Low-cost and flexible radio frequency identification (RFID) tag for automatic identification, tracking, and monitoring of blood products is in great demand by the healthcare industry. A robust performance to meet security and traceability requirements in the different blood sample collection and analysis centers is also required. In this paper, a novel low-cost and flexible passive RFID tag is presented for blood sample collection tubes. The tag antenna is based on two compact symmetrical capacitive structures and works at the ultra-high frequency (UHF) European band (865 MHz–868 MHz). The tag antenna is designed considering the whole dielectric parameters such as the blood, substrate and tube. In this way, it operates efficiently in the presence of blood, which has high dielectric permittivity and loss. Measurement results of the proposed tag have confirmed simulation results. The measured performance of the tag shows good matching in the desired frequency band, leading to reading ranges up to 2.2 m, which is 4.4 times higher than typical commercial tags. The potential of this tag as a sensor to monitor the amount of blood contained in clinic tubes is also demonstrated. It is expected that the proposed tag can be useful and effective in future RFID systems to introduce security and traceability in different blood sample collection and analysis centers.

A new low-profile flexible RFID tag antenna operating in the ultra-high frequency (UHF) European band (865 MHz–868 MHz) is proposed for blood bag traceability. Its structure combines inductive and capacitive parts with nested slots allowing for the achieving of conjugate impedance matching with the IC-chip. The whole electrical parameters of the environment (substrate, bag, and blood) were considered for the design of the tag antenna. A good agreement was obtained between the measurements and electromagnetic simulations for the input impedance of the tag antenna in the UHF band. A reading range close to 2.5 m was experimentally obtained. Therefore, this tag antenna could be effective and useful in future RFID systems for blood bag monitoring, thus improving patient safety in healthcare infrastructures.

Multi-objective evolutionary algorithms have become the most efficient ap- proach for solving real-world problems, where performance depends on the convergence speed, balance between exploitation and exploration, and popu- lation diversity. Self-adaptive techniques are effective for dynamically adjust- ing hyperparameter algorithms. This paper presents an automated methodology for designing and optimizing a complementary split-ring resonator (CSRR)- incorporated microstrip patch antenna (MPA) using a fuzzy adaptive multi- objective genetic algorithm (FAMOGA). A double-ring CSRR structure etched into the ground plane introduces multi-band resonance frequencies, extending antenna coverage to the multi-bands frequencies used in internet of things (IoT) and Wi-Fi applications. The algorithm simultaneously determines the optimal CSRR ring positions, minimizes the antenna size, and satisfies design con- straints. Fuzzy logic controllers evaluate the fitness function and dynamically adapt the crossover and mutation rates, guiding the genetic algorithm toward feasible, high-performance solutions. The FAMOGA converges to the 7th gen- eration with a population of four individuals. At the three target frequencies, the optimized antenna achieves reflection coefficients of −11.08 dB, −39.25 dB, and −30.61 dB , and realized gains of 3.53 dBi, 4.16 dBi, and 6.64 dBi at 2.422 GHz , 3.646 GHz , and 5.259 GHz , correspondingly. The simulation demonstrated that FAMOGA provides a computationally efficient approach for multi-band antenna design without manual parameter tuning.