class schedule, which can be arranged via the web application. The web application can process attendance data, schedules, courses, students, lecturers, and classes. The system can read the RFID tags up to a distance of 4 cm.