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Aquest projecte té com objectiu principal la generació eficient del corrent elèctric a travès d'un sistema integrat composat per un electrolitzador i una pila de combustible. La clau d'aquest procès rau en la descomposició de l'aigua, on l'electrolitzador realitza la separació de l'oxígen i hidrogen i la pila de combustible utilitza aquest elements per portar a cau reaccions de reducció y oxidació, generant d'aquesta manera energía elèctrica de manera sostenible. L'eficiència de tot al sistema es maximitza mitjançant l'implementació d'un sistema de monitorització constant. Aquest control exhaustiu es porta a cau mitjançant una xarxa de sensors estratègicament ubicats, actuadors i altres components electrònics. La interconnexió de aquests elements s'aconsegueix fent ús d'un microcontrolador i tecnología IoT, permetent un control precís i en temps real de cada component del sistema. El disseny d'aquest projecte ha estat meticulòs, abarcant des de la selecció i estudi detallat dels sensors i actuadors incloent la comprensió profunda de las propietats de l'hidrogen i el funcionament intrínsec de las pilas de combustible i l'electrolitzador. A més, s'ha dut a terme el disseny d'una placa electrònica PCB que compacta tots aquests elements a un espai reduït, garantizant que cada component compleix una funció essencial pel correcte funcionament del sistema. Un cop implementat, el sistema recopila dades continues a travès del sistema de control. Aquestes dades son sotmeses a un anàlisis per avaluar la eficiència del sistema en termes de generació d'energia. Aquesta perspectiva analítica, no només permet verificar la funcionalitat del sistema, sinó que també proporciona informació per possibles milloras del projecte. En resum, aquest projecte no només cerca generar energia de manera sostenible, sinó que també garantitzar un control eficient i ajudar a la millora en l'implementació d'aquesta tecnología., Este proyecto tiene como objetivo principal la generación eficiente de corriente eléctrica a través de un sistema integrado compuesto por un electrolizador y una pila de combustible. La clave de este proceso radica en la descomposición del agua, donde el electrolizador realiza la separación del oxígeno e hidrógeno, y la pila de combustible utiliza estos elementos para llevar a cabo reacciones de reducción y oxidación, generando así energía eléctrica de manera sostenible. La eficiencia de todo el sistema se maximiza mediante la implementación de un sistema de monitorización constante. Este control exhaustivo se lleva a cabo mediante una red de sensores estratégicamente ubicados, actuadores y otros componentes electrónicos. La interconexión de estos elementos se logra mediante un microcontrolador y tecnología IoT, permitiendo un control preciso y en tiempo real de cada componente del sistema. El diseño de este proyecto ha sido meticuloso, abarcando desde la selección y estudio detallado de los sensores y actuadores hasta la comprensión profunda de las propiedades del hidrógeno y el funcionamiento intrínseco de las pilas de combustible y el electrolizador. Además, se ha llevado a cabo el diseño de una placa electrónica PCB que compacta todos estos elementos en un espacio reducido, garantizando que cada componente cumpla una función esencial para el correcto funcionamiento del sistema. Una vez implementado, el sistema recopila datos continuos a través del sistema de control. Estos datos son sometidos a análisis para evaluar la eficiencia del sistema en términos de generación de energía. Este enfoque analítico no solo permite verificar la funcionalidad del sistema, sino también proporciona información para posibles mejoras del proyecto. En resumen, este proyecto no solo busca generar energía de manera sostenible, sino también garantizar un control eficiente y ayudar a la mejora en la implementación de esta tecnología., This project aims to efficiently generate electrical current through an integrated system consisting of an electrolyzer and a fuel cell. The key to this process lies in the decomposition of water, where the electrolyzer separates it into oxygen and hydrogen, and the fuel cell utilizes these elements to undergo reduction and oxidation reactions, thereby generating electrical energy sustainably. The efficiency of the entire system is maximized through the implementation of a continuous monitoring system. This thorough control is carried out using a network of strategically placed sensors, actuators, and other crucial electronic components. The interconnection of these elements is achieved through a microcontroller and IoT technology, enabling precise and real-time control of each component of the system. The design of this project has been meticulous, covering everything from the selection and detailed study of sensors and actuators to a deep understanding of the properties of hydrogen and the intrinsic functioning of fuel cells and electrolyzers. Additionally, the design of a PCB electronic board has been executed, compacting all these elements into a confined space, ensuring that each component serves an essential function for the proper operation of the system. Once implemented, the system collects continuous data through the control system. These data are subjected to analysis to evaluate the efficiency of the system in terms of energy generation. This analytical approach not only verifies the functionality of the system but also provides insights for potential improvements to the project. In summary, this project not only aims to generate energy sustainably but also to ensure efficient control and contribute to the continuous improvement in the implementation of this technology.

This is a detailed paper on the design and implementation of a smart farming system using STM32 microcontrollers and some sensors such as for temperature and humidity, CO2 concentration, soil moisture and light sensors. It focuses on improving crop growing efficiency through automation and intelligent management of greenhouse environment. The system collects environmental parameters and displays them in real time on a display screen or a mobile app for automatic regulation and remote control. This innovative approach aims to improve agricultural productivity by integrating advanced sensor technologies, data collection and control mechanisms. The software used for program writing and designing is Keil 5. The hardware and software design aspects of the system were continuously improved after referring to a large number of literary sources, including circuit design, programming. I conducted software and hardware tests,the experimental results were in accordance with the design requirements. The significance of this work is that it revolutionizes the traditional farming methods by introducing precision farming and smart greenhouse management. With the development of science ,technology and intelligence, in recent years, more and more intelligent systems have been applied to daily life. Agricultural intelligence is an emerging industry, how to effectively improve the cultivation efficiency of crops, efficient use of crop growth period, greenhouse environment detection and regulation has become the most critical part of the market there are many intelligent machines that can help improve the efficiency of plant cultivation. However, most of the key elements such as environmental monitoring, automatic processing, timely alarms and remote control are not perfectly combined together, and can only achieve simple functions. Therefore, it is particularly important to design an intelligent agricultural system that combines single-chip microcomputer technology, sensor technology

Diabetes is a global pandemic that increases the risk of various health complications, including heart attacks, renal failure, blindness, stroke, and peripheral neuropathy. Type-2 diabetes (T2D) results from an imbalance in lipid and glucose metabolism due to hostility to insulin action and insufficient insulin production response. Valine amino acid has been identified as a potential biomarker for T2D, but there have been no rigorous studies on its interaction with branch chain amino acids. In this study, we investigated the potential of graphene/modified graphene as a valine biosensor using density functional theory to examine the electronic properties and adsorption behaviour of graphene, Si-doped graphene (SiG), and P-doped graphene (PG). The adsorption of valine over the substrates was physisorption in nature, and the adsorption energies were in the order of SiG > G > PG. Density of states (DOS) and partial DOS calculations confirmed the molecule's adsorption over the monolayers and indicated variations in the electronic properties. We also performed recovery time calculations to examine the reusability of the nano-surfaces as potential biosensors. Ultrafast recovery times were predicted for all three systems, with SiG showing the best results. Our study suggests that SiG could be used as a biosensor for valine, providing a real-time and efficient diagnostic tool for T2D.

The rapid advancement of technology over the past decade has resulted in significant transformations within the photography sector. In photographic processes, photosensitive materials are used by photographers to convert latent images into visible ones. Among other photographic developers, Metol has been used as a monochrome photographic chemical for more than 100 years in Europe. Metol (MTL), chemically N-methyl-p-aminophenol sulphate with formula [HOC6H4NH2(CH3)]2SO4, is also used as a corrosion inhibitor, antioxidant, and antimicrobial, and it serves as an intermediary for the medication diloxanide and dyes for fur and hair [1]. Since it is used in the photographic industry, it is released into the water, contaminating ground, and household water. It can be easily found in different water bodies such as rivers, lakes, ponds, and seas. MTL was found to be a cancerogenic organic pollutant with a significant impact on human health, the environment, animals, plants, and water sources [2]. MTL is non-biodegradable and can accumulate in biotic organisms. It is also related to numerous environmental issues, even in low concentrations. Nevertheless, a larger dose of MTL is necessary to have a substantial effect on several health problems, such as cancer, irritable eyes, slowed heartbeat, skin allergies, and harm to the body's internal blood supply [3]. Therefore, developing a straightforward, quick, affordable, sensitive, and practical method for ML detection in aquatic bodies is imperative. In this study, a susceptible and selective sensor for the detection and quantification of nitrogen-organic pollutant Metol (MTL) was developed. For this purpose, samarium-molybdate (Sm2(MoO4)3 nanoparticles were synthesized by organic solvent-free, eco-friendly, low-cost hydrothermal method and used as an excellent modifier with high catalytic efficiency for implementation into the carbon paste. Electrochemical measurements indicate that the developed electrode facilitates electron t

This work implements a drip irrigation system using NPK sensors, which is suitable for measuring temperature, humidity, conductivity, and soil PH, and also detects the nitrogen, phosphorus, and potassium content in the soil. This system will allow monitoring the appropriate use of water to apply it to a soybean crop of four genotypes based on dry matter; With this data obtained from the sensors it will be displayed in a web application to be analyzed in real time during field tests., El presente trabajo realiza la implementación de un sistema de riego por goteo utilizando sensores NPK, el cual es adecuado para medir la temperatura, humedad, conductividad, el PH del suelo, asimismo detecta el contenido de nitrógeno, fosforo y potasio en el suelo. Este sistema permitirá monitorear el uso adecuado del agua para aplicarlo en un cultivo de soya de cuatro genotipos basado en materia seca; con estos datos obtenidos de los sensores se mostrará en una aplicación web para estar analizando en tiempo real durante las pruebas de campo.

Dehydration is a phenomenon that occurs when the human body loses more fluids than it ingests, which has negative effects on health, and symptoms such as fatigue, dizziness, decreased cognitive function, and even fainting begin to appear. Dehydration can occur in various situations, such as intense physical activities, extreme weather conditions, illnesses, or during aging. In this current project, the objective is the creation of a dehydration sensor through the thermal conductivity of the skin (EDA), which can be measured through skin conductivity data; as skin conductivity is an inverse measure of skin resistance, it therefore describes a proportional response and will be subject to the amount of sweat secretion, thus driving the measurement process., La deshidratación es un fenómeno que ocurre cuando el cuerpo humano pierde más líquidos de los mareos, disminución de la función cognitiva e incluso desmayos. La deshidratación puede ocurrir en diversas situaciones, como actividades físicas intensas, condiciones climáticas extremas, enfermedades o durante el envejecimiento. En este presente proyecto, tiene como objetivo la creación de un sensor de deshidratación por medio de la conductividad térmica de la piel (EDA), la cual se puede medir a través de los datos de dicha conductividad de la piel, y dado que es una medida inversa a la resistencia de la piel, se puede percibir una respuesta proporcional, y esta está sujeta a la cantidad secreción de sudor, de esta manera permite llevar el proceso de la medición de deshidratación.que ingiere, lo cual tiene efectos negativos en la salud, y empiezan a aparecer síntomas como fatiga.

Biomarkers are measurable indicators of disease states or health conditions of an individual. Cellular and subcellular biomarkers offer insights for disease progression and therapeutic response. Traditional methods for biomarker detection, such as reverse transcription polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and mass spectrometry, are proven to be effective but often require complex procedures and extensive sample preparation.To overcome such limitations, this dissertation focuses on two innovative biosensing approaches: deformation-based microfluidic devices for cellular-level diagnosis and photonic sensors for subcellular-level diagnosis. Deformation-based microfluidic devices leverage principles of mechanical filtration, inertial microfluidics, and deterministic lateral displacement to sort cells based on their deformability. A novel microfluidic device featuring a flow-focusing channel with a cylindrical post is proposed to address challenges in current deformation-based sorting methods. On the other hand, photonic sensors offer label-free detection with high sensitivity and multiplexing capabilities. Specifically, ring resonator biosensors are highlighted for their compact size and sensitivity comparable to conventional methods. This dissertation presents design, fabrication, and characterization of integrated ring-assisted Mach-Zehnder interferometer (RA-MZI) biosensor with microfluidic channel. Such RA-MZI sensor offers high signal-to-noise ratio, sensitivity, and capability to detect optical changes in a larger dynamic range. Additionally, by integrating microfluidics, sample volume can be minimized. This dissertation research lays the groundwork for the development of point-of-care platform. By sequentially connecting the deformation-based droplet separation microfluidic device with the RA-MZI photonic sensor, a single system can be created which can be used for purification and detection of desired subcellular biomark

El present treball té com a objectiu dotar de recursos al professorat de tecnologia per poder donar compliment al nou Decret d'Educació pel que fa a l'ensenyament de la programació i la robòtica als instituts de Catalunya. S'utilitzarà la marca LEGO per familiaritzar als estudiants en uns camps molt concrets de la tecnologia, com els engranatges, els sensors i els actuadors, analitzant les seves característiques i possibilitats. Al mateix temps s'iniciarà als estudiants en el món de la programació per blocs, que en aquest cas tindrà la finalitat de controlar els mecanismes construïts. Es proposaran diverses situacions d'aprenentatge en què s'utilitzaran els diferents components analitzats, de manera que els estudiants puguin relacionar el component teòric de l'aprenentatge amb una part pràctica on experimentaran el funcionament real dels mecanismes treballats. S'aposta per l'ús de material de la marca LEGO per dos motius: en primer lloc, la seva divisió LEGO Education disposa de sets molt específics i complets per l'ensenyament, fet que fa molt fàcil el treball amb el seu material a l'aula. En segon lloc, fer servir una marca tan coneguda pel seu vessant lúdic la converteix en una metodologia estimulant pels alumnes.

