Bio-integrated wireless sensors in the form of conformable plaster, based on the Radiofrequency Identification (RFID) communication, have been recently proposed for the battery-less measurement of the human skin temperature. However, the response of the Integrated Circuit (IC) transponder is sensitive to the strength of the interrogating power. Indeed, high power produces artifacts on the sampled temperature up to 2 °C when the mutual position between reader and sensors, as well as the emitted power, can not be carefully controlled. Hence, a reliable adoption of this technology in real cases is challenging and still in question. A combined macro-scale electromagnetic-thermal model is here introduced to predict and correct the above artifact so that the temperature measurement becomes insensitive to the RF power collected by the IC. The method is based on the new generation RFID ICs with on-chip temperature sensor that are also capable to give back the strength of the collected RF power. The model is validated in controlled conditions and then applied for different skin temperature measurements on human body. An average accuracy of ±0.25 °C, compared with a reference calibrated thermocouple, was demonstrated in the considered tests.

Electromagnetic-Based Correction of Bio-Integrated RFID Sensors for Reliable Skin Temperature Monitoring

This paper is an extended version of the work published. Radio-frequency identification (RFID) is widespread in industries such as supply-chain management and logistics due to its low-cost feature. In many real-world problems, one often needs to leverage a considerable amount of RFID readers to cover a large area. Many graph-based dense RFID readers system anti-collision algorithms were proposed to address the collision problems. However, state-of-the-art collision avoidance algorithms are centralized algorithms. In a dense RFID system, the graphs generated by the centralized algorithms could be very complicated. Therefore, a centralized algorithm increases the computational workload of the central server. We proposed a distributed anti-collision algorithm based on the idea of a centralized collision avoidance algorithm called MWISBAII. In our later research, we found that due to the lack of global information, there is a gap between the performance of our distributed algorithm and the centralized MWISBAII. To narrow this gap, we introduced machine learning into the proposed algorithm. The machine learning model is an empirical model that mitigates the deficiency of the lack of global information. The experimental results show that the proposed distributed algorithm with machine learning can get almost the same performance as the centralized MWISBAII in different experimental settings.

/pdf/a-machine-learning-auxiliary-approach-for-the-distributed-kigepc217s.pdf

A Machine Learning Auxiliary Approach for the Distributed Dense RFID Readers Arrangement Algorithm

This paper presents the architecture and design trade-off of a compact, programmable, battery-less UHF-RFID sensor tag for environmental monitoring. The node is based on a single UHF monopole matched to a dual-path rectifier for both energy harvesting purposes and wake-up radio capabilities. The based-band circuit includes a power management unit (PMU) to supply the microcontroller unit which is in charge of implementing the EPC Gen 2 Class 1 standard protocol fully working with European ETSI compliant readers. The prototype was built with off-the-shelf components in a 95x31 mm2 PCB with low losses Rogers 4350B substrate. The proposed circuit can wake-up starting from a fully discharged state and operate at distances up to 9.70 m from a 2W ERP source in the UHF 865868 MHz frequency band, with a power sensitivity of -16 dBm, while performing temperature sensing and radio-frequency communication. If an on-board battery is added, the battery-assisted solution is able to work as far as 15 m from the interrogator reaching the highest sensitivity of -17.8 dBm while the energy harvesting circuits replenishing the battery.

/pdf/long-range-battery-less-uhf-rfid-platform-for-sensor-3bth492irq.pdf

Long Range Battery-Less UHF-RFID Platform for Sensor Applications

In this paper a new backoff algorithm is proposed to enhance both the delay and the throughput performance of IEEE 802.11b MAC protocol. The proposed waiting time based backoff algorithm (WBA), observes the Waiting-time of each station during the backoff procedure in order to estimate the size of contention window in the network. The main objective of our investigation is to examine the performance of IEEE 802.11 MAC protocol with our proposed algorithm and compare with the standard backoff algorithm i.e. Binary Exponential Backoff (BEB) algorithm. The simulation results show that the WBA algorithm outperforms the standard backoff algorithm because it has better adaptability to the network load variations.

A waiting-time based backoff algorithm in the IEEE 802.11 based wireless networks

The current growing demand for low-cost edge devices to bridge the physical-digital divide has triggered the growing scope of Radio Frequency Identification (RFID) technology research. Besides object identification, researchers have also examined the possibility of using RFID tags for low-power wireless sensing, localisation and activity inference. This paper focuses on passive UHF RFID sensing. An RFID system consists of a reader and various numbers of tags, which can incorporate different kinds of sensors. These sensor tags require fast anti-collision protocols to minimise the number of collisions with the other tags sharing the reader's interrogation zone. Therefore, RFID application developers must be mindful of anti-collision protocols. Dynamic Frame Slotted Aloha (DFSA) anti-collision protocols have been used extensively in the literature because EPCglobal Class 1 Generation 2 (EPC C1G2), which is the current communication protocol standard in RFID, employs this strategy. Protocols under this category are distinguished by their policy for updating the transmission frame size. This paper analyses the frame size update policy of DFSA strategies to survey and classify the main state-of-the-art of DFSA protocols according to their policy. Consequently, this paper proposes a novel policy to lower the time to read one sensor data packet compared to existing strategies. Next, the novel anti-collision protocol Fuzzy Frame Slotted Aloha (FFSA) is presented, which applies this novel DFSA policy. The results of our simulation confirm that FFSA significantly decreases the sensor tag read time for a wide range of tag populations when compared to earlier DFSA protocols thanks to the proposed frame size update policy.

https://www.mdpi.com/1424-8220/20/9/2696/pdf

Dynamic Frame Update Policy for UHF RFID Sensor Tag Collisions.

To address the problems of high computational complexity, inflexible frame length adjustment, and sub-optimal system efficiency of the RFID tag anti-collision algorithms in the Internet-of-Things systems, a low-complexity, and universal fast RFID tag anti-collision algorithm is proposed in this paper. A faster and less-complex tag number estimation method depends less on computing and storage resources, making it easier to integrate into the Internet of Things. Using the concepts of sub-frame and system efficiency priority, after each sub-frame is identified, the number of tags is estimated quickly and the frame length is adjusted dynamically to ensure the algorithm's efficiency. Moreover, the proposed algorithm is fully compatible with the EPC Class-1 Generation-2 standard, which ensures its universality and compatibility with the existing systems. The simulation results show that the proposed algorithm can achieve a system efficiency of 0.3554, a time efficiency of 0.7851, and an identification speed of 433 n/s. Compared with the standard Q algorithm, the performance is improved by 9.691%, 5.002%, and 8.250%, respectively. It is, hence, demonstrated that the proposed algorithm meets the requirements for the rapid identification of the RFID tags in the Internet-of-Things applications.

/pdf/a-fast-and-universal-rfid-tag-anti-collision-algorithm-for-513lutkowm.pdf

A Fast and Universal RFID Tag Anti-Collision Algorithm for the Internet of Things

The integration of temperature sensor (TS) and UHF RFID technology has attracted wide attention theoretically and experimentally. The architecture, power consumption, temperature measurement range, accuracy, and communication distance are key indicators of the performance of UHF RFID temperature sensor chip (RID-TSC). This work aims to provide a clearer view of the development of UHF RFID-TSC integration technology. After a systematic analysis of the characteristics of ADC, TDC, and FDC used in an integrated TS, the key low-power technologies under different architectures are summarized. Through the observation of the latest researches and commercial products, the development trend of UHF RFID-TSC technology is obtained, including on-chip and off-chip coordination, multiprotocol and multifrequency support, passive wireless sensor intelligence, miniaturization, and concealment.

/pdf/architecture-characteristics-and-technical-trends-of-uhf-2z02cw6eoz.pdf

Architecture Characteristics and Technical Trends of UHF RFID Temperature Sensor Chip

Radio-frequency identification (RFID) tag anticollision algorithm is a key technology that affects the performance of RFID systems. In dynamic arrival scenarios, when the tags arrive the reader’s interrogation zone, they cannot participate in the ongoing identification immediately, resulting in longer waiting time and tag miss. Focusing on solving this problem, based on blocking technology, dynamic frame-slotted ALOHA (DFSA) algorithm, and the first-come-first-serve (FCFS) idea, a fast RFID tag anticollision algorithm for dynamic arrival scenarios is proposed, named as “DAS-DFSA algorithm”. By optimizing the instruction structure and identification process, the DAS-DFSA allows the new arrival tag to immediately participate in the ongoing identification process, the tag’s waiting time is shortened, and the miss rate is reduced. DAS-DFSA not only adopts blocking technology to prevent the collision between the arrival tag and waiting tag but also uses unequal-length slots to reduce the communication time overhead. Simulation results show that the identification speed of the algorithm is significantly improved and high system efficiency is guaranteed. Under the same operating conditions, compared with similar algorithms, the waiting time is shortened by more than 44.548% and the identification speed is improved by at least 39.053%. More importantly, it can provide the instant-on-service for dynamic arrival tags and can fully meet the requirements of fast identification of tags in different dynamic arrival scenarios.

/pdf/a-fast-rfid-tag-anticollision-algorithm-for-dynamic-arrival-deaax3c91e.pdf

A Fast RFID Tag Anticollision Algorithm for Dynamic Arrival Scenarios Based on First-Come-First-Serve

This paper describes the binary exponential backoff mechanism of 802.11 distributed coordination function (DCF), and introduces some methods of modifying the backoff scheme. Then a novel backoff scheme, called two-step backoff scheme, is presented and illustrated. The simulation process in OPNET environment has been described also. At last, the analysis and simulation results show that the Two-step backoff scheme can enhance the performance of the IEEE 802.11 DCF.

A two-step backoff scheme for improving the performance of the IEEE 802.11 distributed coordination function

With the vigorous development of computing power, Convolutional Neural Network (CNN) is developing rapidly, and new CNN structures with more layers and better performance continue to appear. Field Programmable Gate Array(FPGA) has gradually become the best choice for people to deploy and accelerate CNNs as a current research hotspot. This paper has studied the hardware acceleration method of FPGA to implement and simulate the Softmax layer of Alexnet on Vivado 2018.1. Combined with the features of FPGA, the Cordic algorithm is used to implement basic operations such as division and exponential functions, instead of consuming floating-point arithmetic resources. The paper proposes a method to shrink the convergence domain and analyzes the errors generated by the different digits of data after quantization and fixed-point inputs. The relative error of the Softmax layer exponential function is controlled below 0.0146% by reducing the bit width which satisfied the design requirements and saved resources. This method can complete the calculation and classification of the Softmax layer in 66.5 cycles without processing the layer data at fixed points, which greatly improves the calculation speed of the Softmax layer.

Wan’ang Xiao

Papers

A Fast and Universal RFID Tag Anti-Collision Algorithm for the Internet of Things

Architecture Characteristics and Technical Trends of UHF RFID Temperature Sensor Chip

A Fast RFID Tag Anticollision Algorithm for Dynamic Arrival Scenarios Based on First-Come-First-Serve

A two-step backoff scheme for improving the performance of the IEEE 802.11 distributed coordination function

Cordic-based Softmax Acceleration Method of Convolution Neural Network on FPGA