In this paper, an AI tool based on a Large Language Model is presented to generate the mandatory TEDS of the IEEE 1451 standard. The TEDS generation process is a challenging process that requires a comprehensive knowledge of the IEEE 1451 and TEDS format. Currently, the process is manual, with entering the required data and choosing a TEDS template. However, in order to simplify the process, an AI tool is proposed to receive the user’s data in a simple text entry format and generate the binary codes automatically. This tool is presented in this paper along with some examples to demonstrate the feasibility of the process.

In this paper, a new model for the design and development of distributed control and measurement systems will be presented. The system is based on IEC 61499 and IEEE 1451 standards to benefit from the features they offer. The robust distributed control mechanism of IEC 61499 compliments the advanced plug-and-play feature of IEEE 1451 at the transducer level. The proposed employs the Unified Modelling Language (UML) for an earthquake detection system as a case study. System requirements, design and development, and implementation are the three phases of the model at two levels of Cyber and Physical. This will allow the user to visualize the whole system that can be adopted for any application. Several UML diagrams are used in order to facilitate the design process at different levels of abstraction.

One of the main challenges in applying Artificial Intelligence (AI) is to develop reliable systems that simultaneously give valid and reproducible results. The popularity of such techniques for classification and prediction has had a disruptive impact bringing numerous benefits and accelerating progress in several areas such as autonomous driving, cybersecurity, industrial process condition monitoring, and predictive maintenance. On the other hand, the lack of or little treated evaluation of the quality of these methodologies, is noteworthy, particularly in assessing the uncertainty of measurements obtained through such approaches. This paper highlights the current state of the uncertainty assessment in Artificial Intelligence-based measurement approaches with the primary objective of proposing a new methodology relying on the law of propagation of uncertainty based on the principles described in the ISO GUM (Guide to the Expression of Uncertainty in Measurement) standard. Thus, it is necessary to investigate the aspects related to the propagation of uncertainty to the model of an Artificial Neural Network, taking into account all the issues related to the black-box nature of the networks and the non-linearities that characterize them.

In the last decades, smart sensor networks have become a vital component of society. It has been used over the past years to develop ways to create smart sensor networks in which every smart sensor can communicate its main parameters to the others in the network. In this way, the IEEE 1451 family of standards is becoming significantly used in several fields to establish a communication protocol between smart sensors. This family of standards has been expanded over the last decades with new standards introducing novelties regarding the various aspects of communication between smart sensors. This paper discusses using acoustic waves to transmit data between user applications and smart sensors over metallic-made structures. The possibility of sending modulated signals with an OOK digital modulation is also presented. Finally, the work shows an experimental setup to characterize, from an acoustic propagation point of view, the communication channel.

Indoor tracking solutions of objects and people have gained significant interest in different scenarios and for a wide range of applications. On one end, the ability to detect and locate moving objects is a plus. On the other end, the amount of energy needed to power the tags poses some limitations to its operation. Moreover, as energy harvesting solutions are not always suited, the tags are usually powered by batteries, thus needing recharge or replacement. Therefore, monitoring and estimation of the energy consumption of the tags are required to operate correctly. This contribution presents an experimental setup and methodology to collect data on energy consumption of the tag, using Bluetooth Low Energy (Bluetooth 5.0) for different operation modes, namely the transmission power and the data rate. This methodology allows the estimation of energy needs according to the requirements and adopts energy-saving strategies. The experimental setup uses the Silicon Labs EFR32BG13 family and performs energy measurements via the Simplicity Studio 5 Energy Profiler and the X-NUCLEO-LPM01A board for comparison purposes. The results obtained are presented and discussed.

Data communication is crucial in monitoring and control applications. Several standards and technologies have been developed for the data exchange among the devices (e.g. smart meters, sensors) included in a communication network, exploiting either wired or wireless infrastructures. The choice of the communication technology depends on several factors, like the required data transfer rate, the cost of infrastructure installation, reliability and security. In the last decades, wireless technologies spread thanks to their lower installation costs, higher flexibility and mobility respect to the wired infrastructures that suffer the need of expensive cables deployment, making sometimes the installation not affordable. For this reason, the Power Line Communication (PLC) gained attention being based on the reuse of the existing power grid infrastructure for the data transmission, removing the costs related to the infrastructure installation. A similar approach is proposed in this paper, in which the use of the gas pipelines as communication channel for the data transmission has been investigated. The purpose of the work is to allow the data exchange in a cathodic protection (CP) monitoring system for a gas pipeline network, using the pipeline itself as communication channel, avoiding the need of a separated data transmission infrastructure. The proposed nodes are powered by the cathodic voltage of the pipe.

