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Wireless sensor network (WSN) applications are under extensive research and development due to the need to interconnect devices with each other. To reduce latency while keeping very low power consumption, the implementation of a wake-up receiver (WuR) is of particular interest. In WuR implementations, meeting high performance metrics is a design challenge, and the obtention of high-sensitivity, high data rate, low-power-consumption WuRs is not a straightforward procedure. The focus of our proposals is centered on power consumption and area reduction to provide high integrability and maintain a low cost-per-node, while we simultaneously improve circuit sensitivity. Firstly, we present a two-stage design based on a feedback technique and improve the area use, power consumption and sensitivity of the circuit by adding a current-reuse approach. The first solution is composed of a feedback amplifier, two op-amps plus a low-pass filter. The circuit achieves a sensitivity of –63.2 dBm with a power consumption of 6.77 µA and an area as low as 398 × 266 µm2. With the current-reuse feedback amplifier, the power consumption is halved in the second circuit (resulting in 3.63 µA), and the resulting circuit area is as low as 262 × 262 µm2. Thanks to the nature of the circuit, the sensitivity is improved to –75 dBm. This latter proposal is particularly suitable in applications where a fully integrated WuR is desired, providing a reasonable sensitivity with a low power consumption and a very low die footprint, therefore facilitating integration with other components of the WSN node. A thorough discussion of the most relevant state-of-the-art solutions is presented, too, and the two developed solutions are compared to the most relevant contributions available in the literature.

Integration of technological solutions aims to improve accuracy, precision and repeatability in farming operations, and biosensor devices are increasingly used for understanding basic biology during livestock production. The aim of this study was to design and validate a miniaturized tri-axial accelerometer for non-invasive monitoring of farmed fish with re-programmable schedule protocols. The current device (AE-FishBIT v.1s) is a small (14 mm × 7 mm × 7 mm), stand-alone system with a total mass of 600 mg, which allows monitoring animals from 30 to 35 g onwards. The device was attached to the operculum of gilthead sea bream (Sparus aurata) and European sea bass (Dicentrarchus labrax) juveniles for monitoring their physical activity by measurements of movement accelerations in x- and y-axes, while records of operculum beats (z-axis) served as a measurement of respiratory frequency. Data post-processing of exercised fish in swimming test chambers revealed an exponential increase of fish accelerations with the increase of fish speed from 1 body-length to 4 body-lengths per second, while a close relationship between oxygen consumption (MO2) and opercular frequency was consistently found. Preliminary tests in free-swimming fish kept in rearing tanks also showed that device data recording was able to detect changes in daily fish activity. The usefulness of low computational load for data pre-processing with on-board algorithms was verified from low to submaximal exercise, increasing this procedure the autonomy of the system up to 6 h of data recording with different programmable schedules. Visual observations regarding tissue damage, feeding behavior and circulating levels of stress markers (cortisol, glucose, and lactate) did not reveal at short term a negative impact of device tagging. Reduced plasma levels of triglycerides revealed a transient inhibition of feed intake in small fish (sea bream 50–90 g, sea bass 100–200 g), but this disturbance was not detected in larger fish. All this considered together is the proof of concept that miniaturized devices are suitable for non-invasive and reliable metabolic phenotyping of farmed fish to improve their overall performance and welfare. Further work is underway for improving the attachment procedure and the full device packaging.

The development of wake-up receivers (WuR) has recently received a lot of interest from both academia and industry researchers, primarily because of their major impact on the improvement of the performance of wireless sensor networks (WSNs). In this paper, we present the development of three different radiofrequency envelope detection (RFED) based WuRs operating at the 868 MHz industrial, scientific and medical (ISM) band. These circuits can find application in densely populated WSNs, which are fundamental components of Internet-of-Things (IoT) or Internet-of-Everything (IoE) applications. The aim of this work is to provide circuits with high integrability and a low cost-per-node, so as to facilitate the implementation of sensor nodes in low-cost IoT applications. In order to demonstrate the feasibility of implementing a WuR with commercially available off-chip components, the design of an RFED WuR in a PCB mount is presented. The circuit is validated in a real scenario by testing the WuR in a system with a pattern recognizer (AS3933), an MCU (MSP430G2553 from TI), a transceiver (CC1101 from TI) and a T/R switch (ADG918). The WuR has no active components and features a sensitivity of about −50 dBm, with a total size of 22.5 × 51.8 mm2. To facilitate the integration of the WuR in compact systems and low-cost applications, two designs in a commercial UMC 65 nm CMOS process are also explored. Firstly, an RFED WuR with integrated transformer providing a passive voltage gain of 18 dB is demonstrated. The circuit achieves a sensitivity as low as −62 dBm and a power consumption of only 528 nW, with a total area of 634 × 391 μm2. Secondly, so as to reduce the area of the circuit, a design of a tuned-RF WuR with integrated current-reuse active inductor is presented. In this case, the WuR features a sensitivity of −55 dBm with a power consumption of 43.5 μW and a total area of 272 × 464 μm2, obtaining a significant area reduction at the expense of higher power consumption. The alternatives presented show a very low die footprint with a performance in line with most of the state-of-the-art contributions, making the topologies attractive in scenarios where high integrability and low cost-per-node are necessary.