Principal Component Analysis Applied to Digital Pulse Shape Analysis for Isotope Discrimination.

Digital pulse shape analysis (DPSA) techniques are becoming increasingly important for the study of nuclear reactions since the development of fast digitizers. These techniques allow us to obtain the (A, Z) values of the reaction products impinging on the new generation solid-state detectors. In this paper, we present a computationally efficient method to discriminate isotopes with similar energy levels, with the aim of enabling the edge-computing paradigm in future field-programmable gate-array-based acquisition systems. The discrimination of isotope pairs with analogous energy levels has been a topic of interest in the literature, leading to various solutions based on statistical features or convolutional neural networks. Leveraging a valuable dataset obtained from experiments conducted by researchers in the FAZIA Collaboration at the CIME cyclotron in GANIL laboratories, we aim to establish a comparative analysis regarding selectivity and computational efficiency, as this dataset has been employed in several prior publications. Specifically, this work presents an approach to discriminate between pairs of isotopes with similar energies, namely, 12,13C, 36,40Ar, and 80,84Kr, using principal component analysis (PCA) for data preprocessing. Consequently, a linear and cubic machine learning (ML) support vector machine (SVM) classification model was trained and tested, achieving a high identification capability, especially in the cubic one. These results offer improved computational efficiency compared to the previously reported methodologies.

Aerial monitoring of atmospheric particulate matter produced by open-pit mining using low-cost airborne sensors.

Mining is an economic activity that entails the production and displacement of significant amounts of atmospheric particulate matter (PM) during operations involving intense earthcrushing or earthmoving. As high concentrations of PM may have adverse effects on human health, it is necessary to monitor and control the fugitive emissions of this pollutant. This paper presents an innovative methodology for the online monitoring of PM10 concentrations in air using a low-cost sensor (LCS, <300 USD) onboard an unmanned aerial vehicle. After comprehensive calibration, the LCS was horizontally flown over seven different areas of the large Riotinto copper mine (Huelva, Spain) at different heights to study the PM10 distribution at different longitudes and altitudes. The flights covered areas of zero activity, intense mining, drilling, ore loading, waste discharge, open stockpiling, and mineral processing. In the zero-activity area, the resuspension of PM10 was very low, with a weak wind speed (3.6 m/s). In the intense-mining area, unhealthy concentrations of PM10 (>51 µgPM10/m3) could be released, and the PM10 can reach surrounding populations through long-distance transport driven by several processes being performed simultaneously. Strong dilution was also observed at high altitudes (> 50 m). Mean concentrations were found to be 22-89 µgPM10/m3, with peaks ranging from 86 to 284 µgPM10/m3. This study demonstrates the potential applicability of airborne LCSs in the high-resolution online monitoring of PM in mining, thus supporting environmental managers during decision-making against fugitive emissions in a cost-effective manner.

Battery-Less Industrial Wireless Monitoring and Control System for Improved Operational Efficiency.

An industrial wireless monitoring and control system, capable of supporting energy-harvesting devices through smart sensing and network management, designed for improving electro-refinery performance by applying predictive maintenance, is presented. The system is self-powered from bus bars, and features wireless communication and easy-to-access information and alarms. With cell voltage and electrolyte temperature measurements, the system enables real-time cell performance discovery and early reaction to critical production or quality disturbances such as short-circuiting, flow blockages, or electrolyte temperature excursions. Field validation shows an increase in operational performance of 30% (reaching 97%) in the detection of short circuits, which, thanks to a neural network deployed, are detected, on average, 10.5 h earlier compared to the traditional methodology. The developed system is a sustainable IoT solution, being easy to maintain after its deployment, and providing benefits of improved control and operation, increased current efficiency, and decreased maintenance costs.

Controlled Electromagnetic Field Based Safety System for Handheld Circular Saw.