The paper describes a robust technique implemented into the inclinometer based on Lookup Table (LUT) Filter. The filter memorizes the acceleration data corresponding to the angle of inclination as an ideal curve graph of Microelectromechanical Systems (MEMS) accelerometer. This technique works as not only acceleration calibration but also a powerful tool of inclination measurement. A high precision robust setup for inclinometer calibration and metrology was built. The proposed method is applied to two axis-inclinometer with a maximum error of 0.2 degrees. For industrial applications, Control Area Network open (CANopen) is used as an embedded network communication system. The experiment includes both static and dynamic procedures to justify the accuracy as well as the stability of the operating system. The project was carried out at the `Sensor System' in Italy, which is an industrial company in the inclinometer field.

With the demand for greener urban mobility solutions, cities are implementing bike-sharing systems to reduce the usage of combustion engine vehicles and, at same time, promote physical activities. This concept presents itself as a good scenario to the implementation of wireless sensors network on bicycles due to its features: mobile transducers, different sensors and data, and system architecture. This paper discusses the scenario of an e-bike sharing infrastructure that implements a network of transducers following the guidelines from IEEE 1451 standards, highlighting the implementation its details. The development of network compliant with this family of standards promotes the implementation of features such as interoperability, connectivity, scalability, and plug-and-play on new devices and systems.

Most of engineering infrastructure including bridges impacts significantly civilians life quality and safety. Despite carrying their own weight and live load during operation, structure members are also seriously affected by disaster and environment. This research paper proposed an investigation in the changes of vibration frequency and the main girder(road) deflection. The outcome of the dynamic analysis that considered a vehicle traveling on the bridge, demonstrate that the vibration characteristics and the deflection response changed as damage progressed. It was discovered to be possible to identify the conditions leading to advanced deformations and collapse of the bridge. The paper finally proposes an sensor network able to identify the earliest damage which can occurs on the bridge.

In this paper a method for IMU and MARG alignment in two wheeled vehicles suspension control system is presented. Nowadays, the initial alignment of the device with respect to the vehicle frame is obtained thanks to algorithms available in literature based on the estimation of the attitude and simple geometrical rules to determine. However, these classical procedures do not allow to obtain a precise measurement of the initial device attitude. The proposed method aims to fuse data between classical methods results and GPS/GNSS signals to improve the existing methodologies. The algorithm has been implemented on a low cost platform to demonstrate its feasibility and it has been tested on a motorcycle during real ride conditions. The performed experiments have demonstrated the repeatability of the procedures and its high accuracy.

Technological advancements are allowing the development of smart sensing devices with extremely low energy requirements. An emerging trend is the powering of smart sensors with energy harvested from the operating environment. Simultaneously, the task performed by a sensing node can be performed by a microprocessor with low computational resources. Energy demand of the devices is also decreasing by the adoption of advanced operating methods and energy management strategies. For devices to interoperate efficiently together, the design and operation need to follow standardization methods.

Advanced Metering Infrastructure (AMI) today represents the backbone of Smart City intended as urban area where the most of public services are smart. Smart devices allow cities to be smart, enabling communication also among things and creating a new system nowadays known as IoT (Internet of Things). In particular the smarter the meters, the smarter the City, but the concept of smartness is not univocal. In urban area, smart meters must be accessible, collaborative and accurate. The paper faces this topic, mainly with reference to power measurements and wireless networks. In particular, it describes an innovative solution for electrical power, gas and water metering integration in the same infrastructure. Then it describes metrics and hardware details of a smart electrical power meter and, finally it shows the experimental results of the smart meter metrological characterization.

Semi-active suspension control is able to regulate the damping forces by measuring the relative velocity of the wheels respect to the vehicle body. The adoption of linear potentiometers (the most used sensors in racing for linearity and simplicity) reveals to be expensive for mass market and unreliable in the long run. The paper deals with the validation of a soft sensor for the online estimation of the suspension velocity from acceleration signals. Main features of the soft sensor implementation according to different approaches (based on time-domain integration and Artificial Neural Networks respectively) are discussed with reference to the typical requirements for the real-time prediction of the suspension velocity.

Smart cities and smart homes are driving economic growth and improving the quality of people's life by enabling local development and harnessing technologies, especially the ones leading to smart outcomes and connectivity. Application of smart solutions will enable human living environments to use technology, information and data to improve infrastructures and services in the behalf of human beings. The welfare of elderly people living alone, at their homes, or, in rest houses, can significantly be improved with the introduction of these smart solutions. Wireless indoor tracking of elderly people is an important feature together with the DLMS/COSEM protocol. Above all using low power devices to assist and monitoring them. The paper highlights implementation in the real world, proposing a method that can be suited in a large range of cases thanks to the scene analysis. An indoor scalable infrastructure allows the tracking method to be implemented incrementally with different performances, where optimal accuracy comes from an adaptable threshold. The method has been tested in different environments using both simulations and direct measurements. Result from the proposed method are compared with the KNN method.

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.