Vivim en una era on la tecnologia ha transformat radicalment la nostra manera de viure i d'interactuar amb l’entorn. El que fa només uns anys semblava impensable, avui és una realitat quotidiana. Estem envoltats de dispositius tecnològics, des de petits robots aspiradors fins a telèfons mòbils que funcionen com ordinadors, equipats amb una gran varietat de sensors com GPS, acceleròmetres, giroscopis o magnetòmetres. En aquest món cada vegada més automatitzat, s’ha tornat imprescindible aprendre i comprendre l´ús i el maneig d'aquestes tecnologies. L'educació, tant formal com autodidacta, juga un paper crucial en aquest aprenentatge. Aquest Treball de Fi de Grau tracta sobre el disseny i implementació d'una estació de treball dedicada a la robòtica educativa fent servir la plataforma Arduino. L'estació intenta abastar totes les possibilitats que ens brinda el món de la robòtica actual incloent des d’una gran varietat de sensors i actuadors fins a un braç robòtic i un robot mòbil a més a més de microcontroladors com l'Arduino UNO i la placa ZUM Core de BQ. L'objectiu és proporcionar una experiència pràctica i accessible en robòtica, electrònica i programació, adequada per a tot tipus de públic amb diferents nivells de coneixements. Mitjançant una sèrie d'activitats dissenyades per fomentar l'interès i les habilitats en robòtica, aquest projecte pretén acostar aquestes tecnologies de manera interactiva i estimulant, permetent als usuaris aprendre i experimentar de forma pràctica i divertida., We live in an era where technology has radically transformed our way of life and interaction with the environment. What seemed unimaginable only a few years ago is now a daily reality. We are surrounded by technological devices, from small robotic vacuum cleaners to mobile phones that function as computers, equipped with a wide variety of sensors such as GPS, accelerometers, gyroscopes, and magnetometers. In this increasingly automated world, it has become essential to learn and understand the use and management of these technologies. Education, both formal and self-taught, plays a crucial role in this learning process. This end-of-degree project focuses on the design and implementation of a workstation dedicated to educational robotics using the Arduino platform. The workstation aims to encompass all the possibilities offered by the current world of robotics, including a wide variety of sensors and actuators, a robotic arm, and a mobile robot. Additionally, it includes microcontrollers such as the Arduino Uno and the ZUM Core board from BQ. The objective is to provide a practical and accessible experience in robotics, electronics, and programming, suitable for all types of audiences with different levels of knowledge. Through a series of activities designed to foster interest and skills in robotics, this project aims to bring these technologies closer in an interactive and stimulating way, allowing users to learn and experiment practically and enjoyably.

This paper studies the conductivity and chemiresistive H2S gas sensitivity of graphene(75wt%)-Cu(25wt%) composite thin film, using self-made chamber and common laboratory apparatus. The method adopted involves mixture of 2 drops of ethanol with the synthesized composite and prepared on a glass substrate by tape casting method. Two small copper metal sheets were used as electrodes for clipping of crocodile which were also connected to digital meter for resistance readings and its changes. The X-ray Diffraction (XRD) shows that annealing temperature reduced the crystallite sizes. The Fourier Transform Infrared Radiation (FTIR) spectra show the functional groups present to be transition metal carbonyls or aromatic combination bands, terminal alkyne (monosubstituted), isothiocyanate and that between 2300 and 2400 cm-1 indicates N=C=S functional group and evidence of CO2 interaction with external surface of the material or intercalating in the interlayer of the host material Also, increase in the conductivity was observed due to decrease in resistivity. The response/sensitivity peak of the sensor to hydrogen sulfide was seen to rise proportionally as temperature rose with percentage 3.97% for as grown, annealed at 200°C is at 12.98% while the annealed at 400°C is at 27.34%.

To prevent postharvest losses, optimal fruit temperatures should be maintained. However, non-uniform hygrothermal conditions and hotspots can develop due to the dense stacking of the fruit inside refrigerated trailers. The question remains when and where they arise. In commercial shipments, only the air temperature at the back of the trailer is typically monitored. However, it is still unknown how this temperature relates to fruit temperatures within the cargo. This study experimentally measured air and fruit temperatures for citrus fruit transported from Greece to Switzerland within a commercial supply chain. 108 sensors were placed inside one shipment to map air and fruit temperature gradients and identify hotspots during precooling and transport. Besides, air and fruit temperatures were measured at the back of the trailer within 30 additional shipments to analyze the variations between different transports. The results showed insufficient precooling (room precooling), as not all fruit reached the required setpoint temperature (4–6 °C) after 24 h of precooling. Although most of the field heat was removed during precooling, re-heating (>10 °C) of some fruit in the middle of the trailer was observed due to insufficient ventilation of the pallets. Finally, different shipments showed varying air temperatures (average interquartile range: 1.5 °C), where significant variations were observed between different shipments (up to 9 °C difference between the average temperatures) and where the measured air temperatures deviated from the setpoint. The results of this full-scale experiment indicate the importance of monitoring commercial supply chains to better understand transport processes within refrigerated trailers and prevent fruit losses.

La acústica submarina es crucial para entender el entorno marino y la vida acuática. Recientes estudios revelan que los peces son particularmente sensibles al movimiento de partículas en el agua, abarcando desplazamiento, velocidad y aceleración, más que a la presión sonora, especialmente en condiciones de campo cercano debido a las propiedades vectoriales del movimiento de partículas. Esta sensibilidad destaca la necesidad de evaluar cómo el ruido antropogénico, generado por actividades humanas como el tráfico marítimo y la exploración petrolera, afecta a la vida marina. Este tipo de ruido perjudica la comunicación, reproducción y supervivencia de las especies marinas. El estudio se centra en el desplazamiento de partículas generadas por fuentes sonoras submarinas y su relación con la presión sonora. Desarrollar sensores que midan este desplazamiento es esencial para comprender cómo las partículas se mueven en respuesta a ondas de presión en el entorno submarino. Esta investigación es vital para entender los efectos del ruido submarino en las especies y contribuir a su conservación. Con estos conocimientos, se pueden crear estrategias de mitigación para proteger la vida y los ecosistemas submarinos.

