A new measurement method for through-the-wall detection of life signs is proposed hereinafter. The method analyzes the phase modulation that a sinusoidal signal, generated by means of a proper continuous-wave microwave transceiver, undergoes when reflected by the chest periodic displacement associated with breathing. It takes advantage of a suitable spatial smoothing decorrelation strategy applied to the traditional algorithm for MUltiple SIgnal Classification (MUSIC), mandated to single out the spectral components of the received phase signal. With respect to other measurement solutions, already available in the literature and exploiting either the traditional discrete-time Fourier transform, or matched filters, or standard singular value decomposition, the proposed method assures competitive performance in detecting the respiratory activity from the received microwave signal and effective noise/clutter rejection. The results of several tests both in simulated and actual scenarios, i.e., people behind walls in a furnished room, prove the efficacy and reliability of the method also in the presence of critical measurement conditions such as low signal-to-noise ratios and chest displacement associated with shallow breathing.

A new digital signal-processing method for ultrasonic time-of-flight (TOF) estimation is presented. The method applies the discrete extended Kalman filter (DEKF) to the acquired ultrasonic signal in order to accurately estimate the shape factors of the echo envelope as well as locate its onset. It is also possible to assure reduced bias and uncertainty in critical TOF measurements, such as those involving low signal-to-noise ratio (SNR) as well as severe distortion of echo shape. A number of numerical tests are conducted on simulated signals with the aim of highlighting the good performance of the method when operating in critical conditions. Results attained in TOF-based distance measurements finally assess the reliability and efficacy of the method in the presence of actual ultrasonic signals.

Maintenance strategies based on structural health monitoring can provide effective support in the optimization of scheduled repair of existing structures, thus enabling their lifetime to be extended. With specific regard to reinforced concrete (RC) structures, the state of the art seems to still be lacking an efficient and cost-effective technique capable of monitoring material properties continuously over the lifetime of a structure. Current solutions can typically only measure the required mechanical variables in an indirect, but economic, manner, or directly, but expensively. Moreover, most of the proposed solutions can only be implemented by means of manual activation, making the monitoring very inefficient and then poorly supported. This paper proposes a structural health monitoring system based on a wireless sensor network (WSN) that enables the automatic monitoring of a complete structure. The network includes wireless distributed sensors embedded in the structure itself, and follows the monitoring-based maintenance (MBM) approach, with its ABCDE paradigm, namely: accuracy, benefit, compactness, durability, and easiness of operations. The system is structured in a node level and has a network architecture that enables all the node data to converge in a central unit. Human control is completely unnecessary until the periodic evaluation of the collected data. Several tests are conducted in order to characterize the system from a metrological point of view and assess its performance and effectiveness in real RC conditions.

LPWAN systems are being deployed in lightly licensed regional bands. For applications with low data rate and low duty cycle, LPWAN extends battery life, reduces cost and offers improved link budgets compared with current cellular formats. Networks often use a star topology around a gateway node. LoRa is a Sub-GHz wireless technology designed for low power, unlicensed, Long Range operations. The communication performance of this technology was assessed. The results indicated that this technology can provide very robust communication even in the presence of high noise level.

The increasing pervasiveness of wearable sensors opens new scenarios in the continuous monitoring of health parameters. In particular, wearables are becoming the sensing part of the Internet of Medical Things (IoMT), i.e. IoT in the healthcare field. Currently, several IoMT based devices capable of measuring blood pressure (BP) are starting to be offered on the market, giving the possibility to monitor BP every time and everywhere. An open issue is the lack of the traceability and reliability of the BP measurements. The aim of this paper is stimulating the research to fulfil this lack by presenting an overview for IoMT and commercial wearables in BP monitoring, from a metrological point of view.