Characterization of a Piezoelectric Acoustic Sensor Fabricated for Low-Frequency Applications: A Comparative Study of Three Methods.

Piezoelectric transducers are widely used for generating acoustic energy, and choosing the right radiating element is crucial for efficient energy conversion. In recent decades, numerous studies have been conducted to characterize ceramics based on their elastic, dielectric, and electromechanical properties, which have improved our understanding of their vibrational behavior and aided in the manufacturing of piezoelectric transducers for ultrasonic applications. However, most of these studies have focused on the characterization of ceramics and transducers using electrical impedance to obtain resonance and anti-resonance frequencies. Few studies have explored other important quantities such as acoustic sensitivity using the direct comparison method. In this work, we present a comprehensive study that covers the design, manufacturing, and experimental validation of a small-sized, easy-to-assemble piezoelectric acoustic sensor for low-frequency applications, using a soft ceramic PIC255 from PI Ceramic with a diameter of 10 mm and a thickness of 5 mm. We present two methods, analytical and numerical, for sensor design, followed by experimental validation, allowing for a direct comparison of measurements with simulated results. This work provides a useful evaluation and characterization tool for future applications of ultrasonic measurement systems.

Smart Air Quality Monitoring IoT-Based Infrastructure for Industrial Environments.

Deficient air quality in industrial environments creates a number of problems that affect both the staff and the ecosystems of a particular area. To address this, periodic measurements must be taken to monitor the pollutant substances discharged into the atmosphere. However, the deployed system should also be adapted to the specific requirements of the industry. This paper presents a complete air quality monitoring infrastructure based on the IoT paradigm that is fully integrable into current industrial systems. It includes the development of two highly precise compact devices to facilitate real-time monitoring of particulate matter concentrations and polluting gases in the air. These devices are able to collect other information of interest, such as the temperature and humidity of the environment or the Global Positioning System (GPS) location of the device. Furthermore, machine learning techniques have been applied to the Big Data collected by this system. The results identify that the Gaussian Process Regression is the technique with the highest accuracy among the air quality data sets gathered by the devices. This provides our solution with, for instance, the intelligence to predict when safety levels might be surpassed.

An Analytical Approach to Flow-Guided Nanocommunication Networks.

Continuous progress of nanocommunications and nano-networking is opening the door to the development of innovative yet unimaginable services, with a special focus on medical applications. Among several nano-network topologies, flow-guided nanocommunication networks have recently emerged as a promising solution to monitoring, gathering information, and data communication inside the human body. In particular, flow-guided nano-networks display a number of specific characteristics, such as the type of nodes comprising the network or the ability of a nano-node to transmit successfully, which significantly differentiates them from other types of networks, both at the nano and larger scales. This paper presents the first analytical study on the behavior of these networks, with the objective of evaluating their metrics mathematically. To this end, a theoretical framework of the flow-guided nano-networks is developed and an analytical model derived. The main results reveal that, due to frame collisions, there is an optimal number of nano-nodes for any flow-guided network, which, as a consequence, limits the maximum achievable throughput. Finally, the analytical results obtained are validated through simulations and are further discussed.

Improving management performance of P2PSIP for mobile sensing in wireless overlays.

Future wireless communications are heading towards an all-Internet Protocol (all-IP) design, and will rely on the Session Initiation Protocol (SIP) to manage services, such as voice over IP (VoIP). The centralized architecture of traditional SIP has numerous disadvantages for mobile ad hoc services that may be possibly overcome by advanced peer-to-peer (P2P) technologies initially developed for the Internet. In the context of mobile sensing, P2PSIP protocols facilitate decentralized and fast communications with sensor-enabled terminals. Nevertheless, in order to make P2PSIP protocols feasible in mobile sensing networks, it is necessary to minimize overhead transmissions for signaling purposes, which reduces the battery lifetime. In this paper, we present a solution to improve the management of wireless overlay networks by defining an adaptive algorithm for the calculation of refresh time. The main advantage of the proposed algorithm is that it takes into account new parameters, such as the delay between nodes, and provides satisfactory performance and reliability levels at a much lower management overhead than previous approaches. The proposed solution can be applied to many structured P2P overlays or P2PSIP protocols. We evaluate it with Kademlia-based distributed hash tables (DHT) and dSIP.

On maximizing the lifetime of Wireless Sensor Networks by optimally assigning energy supplies.

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively.