Radio frequency identification (RFID) and wireless sensors networks (WSNs) are two fundamental pillars that enable the Internet of Things (IoT). RFID systems are able to identify and track devices, whilst WSNs cooperate to gather and provide information from interconnected sensors. This involves challenges, for example, in transforming RFID systems with identification capabilities into sensing and computational platforms, as well as considering them as architectures of wirelessly connected sensing tags. This, together with the latest advances in WSNs and with the integration of both technologies, has resulted in the opportunity to develop novel IoT applications. This paper presents a review of these two technologies and the obstacles and challenges that need to be overcome. Some of these challenges are the efficiency of the energy harvesting, communication interference, fault tolerance, higher capacities to handling data processing, cost feasibility, and an appropriate integration of these factors. Additionally, two emerging trends in IoT are reviewed: the combination of RFID and WSNs in order to exploit their advantages and complement their limitations, and wearable sensors, which enable new promising IoT applications.

Currently, there is an increasing interest in the use of Radio Frequency Identification (RFID) tags which incorporate passive or battery-less sensors. These systems are known as computational RFID (CRFID). Several CRFID tags together with a reader set up an RFID sensor network. The reader powers up the tags’ microcontroller and their attached sensor using radio frequency waves, and tags backscatter, not only their EPC code but also the value of those sensors. The current standard for interrogating these CRFID tags is the EPC global Class 1 Generation 2 (EPC C1G2). When several tags are located inside the reader interrogation area, the EPC C1G2 results in very poor performance to obtain sensor data values. To solve this problem, a novel protocol called Sensor Frmed Slotted Aloha (sFSA) for streaming sensor data dealing with the tag collisions is presented. The proposed protocol increases the Sensor Read Rate (SRR), defined as the number of sensor data reads per second, compared to the standard. Additionally, this paper presents a prototype of an RFID sensor network to compare the proposed sFSA with the standard, increasing the SRR by more than five times on average. Additionally, the proposed protocol keeps a constant sensor sampling frequency for a suitable streaming of these tag sensors.

A methodology to carefully select the impedance states of a backscatter phase-shift keying (PSK) load modulator in a passive computational ultrahigh-frequency (UHF) radio frequency identification (RFID) tag is presented. Considering the most significant tag read range limitations reader sensitivity, power transmission and bit error rate (BER), the proposed selection results in constant power transmission to the energy harvester and thus in an increase of the average power at the input of the energy harvester during tag-to-reader communication. A graphical tool to select the modulator impedance states using a Smith chart is proposed.

This article presents the design and implementation of a passive, computational ultra high frequency (UHF) radio frequency identification (RFID) platform using vector backscatter modulation on the uplink (tag-to-reader). The proposed RFID system consists of a software defined radio (SDR) reader and the corresponding passive, computational tag. The communication protocol is firmware-implemented, thus offering high flexibility in configuring its functionalities. A dual-gate MOSFET is used to implement the vector backscatter modulator. Experimental results prove the platform’s feasibility and show the benefits of using vector backscatter communication compared to using the standard binary phase-shift keying (BPSK). For the investigated 128-bit tag-to-reader message based on the EPC Class 1 Generation 2 communication protocol, the sequence length was shortened by a factor of 1.91.

This manuscript presents the design and implementation of a passive, modular, computational ultra high frequency (UHF) radio frequency identification (RFID) research platform. The proposed platform consists of a software defined radio (SDR) reader and a modular UHF RFID tag. Such a tag can be subdivided into a number of modules (e.g., Modulator, Rectifier, etc.), which have been separated and optimized for easy connectability using sub-miniature A (SMA) connectors and standard jumper wires. Experimental results of module specific parameters show the accessibility of each section and prove the platform’s value for designing novel UHF RFID solutions.

Phase-based sensing using ultra high frequency (UHF) radio frequency identification (RFID) has, in recent years, yielded numerous additions to the Internet of Things (IoT). This work presents a polarization diversity based rotation sensing methodology using common-off-the-shelf (COTS) UHF RFID tags identified with a software defined radio (SDR) UHF RFID reader. The proposed methodology uses the tag-to-reader message after fully coherent demodulation to calculate a difference signal of the backscatter load modulation states. This sequence is then used to compute the rotation speed by evaluating its phase change over time. Experimental results are used to validate the theoretical model and to evaluate the performance and limitiations of the proposed system.