Francesco Bonavolontà

Inductive power transmission for wireless sensor networks supply

Wireless sensor networks are today more and more widespread. Along with the installation of more and more networks, a number of new standard documents has also been produced to update the regulation concerning data communication between sensors and data collectors. Differently, less attention has been paid to the different modes of powering the local sensors. At present, the energy required for local sensors functioning is essentially battery provided, despite the battery supply is often recognized as a critical aspect of remote sensing. In fact, the periodical battery replacement is sometimes non-strategic and troublesome, especially for those sensors which have to be installed in difficult to reach sites, or are integrated into medical implantable devices. In the above mentioned circumstances, battery-less sensors appear to be attractive, both from a pragmatic point of view, because of the strategic role they can play in critical scenarios, and from an innovation-oriented point of view, because of the novelty that wireless power transmission can add to a new ground-breaking remote sensors technology. Wireless power transmission technologies are capable of supporting battery-less sensor functioning. In this paper, first the main issues related to alternative remote devices powering solutions are plainly discussed, then, a resonant-based induction power transmission system for supplying a sensor network is also presented.

On the suitability of compressive sampling for the measurement of electrical power quality

The deeper interconnection and the increasing presence of active devices on the electrical networks is raising many issues concerning with the monitoring of Power Quality phenomena. Voltage parameters related to the supply of electricity and current parameters related to the working of electrical apparatuses have to be monitored as accurately as possible. To this aim specific international standards impose strict measurement methods and complex measurement instrument architectures, usually based on the computation of real time Fast Fourier Transforms, to be adopted for the purpose. In particular, considering poly-phase systems, four currents and four voltages have to be detected, synchronized, measured and analyzed with good accuracy and spectral resolution. This imposes to the measurement the calculation of eight FFTs in a very short time. These requirements conflicts with the need of cost-effective measurement instruments required by spread and distributed monitoring systems in many points of the electrical plant. To face this issues this paper proposes the study and the tuning of compressive sampling (CS) techniques capable of assuring reliable reconstruction of the signal of interest from very low acquired samples. In particular, to make the CS use more feasible, the authors have also exploited some peculiarities of the CS approach in order to reduce the computational burden usually associated with the mere application of its acquisition and reconstruction protocol. Preliminary results confirm the applicability of the proposed solution.

A compressive sampling based method for power measurement of band-pass signals

The paper deals with the problem of measuring the power of band-pass signals; to this aim, a new method, taking advantage of the interesting features of compressive sampling, is presented. The method proves to be particularly tailored for band-pass signals characterizing wireless communications system, whose parameters of interest are typically evaluated in frequency domain and require spectrum estimation with high frequency resolution. The use of compressive sampling, in fact, allows to preserve elevated sampling rate (needed to assure alias-free sampling of the signal of interest) and, simultaneously, avoid to acquire very long record (necessary to assure the desired frequency resolution). Moreover, the authors suggest a strategy for appropriately choosing the random sampling sequence of the input signal to overcome some known limitations of compressive sampling in terms of computational burden. Preliminary tests conducted by means of numerical simulations show promising results; differences, expressed in relative percentage terms, between estimated and nominal power never greater than 2% have been encountered, if the proper number of samples is chosen.

First step towards an IoT implementation of a wireless sensors network for environmental radiation monitoring

The paper deals with the problem of designing and implementing an inexpensive wide area sensors network for environmental radiological monitoring. To this aim, the measurement node takes advantage from a low-cost, Linux based, development platform, and some new open-source software tool, which are pushed towards a network-oriented vision of Internet of Things (IoT).

