Francesco Abate

A Comparison Between Sensor Signal Preprocessing Techniques

The need for the use of sensor networks in ever more efficient manner drives research methods for better information management. It would be useful to decrease the amount of managed data. Often, we are interested in few noteworthy information of a signal (for example, period, amplitude, time constant, steady state value, and so on) not in the whole waveform. The idea is to take less data, but acquire the same information. In a highly oversampled signal, each single sample does not carry a lot of information. From this point, two different algorithms are compared, in which only few samples are stored or transferred. This paper describes these two algorithms: the first one is the segmentation and labeling algorithm, also proposed for the definition of the new standard of the IEEE 1451 and the second one is based on compressive sensing theory. These two algorithms are compared, the simulations results are shown, and it is discussed which case could be more suitable.

Normalizing transducer signals: An overview of a proposed standard

This paper presents an overview of the proposed standard ISO/IEC/IEEE P21451-001 for sensor signals that is currently under development. The IoT, Internet of Things, is a reality. Most of things have sensors embedded without drawing distinction between industrial and consumer products. Things can be easily identified and the protocols that govern the traffic over the nets are well defined. However, what is difficult to define is the information that a thing with sensors should report. Therefore, the objective of this standard is to define a first approach to describe sensor signals, in a way that can be applied to any sensor extracting information from samples. The paper is divided into two main sections. The first one describes the basic algorithms that extract knowledge from samples. The second one shows the internal structure of the working group for normalizing these algorithms and the remaining challenges.

Preliminary analysis of a real time segmentation and labeling algorithm

An analysis of parameters extraction algorithms, like mean, period or root mean square value, based on a real time segmentation and labeling technique is shown in this paper. This algorithm, proposed also as a recommended practice for the IEEE 21451 new family of standard for smart sensors, allows to obtain as an output only several meaningful samples, with an additional information about the shape. Results of simulations of the algorithm are shown, comparing these with implementations results for the same parameters computations on a scope.

A comparison between FFT and MCT for period measurement with an ARM microcontroller

A comparison between two different algorithms to measure the period of a signal is performed on this work. One of the algorithms is based on the Fast Fourier Transformation (FFT) measurement procedure, whereas the other is based on the Segmentation and Labeling algorithm (MCT). Both algorithms have been prepared for implementation in a microcontroller with ARM architecture. The measurement operation of each one of the algorithms is described in detail. Experimental results are reported, with the purpose of demonstrating both performance and output format for signal analysis.

Semi-active RFID Devices for Traceability

In this paper a semi-active RFID module for remote monitoring of storage conditions during the transportation is proposed. It integrates one SmartTag and some sensors, and allows also to locate the object to the one which is related. In order to obtain the real time observing on the transportation vehicle an On Board Unit (OBU) is installed that works as a concentrator and communicates with a central control room.

Real time transducer signal features extraction: A standard approach

This paper presents a real time algorithm, based on a segmentation and labelling technique, for analog transducer signals, which extracts information from the signal. The process of sampling is extremely important because it is the only one that connects the real world with the digital world. In addition, the proposed technique can be embedded into sensors, allowing applications in sensor networks and sensors data fusion architectures like Internet of Things. A simplified version of these algorithms has been proposed as a standard for transducer signal feature extraction. These algorithms are analysed and experimental results are tackled for representative signals, in different fields.

A multiservice network for gas and water meters management

The increasing offer of connectivity and of mobile tools (mobile phones, PDA) has determined a new scenario of computation in which the users can access resources and services and interact with each other in any moment and place. This technological revolution has involved all the fields, included the one that involves the meters and their management. If the remote management of the meters of latest generation has at this point entered our everyday life, there is a considerable number of old meters that cannot be neglected, but that have to be remotely controlled for reasons of security and efficacy. In this paper, it is proposed a system to connect these devices creating a management environment in complete compliance with the paradigm of the Internet of Things. The entire environment has been tested in a real context giving satisfying results.

Impedance measurement in IEEE 21451 transducer interface modules

The paper deals with an impedance measurement technique that could be real time executed by smart transducers. The technique is based on a standardized data structure (in the following named MCT), that is a new way to represent sampled signals within transducer interface modules, as defined in the standard IEEE 21451-001-2017. At first, the MCT data structure is briefly presented. Then the impedance measurement algorithm is described. Finally, the results of some simulation tests are reported and discussed.

Uncertainty of a real time segmentation and labeling algorithm in signal period measurement

This paper examines the uncertainty of period measurement, using a real time segmentation and labeling algorithm, proposed for the definition of a new standard of the IEEE 1451, the family of standards for smart sensors. Firstly, an explanation of the algorithm is shown. Secondly, several simulation results are analyzed. Finally, experimental result are shown.

Power data fusion for train and railway electrification system

The reduction of energy consumption in electric trains is a big challenge of the next years. Lower consumptions means a more convenient design of the electric power supply network of the trains; in particular increasing the margin between peak demand and maximum power limit of the network improves the overall reliability. To this aim, the energy recovered from braking of one train may be used to aid the acceleration of the same or another train. Recovering energy from braking is a well-known idea, and the possibility to exchange energy between breaking trains and departing trains is very attractive. With this goal in mind the train vectors need to exchange information about their instantaneous power consumption and the data should be available for comparisons in a common time scale. In this paper will be presented an Android based measurement system for electric trains able to make synchronous measurements. The measurement system presented is composed of wireless sensors making it easy to install on modern train vectors.