Due to impacts and constant stress, the leading edges of aircraft engine blades often lose their shape, while the other parts of the blade are still functional. This results in unnecessary performance losses. Currently, there is no method for a fast and effective repair process as the initial shape of the blade cannot be restored. This paper presents an automated re-contouring process chain for leading edges without prior material application. Thus, it is a sustainable approach to extend the lifespan until an energy-consuming welding process can be performed. It consists of an in-machine scanning process to obtain information about the worn shape, a subsequent target model generation based on the worn shape, and an automated process planning. The process chain is evaluated using a universal, leading edge workpiece. The results show that the target requirements for shape and smoothness are fulfilled.

The Internet of Things (IoT) is a technology that connects everyday objects to the Internet, allowing them to send and receive data. This technology is becoming more common in many areas like smart homes, factories, and healthcare, enhancing operational efficiency and ena-bling real-time monitoring.This project focused on developing a smart home system utilizing IoT. Microcontroller and sensors were employed to better manage home environments. Temperature and humidity sensor with a fan were connected to control ventilation, ensuring the air remains comfortable. Additionally, a gas sensor with a buzzer was installed to quickly alert to any potential leaks, increasing safety. The system allows for remote monitoring and control of home environments through real-time data displayed on an LCD screen and online on the ThingSpeak platform. This demon-strates how IoT can simplify home management and enhance safety with minimal human intervention. The project successfully showed that these systems are effective and highlighted their potential benefits in everyday life, setting the stage for future innovation in smart home technology., Poängen är 21 HP

Detta projekt demonstrerar grundläggande principer inom reglerteknik genom konstruktionen och implementeringen av en självbalanserande kub. Kuben använder tre reaktionshjul fästa vid elektriska motorer, en omborddator med en PID-regulator och en gyroskopisk sensor för att övervaka och justera sitt tillstånd för stabilitet. Trots utmaningar med externa störningar och att balansera på ett hörn, samt mindre problem under projektets gång, uppnåddes projektmålen och kuben klarar av att självbalansera på kanter och hörn.

The escalating issue of air pollution, particularly the presence of fine particulate matter (PM2.5), which can lead to serious health conditions, requires innovative solutions for effective monitoring and management. This thesis serves as a proof of concept system aimed at advancing air quality monitoring by researching the potential of Digital Twin (DT) technology. While not implementing a full-scale DT, the study lays the groundwork for future implementation. The system uses real-time sensor data to deliver live updates on various air quality parameters. Initially, the thesis attempted a Narrowband-Internet of Things (NB-IoT) solution but ended up with a different approach. Sensors are connected through 4G cellular networks to a cloud-based platform for data storage. This allows researchers to visualize the data and analyze current air quality conditions. This study presents the vision of an operational DT system, showcasing the feasibility of its components. The proof of concept focuses on implementing sensor nodes and data transmission, demonstrating how the system can optimize the process of collecting and visualizing air quality data. Results aim to support future developers in refining air quality measurement methodologies and contributing to healthier urban environments. This thesis emphasizes the importance of integrating advanced technologies such as Internet of Things (IoT) and cloud computing in environmental monitoring. It presents a scalable solution adaptable to the evolving needs of smart cities.

Overcrowding during indoor events can be risky, in-case of any kind of a hazard such as fire.This solution address this by providing real-time crowd detection solution using Force-SensingResistor (FSR) sensors, referred sensor (IR) and microcontrollers. The solution needs to offer accurate data in real-time to the event managers including number of people and entrancerate to help when and if the event areas will be overcrowded, thereby enhancing event safetyand decision-making. This thesis indicate that the system offers essential real-time data forevent safety with an accuracy of 87.25%. These data will assists event managers in makinginformed decisions to avoid the risks of overcrowding. This thesis evaluates the effectivenessof our system in comparison to other systems, discussing what we’ve learned, suggest possibleimprovements, and talk about whether our system could be useful in real-world indoor events.

This thesis investigates time synchronization, which is crucial in various applications, such as power grid monitoring, communication systems, and in the fusion of information from different sensors. Global Navigation Satellite Systems (GNSS) are currently the state-of-the-art for time synchronization in distributed wireless sensor networks. However, due to GNSS being vulnerable to jamming, alternative methods are required to ensure robustness in critical systems. Preferably, a system would not be controlled by a single country or organization, e.g., GPS. Therefore, time synchronization methods utilizing commonly available signals, such as radio or television broadcasting, are of interest. Long Term Evolution (LTE), the fourth-generation (4G) cellular network, is widely accessible and the framework is internationally standardized. Consequently, the scope of the thesis is limited to LTE-based methods for time synchronization. Based on the desired receiver-to-receiver characteristics, Scalable Wireless Network Synchronization (SWINS) and Reference Broadcast Synchronization (RBS) were selected to obtain time synchronization. RBS is an active synchronization method requiring communication within the sensor network, while the passive SWINS method solely relies on self-captured measurements. Time synchronization performance was evaluated using Matlab. Simulations show an increased accuracy for SWINS in synchronized LTE networks, while RBS is superior in unsynchronized cellular networks. Both LTE-based methods show performance comparable to the time synchronization accuracy guaranteed with publicly available GPS signals. A sensitivity analysis with varying disturbances shows that jointly estimating time offset and position is preferred to sole time offset estimation if the transceiver position uncertainty exceeds 50 meters.