New Approach Based on Compressive Sampling for Sample Rate Enhancement in DASs for Low-Cost Sensing Nodes

The paper deals with the problem of improving the maximum sample rate of analog-to-digital converters (ADCs) included in low cost wireless sensing nodes. To this aim, the authors propose an efficient acquisition strategy based on the combined use of high-resolution time-basis and compressive sampling. In particular, the high-resolution time-basis is adopted to provide a proper sequence of random sampling instants, and a suitable software procedure, based on compressive sampling approach, is exploited to reconstruct the signal of interest from the acquired samples. Thanks to the proposed strategy, the effective sample rate of the reconstructed signal can be as high as the frequency of the considered time-basis, thus significantly improving the inherent ADC sample rate. Several tests are carried out in simulated and real conditions to assess the performance of the proposed acquisition strategy in terms of reconstruction error. In particular, the results obtained in experimental tests with ADC included in actual 8- and 32-bits microcontrollers highlight the possibility of achieving effective sample rate up to 50 times higher than that of the original ADC sample rate.

Frequency domain measurement node based on compressive sampling for sensors networks

The paper deals with the problem of designing and implementing a measurement node based on compressive sampling (CS). The considered node is tailored for wide area sensors networks aimed to carry out measurements in frequency domain. To this aim, the node takes advantage from some known or recently proposed CS features in such a way as to outperform the nominal specification of its data acquisition module. To make the spectrum estimation feasible on the node level, a suitable strategy for input signal random sampling and an efficient CS implementation, i.e. the greedy algorithms based on the so-called match-pursuit approach, are exploited. First tests are presented, related to a cost-effective microcontroller from STMicrocontroller, namely STM32F429ZI, characterized by a data memory depth sufficient to execute the agile computational scheme of the greedy algorithm. The estimated spectra concur with those obtained through standard discrete Fourier transform-based approaches, thus highlighting the feasibility of the proposed measurement node.

An Embedded Wireless Sensor Network with Wireless Power Transmission Capability for the Structural Health Monitoring of Reinforced Concrete Structures

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.

Experimental performance assessment of compressive sampling-based THz imaging systems

The paper aims at experimentally assessing the metrological performance of a compressive sampling (CS)-based terahertz (THz) imaging system, an emerging technology for carrying out non-destructive tests of materials in order to detect defects and flaws. Differently from systems based on traditional raster scan, the exploitation of CS allows, in fact, obtaining images of interest in a reduced observation interval to the detriment of accuracy. In literature, several studies have faced the topic at hand showing results obtained in simulated and real conditions. On the same way, the authors have decided to focus their attention on the experimental investigation of the impact of some uncertainty sources on the final image reconstruction realizing a metrological characterization that could be used in different fields as for example aerospace. It is so possible to provide a preliminary roadmap capable of driving experimenters in the definition of the main features of the measurement setup to achieve a defined goal in term of reconstruction quality.

First step towards a cost-effective lot platform for customers power consumption awareness

The paper deals with the definition, implementation and performance assessment of an Internet of things (IoT) platform for measuring and monitoring power consumption in smart home or smart industry applications. Thanks to the adoption of suitable cost-effective hardware components and a proper software architecture implemented on Raspberry PI, the IoT platform can assure real-time power monitoring on electrical loads connected to domestic and industrial power plugs. Particular attention has been paid to the selection of the application layer protocol mandated to exchange data between the power measuring nodes and the Raspberry PI in order to assure reliable communication with a reduced computational and connection overhead. The availability of the measurement results on a web page that does not require any specific software but a web browser highlights the efficacy of the adopted platform to assure aware in power consumption for domestic and industrial customers.

Enabling wireless technologies for industry 4.0: State of the art

The current revolution of the manufacturing sector, usually referred to as Industry 4.0, is deeply modifying the traditional production paradigms. The availability of cost-effective sensing and/or computing elements as well as ad-hoc communications protocols are, in fact, making it possible to provide the whole supply chain with a global awareness about the production process. Selecting the most adequate protocol results fundamental to assure the best integration of the industrial machines with the current de-facto information framework, i.e. Internet of Things. Stemming from their past experiences on wireless communication and distributed measurement systems, the authors will provide hereinafter a proper roadmap between the different and most common communication protocols according both to the wireless operating range and industrial requirements.