This paper presents the design of a safety system based on controlled electromagnetic field (CEMF) sensing technology to prevent accidents caused by power tools, especially related to handheld circular saws. The safety system creates an invisible protection bubble of electromagnetic field around the cutting edge. The system can provide early warning or critical warning when a person penetrates the safety bubble. This paper covers how the CEMF technology has been adapted to add value within this application where it needs to coexist with a difficult environment of metallic parts turning thousands of times per minute, strong vibrations, and different ranges of materials to be processed. The proposed contactless solution successfully detects the user, providing enough time for the power tool to totally stop its movement before touching and harming the user. This key property has required a careful optimization of the electromagnetic field generation, the design of a shield circuitry capable of operating properly in a large metal device, and the development of a multi-frame algorithm to address the stringent requirements related to the ability of the system to react to both very fast and very slow events. The feasibility of the system has been validated by a virtual testbench.

Secured Perimeter with Electromagnetic Detection and Tracking with Drone Embedded and Static Cameras.

Perimeter detection systems detect intruders penetrating protected areas, but modern solutions require the combination of smart detectors, information networks and controlling software to reduce false alarms and extend detection range. The current solutions available to secure a perimeter (infrared and motion sensors, fiber optics, cameras, radar, among others) have several problems, such as sensitivity to weather conditions or the high failure alarm rate that forces the need for human supervision. The system exposed in this paper overcomes these problems by combining a perimeter security system based on CEMF (control of electromagnetic fields) sensing technology, a set of video cameras that remain powered off except when an event has been detected. An autonomous drone is also informed where the event has been initially detected. Then, it flies through computer vision to follow the intruder for as long as they remain within the perimeter. This paper covers a detailed view of how all three components cooperate in harmony to protect a perimeter effectively, without having to worry about false alarms, blinding due to weather conditions, clearance areas, or privacy issues. The system also provides extra information of where the intruder is or has been, at all times, no matter whether they have become mixed up with more people or not during the attack.

Real-Time Wireless Platform for In Vivo Monitoring of Bone Regeneration.

For the monitoring of bone regeneration processes, the instrumentation of the fixation is an increasingly common technique to indirectly measure the evolution of bone formation instead of ex vivo measurements or traditional in vivo techniques, such as X-ray or visual review. A versatile instrumented external fixator capable of adapting to multiple bone regeneration processes was designed, as well as a wireless acquisition system for the data collection. The design and implementation of the overall architecture of such a system is described in this work, including the hardware, firmware, and mechanical components. The measurements are conditioned and subsequently sent to a PC via wireless communication to be in vivo displayed and analyzed using a developed real-time monitoring application. Moreover, a model for the in vivo estimation of the bone callus stiffness from collected data was defined. This model was validated in vitro using elastic springs, reporting promising results with respect to previous equipment, with average errors and uncertainties below 6.7% and 14.04%. The devices were also validated in vivo performing a bone lengthening treatment on a sheep metatarsus. The resulting system allowed the in vivo mechanical characterization of the bone callus during experimentation, providing a low-cost, simple, and highly reliable solution.

ITERL: A Wireless Adaptive System for Efficient Road Lighting.

This work presents the development and construction of an adaptive street lighting system that improves safety at intersections, which is the result of applying low-power Internet of Things (IoT) techniques to intelligent transportation systems. A set of wireless sensor nodes using the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard with additional internet protocol (IP) connectivity measures both ambient conditions and vehicle transit. These measurements are sent to a coordinator node that collects and passes them to a local controller, which then makes decisions leading to the streetlight being turned on and its illumination level controlled. Streetlights are autonomous, powered by photovoltaic energy, and wirelessly connected, achieving a high degree of energy efficiency. Relevant data are also sent to the highway conservation center, allowing it to maintain up-to-date information for the system, enabling preventive maintenance.

Low-Power Low-Cost Wireless Flood Sensor for Smart Home Systems.

This paper presents the design of a wireless flood sensor to detect the presence of water on home floors, providing early warning of water leaks. A wireless sensor network has been deployed to gather the measurements from the sensor nodes. A control central coordinates the network and processes the data. Users can remotely inquire for the presence of water, status of the batteries for a specific node, the type of liquid and information about its functionality and alarms, thanks to a proprietary software application. The alerts are also communicated to the user within the home through an audible siren. The designed device is optimized in terms of costs, ease of deployment and maintenance, thus making it widely acceptable to end users.