In the fast-paced and time-sensitive fields of construction and concrete production, real-time monitoring of concrete strength is crucial. Traditional testing methods, such as hydraulic compression (ASTM C 39) and maturity methods (ASTM C 1074), are often laborious and challenging to implement on-site. Building on prior research (SPR 4210 and SPR 4513), we have advanced the electromechanical impedance (EMI) technique for in-situ concrete strength monitoring, crucial for determining safe traffic opening times. These projects have made significant strides in technology, including the development of an IoT-based hardware system for wireless data collection and a cloud-based platform for efficient data processing. A key innovation is the integration of machine learning tools, which not only enhance immediate strength predictions but also facilitate long-term projections vital for maintenance and asset management. To bring this technology to practical use, we collaborated with third-party manufacturers to set up a production line for the sensor and datalogger assembly. The system was extensively tested in various field scenarios, including pavements, patches, and bridge decks. Our refined signal processing algorithms, benchmarked against a mean absolute percentage error (MAPE) of 16%, which is comparable to the ASTM C39 interlaboratory variance of 14%, demonstrate reliable accuracy. Additionally, we have developed a comprehensive user manual to aid field engineers in deploying, connecting, and maintaining the sensing system, paving the way for broader implementation in real-world construction settings.

[Resumen]: Los vehículos aéreos no tripulados (UAVs) se utilizan en una gran variedad de ámbitos, tanto militares como civiles. Algunos ejemplos de uso son la vigilancia y seguridad en fronteras, la inspección de infraestructuras críticas (tendidos eléctricos, oleoductos…), la búsqueda de supervivientes, el monitoreo o riego de cultivos, la entrega de paquetes y suministros en zonas de difícil acceso y la grabación para la industria del entretenimiento, entre otros. Para conocer el estado en el que se encuentra el UAV, se utilizan varios sensores, los cuales están sometidos a múltiples fuentes de ruido, lo que puede hacer que se estime una trayectoria que difiere de la trayectoria real. En todas las aplicaciones mencionadas, garantizar un seguimiento preciso y en tiempo real de la trayectoria del UAV es fundamental para maximizar la eficacia de la tarea realizada y la seguridad en la operación. Con este objetivo, en este proyecto se aborda el problema del seguimiento de la trayectoria de un UAV que presenta sensores sometidos a ruido. Para ello, se obtienen las coordenadas y la altitud de un UAV durante diferentes vuelos, utilizando un módulo GPS y un altímetro barométrico. Utilizando estos datos, que contienen un cierto nivel de ruido, se implementa y se prueba el rendimiento tanto del filtro de Kalman como de las redes neuronales recurrentes en la estimación de las trayectorias reales del UAV, realizando también una comparación entre ambos enfoques, de tal forma que se identifiquen las fortalezas y limitaciones de cada técnica., [Abstract]: Unmanned Aerial Vehicles (UAVs) are used in a wide variety of areas, both military and civilian. Some examples of UAV uses are surveillance and security at borders, inspection of critical infrastructure (power lines, pipelines…), search for survivors, monitoring or irrigation of crops, delivery of packages and supplies in hard-to-reach areas, recording for the entertainment industry, etc. To know the state of the UAV, various sensors are used, which are subject to multiple sources of noise. This fact can lead to an estimated trajectory that differs from the actual trajectory. In all the mentioned applications, ensuring accurate and real-time tracking of the UAV’s trajectory is essential to maximize the effectiveness of the performed task and safety in operation.With this objective, this project addresses the problem of tracking the trajectory of a UAV that presents sensors subject to noise. To do this, the coordinates and altitude of a UAV are obtained during different flights by using a GPS module and a barometric altimeter. Using these data, which contain a certain level of noise, the performance of both the Kalman filter and recurrent neural networks is tested in the estimation of the UAV’s actual trajectories, also making a comparison between both approaches, so that the strengths and limitations of each technique are identified.

In climate and oceanographic research, precise temperature measurements within the very limited temperature range of the ocean are essential. This paper covers the design and analysis of a temperature sensor that measures with millikelvin accuracy. The first prototype has an energy consumption of 84.64 mWs with a sampling time of 10 seconds per measurement and a component cost of less than 100 EUR. The proposed design is able to measure within 6 mK accuracy on a subset measurement range despite a simple three-point calibration. The core circuit is enhanced with two temperature sensing elements to allow for an increase in sensor sensitivity. A further approach on sensor readout is proposed and analyzed, showing good potential in combination with linearized temperature compensation for the major part of this sensors range.

