Nowadays, wireless sensor network (WSN) users are demanding more and more in terms of choice and diversity of applications. Hence, as the diversity of applications is increasing, it is worthwhile to propose a structure for the set of characterization parameters that allows sketching a taxonomy for WSN applications. This taxonomy is established via an application-oriented approach, identifying the specific services offered by each application. In this survey, we fill this gap in the WSN literature by describing the characterization parameters, organized into six different categories. Our taxonomy for application classification is centered on the different sets of parameters that have high impact on a given future WSN application. Typical attributes and values from related research works are considered as a reference, but in this survey, we propose inter- and intra-connections among the considered application groups. Based on these connections, new application groups have been proposed for applications that share common characterization parameters, along with a holistic overview of WSN application taxonomy and the discussion of the three generations of WSNs toward communication between things and the Internet of Things, as well as future trends for the development of WSN applications. Moreover, detailed parameters from different projects and authors in the field of WSNs are joined together for comparison purposes.

The radio frequency spectrum is getting more congested day by day due to the growth of wireless devices, applications, and the arrival of fifth generation (5G) mobile communications. This happens because the radio spectrum is a natural resource that has a restricted existence. Access to all devices can be granted, but in a more efficient way. To resolve the issue, cognitive radio technology has come out as a way, because it is possible to sense the radio spectrum in the neighboring. Spectrum sensing has been recognized as an important technology, in cognitive radio networks, to allow secondary users (SUs) to detect spectrum holes and opportunistically access primary licensed spectrum band without harmful interference. This paper considers the Energy Detection (ED) and Matched Filter Detection (MFD) spectrum sensing techniques as the baseline for a study where the so-called Hybrid Matched Filter Detection (Hybrid MFD) was proposed. Apart from an analytical approach, Monte Carlo simulations have been performed in MATLAB. These simulations aimed at understanding how the variation of parameters like the probability of false alarm, the signal-to-noise ratio ( SNR ) and the number of samples, can affect the probability of miss-detection. Simulation results show that i) higher probability of miss-detection is achieved for the ED spectrum sensing technique when compared to the MFD and Hybrid MFD techniques; ii) More importantly, the proposed Hybrid MFD technique outperforms MFD in terms of the ability to detect the presence of a primary user in licensed spectrum, for a probability of false alarm slightly lower than 0.5, low number of samples and low signal-to-noise ratio.

Wearable wireless medical sensors beneficially impact the healthcare sector, and this market is experiencing rapid growth. In the United States alone, the telecommunications services market for the healthcare sector is forecast to increase from $7.5 billion in 2008 to $11.3 billion in 2013. Medical body area networks improve the mobility of patients and medical personnel during surgery, accelerate the patients¿ recovery, and facilitate the remote monitoring of patients suffering from chronic diseases. Currently, MBANs are being introduced in unlicensed frequency bands, where the risk of mutual interference with other electronic devices can be high. Techniques developed during the evolution of cognitive radio can potentially alleviate these problems in medical communication environments. In addition, these techniques can help increase the efficiency of spectrum usage to accommodate the rapidly growing demand for wireless MBAN solutions and enhance coexistence with other collocated wireless systems. This article proposes a viable architecture of an MBAN with practical CR features based on ultra wideband radio technology. UWB signals offer many advantages to MBANs, and some features of this technology can be exploited for effective implementation of CR. We discuss the physical and MAC layer aspects of the proposal in addition to the implementation challenges.

This paper presents a study of the electrical and mechanical behavior of several continuous carbon fibers epoxy composites for both strengthening and monitoring of structures. In these composites, the arrangement of fibers was deliberately diversified to test and understand the ability of the composites for self-sensing low strains. Composites with different arrangements of fibers and textile weaves, mainly unidirectional continuous carbon reinforced composites, were tested at the dynamometer. A two-probe method was considered to measure the relative electrical resistance of these composites during loading. The measured relative electrical resistance includes volume and contact electrical resistances. For all tested specimens, it increases with an increase in tensile strain, at low strain values. This is explained by the improved alignment of fibers and resulting reduction of the number of possible contacts between fibers during loading, increasing as a consequence the contact electrical resistance of the composite. Laboratory tests on strengthening of structural elements were also performed, making hand-made composites by the “wet process”, which is commonly used in civil engineering for the strengthening of all types of structures in-situ. Results show that the woven epoxy composite, used for strengthening of concrete elements is also able to sense low deformations, below 1%. Moreover, results clearly show that this textile sensor also improves the mechanical work of the strengthened structural elements, increasing their bearing capacity. Finally, the set of obtained results supports the concept of a textile fabric capable of both structural upgrade and self-monitoring of structures, especially large structures of difficult access and needing constant, sometimes very expensive, health monitoring.

The use of wearable biomedical sensors for the continuous monitoring of physiological signals will facilitate the involvement of the patients in the prevention and management of chronic diseases. The fabrication of small biomedical sensors transmitting physiological data wirelessly is possible as a result of the tremendous advances in ultra‐low power electronics and radio communications. However, the widespread adoption of these devices depends very much on their ability to operate for long periods of time without the need to frequently change, recharge or even use batteries. In this context, energy harvesting (EH) is the disruptive technology that can pave the road towards the massive utilisation of wireless wearable sensors for patient self‐monitoring and daily healthcare. Radio‐frequency (RF) transmissions from commercial telecommunication networks represent reliable ambient energy that can be harvested as they are ubiquitous in urban and suburban areas. The state‐of‐the‐art in RF EH for wearable biomedical sensors specifically targeting the global system of mobile 900/1800 cellular and 700 MHz digital terrestrial television networks as ambient RF energy sources are showcased. Furthermore, guidelines for the choice of the number of stages for the RF energy harvester are presented, depending on the requirements from the embedded system to power supply, which is useful for other researchers that work in the same area. The present authors' recent advances towards the development of an efficient RF energy harvester and storing system are presented and thoroughly discussed too.