Compact Embedded Wireless Sensor-Based Monitoring of Concrete Curing.

This work presents the design, construction and testing of a new embedded sensor system for monitoring concrete curing. A specific mote has been implemented to withstand the aggressive environment without affecting the measured variables. The system also includes a real-time monitoring application operating from a remote computer placed in a central location. The testing was done in two phases: the first in the laboratory, to validate the functional requirements of the developed devices; and the second on civil works to evaluate the functional features of the devices, such as range, robustness and flexibility. The devices were successfully implemented resulting in a low cost, highly reliable, compact and non-destructive solution.

An Efficient Wireless Sensor Network for Industrial Monitoring and Control.

This paper presents the design of a wireless sensor network particularly designed for remote monitoring and control of industrial parameters. The article describes the network components, protocol and sensor deployment, aimed to accomplish industrial constraint and to assure reliability and low power consumption. A particular case of study is presented. The system consists of a base station, gas sensing nodes, a tree-based routing scheme for the wireless sensor nodes and a real-time monitoring application that operates from a remote computer and a mobile phone. The system assures that the industrial safety quality and the measurement and monitoring system achieves an efficient industrial monitoring operations. The robustness of the developed system and the security in the communications have been guaranteed both in hardware and software level. The system is flexible and can be adapted to different environments. The testing of the system confirms the feasibility of the proposed implementation and validates the functional requirements of the developed devices, the networking solution and the power consumption management.

A Smart Sensor for Defending against Clock Glitching Attacks on the I2C Protocol in Robotic Applications.

This paper presents a study about hardware attacking and clock signal vulnerability. It considers a particular type of attack on the clock signal in the I2C protocol, and proposes the design of a new sensor for detecting and defending against this type of perturbation. The analysis of the attack and the defense is validated by means of a configurable experimental platform that emulates a differential drive robot. A set of experimental results confirm the interest of the studied vulnerabilities and the efficiency of the proposed sensor in defending against this type of situation.

Low Power Wireless Smoke Alarm System in Home Fires.

A novel sensing device for fire detection in domestic environments is presented. The fire detector uses a combination of several sensors that not only detect smoke, but discriminate between different types of smoke. This feature avoids false alarms and warns of different situations. Power consumption is optimized both in terms of hardware and software, providing a high degree of autonomy of almost five years. Data gathered from the device are transmitted through a wireless communication to a base station. The low cost and compact design provides wide application prospects.

Design and implementation of a smart sensor for respiratory rate monitoring.

This work presents the design, development and implementation of a smart sensor to monitor the respiratory rate. This sensor is aimed at overcoming the drawbacks of other systems currently available in market, namely, devices that are costly, uncomfortable, difficult-to-install, provide low detection sensitivity, and little-to-null patient-to-patient calibration. The device is based on capacitive sensing by means of an LC oscillator. Experimental results show that the sensor meets the necessary requirements, making feasible the proposed monitoring system with the technology used.

Design and implementation of a new real-time frequency sensor used as hardware countermeasure.

A new digital countermeasure against attacks related to the clock frequency is presented. This countermeasure, known as frequency sensor, consists of a local oscillator, a transition detector, a measurement element and an output block. The countermeasure has been designed using a full-custom technique implemented in an Application-Specific Integrated Circuit (ASIC), and the implementation has been verified and characterized with an integrated design using a 0.35 mm standard Complementary Metal Oxide Semiconductor (CMOS) technology (Very Large Scale Implementation-VLSI implementation). The proposed solution is configurable in resolution time and allowed range of period, achieving a minimum resolution time of only 1.91 ns and an initialization time of 5.84 ns. The proposed VLSI implementation shows better results than other solutions, such as digital ones based on semi-custom techniques and analog ones based on band pass filters, all design parameters considered. Finally, a counter has been used to verify the good performance of the countermeasure in avoiding the success of an attack.