The everlasting pursuit of process miniaturization causes inherent security vulnerabilities, as the increasing complexity of Integrated Circuit (IC) manufacturing forces companies to outsource production, exposing ICs to unauthorized modifications, commonly referred to as Hardware Trojans (HTs). The outsourcing allows adversaries to gather detailed IC information, which may be leveraged for malicious intents using HTs. An additional side-effect of process miniaturization is increasing Process Variation (PV) levels, creating non-deterministic attributes in modern ICs technologies, allowing the concealment of HTs. While numerous successful HT detection techniques utilizing Side-Channel Analysis (SCA) and on-chip temperature sensors have been proposed in contemporary research, such methods often assume the complete integrity of sensor data, rendering them susceptible to HTs manipulating the data used in detection decisions. Recent research has introduced a HT that manipulates temperature sensor data, potentially enabling the launch of Performance Degradation (PD) attacks. However, this study overlooks PV and sensor noise, limiting opportunities to mask HT behavior. This thesis explores the security implications of aggressive process miniaturization by attempting to mask HT attacks within the inherited side-effects. To explore this theory, two proposed HTs are designed and simulated using Core and Memory interval Thermal (CoMeT), demonstrating a 63%-73% PD while remaining indistinguishable from Trojan Free (TF) ICs across multiple HT detection methods.

Light Detection and Ranging (Lidar) is a kind of active sensor that emits a laser pulse and primarily measures the time of flight of the returning pulse and uses it to construct a 3D point cloud of the scene around the lidar sensor. The constructed point cloud is an essential asset for the control of autonomous vehicles, and especially today, an essential basis for the training of autonomous vehicle control models. However, it remains time-consuming, high-risk and expensive to acquire the amounts of data necessary to train the rather complex modern control models. As such, generating the point cloud through simulations becomes a natural solution. Yet, many lidar simulations today produce ideal point clouds, corrected only by random noise, without considering the physical reasons behind the imperfections visible in real lidar point clouds. The aim of this study was to investigate real-time simulation models for disturbances that may cause imperfections in lidar data. From a base investigation of lidar, disturbances were found, models were investigated and finally a real-time implementation of Atmospheric Effects and attenuation from Beam Divergence was evaluated. It was found that the implemented models could produce physically accurate lidar point placement while keeping the computational time low enough for real-time evaluation. However, to achieve correct separation of target hit rates under Atmospheric Effects, as high as 34% of the points had to be dropped. Additionally, the intensity of the return points could not be properly verified. From these results it can be concluded that, with additional verification and adjustment, the presented models can achieve good results for evaluation in real-time. The results of this study thus serve as a support for future developments of realistic real-time lidar simulations, for use in development of autonomous vehicle control models and implementation of digital twins.

This thesis is dedicated to exploring effective person counting using sensors, an important technology in areas such as space optimization. The main challenges in this field include issues with accuracy and reliability. The goal of this thesis is to explore and identify the most effective sensor type for counting individuals in a space. To address these problems, three main types of sensors were used: ultrasound, infrared, and laser. Each sensor was tested and the results show that ultrasound sensors generally had the highest reliability, although no sensor achieved complete accuracy. The study underscores the need for further development and the potential for combining technologies to enhance accuracy and reliability in person counting systems., Denna uppsats ägnas åt undersökning av effektiv personräkning med hjälp av sensorer, en viktig teknik inom områden såsom optimering av lokalanvändning. Huvudproblemen inom området inkluderar utmaningar med noggrannhet och pålitlighet. Målet med denna uppsats är att undersöka och identifiera den mest effektiva sensortypen för personräkning i en lokal. För att lösa dessa problem användes tre huvudtyper av sensorer: ultraljud, infraröd och laser. Varje sensor testades och resultaten visar att ultraljudssensorer överlag hade högst pålitlighet, även om ingen av sensorerna uppnådde fullständig noggrannhet. Studien understryker behovet av vidare utveckling och potentialen för att kombinera tekniker för att förbättra noggrannheten och tillförlitligheten i personräkningssystem.

Gilbert Prokop, B.Sc., in englischer Sprache, Masterarbeit Universität Innsbruck 2024

A styrene-butadiene-styrene co-polymer matrix nanocomposite filled with graphene nanoplatelets was studied to prepare chemiresistive volatile organic compounds (VOCs) room temperature sensors with considerable response and selectivity. Nanofiller concentration was estimated from the electrical conductivity percolation behaviour of the nanocomposite. Fabricated sensors provided selective relative responses to representative VOCs differing by orders of magnitude. Maximum observed average relative responses upon exposure to saturated vapours of the tested VOCs were ca. 23% for ethanol, 1600% for acetone, and the giant values were 9 × 106% for n-heptane and 10 × 106% for toluene. The insensitivity of the sensor to the direct saturated water vapour exposure was verified. Although high humidity decreases the sensor’s response, it paradoxically enhances the resolution between hydrocarbons and polar organics. The non-trivial sensing mechanism is explained using the Hansen solubility parameters (HSP), enabling a rational design of new sensors; thus, the HSP-based class of sensors is outlined.

DATIV is an open source, low cost, distributed, portable sensor system which incorporates cameras and particulate matter sensors (PMS). This system can employ multiple sensors simultaneously and can be remotely operated using a web based GUI.

Automation of aquaponics systems is key in increasing agricultural efficiency and productivity. A system considered an innovative method of sustainable food production that combines fish farming with agriculture simultaneously. The problem that often occurs is crop failure, due to the lack of technology that can monitor automatically, so that farmers experience losses as a result of fish and plant growth does not thrive, and problems in urban areas that require land for planting and fish farming due to limited land in urban areas. There is another problem with the lack of accurate timing and monitoring of water quality in aquaponics. The purpose of this research is to implement an IoT system in aquaponics that is connected to various sensors, such as Turbidity sensors, Water Level sensors, and RTC Modules. To monitor water quality conditions in tilapia habitat and accurate time measurement to provide fish feed automatically so as to improve fish health and growth and support better and consistent yields. The findings of this study show that the implementation of IoT systems in aquaponics can overcome environmental monitoring and control problems effectively. Using the integration of RTC modules, turbidity sensors, and water level sensors effectively improves the automation of aquaponics systems. This optimized system provides better monitoring of environmental conditions, reduces reliance on manual maintenance, and increases overall productivity. It helps increase tilapia growth and plant productivity in a modern aquaponics system. This research demonstrates the great potential of IoT technology in increasing efficiency and productivity in aquaponics aquaculture, so that it can push the fisheries sector towards a more advanced and competitive direction. So the main conclusion is expected that this automation can increase the productivity of ecosystem balance, and can face food security challenges and move towards more environmentally friendly solutions, towards effe

The document presents an innovative type of sensor that can be used to measure forces on aircraft control inceptors. The measures can be applied both to in-flight and on simulators and allow for measure not only the total force applied on the inceptor’s grip but also their distribution over the inceptor grip without altering the ergonomics of the input device. The sensor aims also to provide a reliable way to quantify the workload to which a pilot is subjected during specific mission task elements. The sensor working principle is based on an optical measure making it not sensible to typical temperature-drift problems that affect classical electro-mechanical systems. A prototype of the sensor embedded in the yoke of an aircraft flight simulator has been designed, built, and tested. The results of an experiment involving several experienced pilots to assess the workload will be reported.

Medical ultrasound is a powerful tool for diagnosis. However, conventional ultrasound devices suffer from operator dependency and do not allow long-term usage. Recent advances in wearable ultrasound technologies have demonstrated the potential for hands-free data acquisition, but technical barriers remain as these probes require wire connections, can lose track of moving targets, and create data-interpretation challenges. Here, I report a fully integrated autonomous wearable ultrasonic-system-on-patch (USoP). A miniaturized flexible control circuit is designed to interface with an ultrasound transducer array for signal pre-conditioning and wireless data communication. Machine learning is used to track moving tissue targets and assist the data interpretation. I demonstrate that the USoP allows continuous tracking of physiological signals from tissues as deep as 164 mm. On mobile subjects, the USoP can continuously monitor physiological signals, including central blood pressure, heart rate, and cardiac output, for as long as two hours. This result enables continuous autonomous surveillance of deep tissue signals toward internet-of-medical-things.

The Arduino-based RFID Door Lock Security System with Piezoelectric Sensor and GSM Module for Venezia Town Homes in Santa Maria, Bulacan, is a digital security lock that will help minimize the crime rate index and reduce homeowners' worries.   The researchers used a quantitative survey method with a purposive sampling technique, T-test, and Likert Scale. The information acquired came from the survey questionnaire, which was used to confirm the project's accuracy. The study utilized selected thirty-two (32) homeowners and three (3) security personnel of Venezia Townhomes. Thirty-five (35) respondents were chosen for the study.

In most comfort rooms in the country, they are sometimes seen as unclean, so they omit foul smells in their surroundings. Odour Detection with SMS Notification using Arduino in the Comfort Room of Bestlink College of the Philippines is a device that can alert or send an SMS to the cleaner if the room is unclean and causes harmful and odorous scent.  The researchers used surveys to gather data. Twenty respondents (10 students, five janitors, and five staff) participated in the study. The survey statement no. one (1) gets fifty-five per cent (55%) or 4.05 mean with verbal interpretation of frequently observed and statement no. two (2) gets the result of sixty per cent (60%) or 3.3 in mean with a verbal interpretation of sometimes observed that seeks to SOP no. three (3), which means that device can help to the utilities by alerting them in terms of immediate clean in the comfort room.  Air pollutants are mainly comprised of harmful gases. MQ-135 is a semiconductor base gas sensor capable of detecting such things as NH4, NH3, or ammonia that occur naturally and are produced by human activity. Bacteria found in the intestines can produce this and go through ambient air.  The researchers found that air pollution is increasing due to the number and monitoring of human activities, which is vital to the relaxation of some measures to control it. The study used a low-cost and low-power sensor to monitor the air quality and alert the utility personnel, especially in the comfort room of Bestlink College of the Philippines.

Confronting the challenge of biofilm resistance and widespread antimicrobial resistance (AMR), this study emphasizes the need for innovative monitoring methods and explores the potential of bacteriophages against bacterial biofilms. Traditional methods, like optical density (OD) measurements and confocal microscopy, crucial in studying biofilm–virus interactions, often lack real-time monitoring and early detection capabilities, especially for biofilm formation and low bacterial concentrations. Addressing these gaps, we developed a new real-time, label-free radiofrequency sensor for monitoring bacteria and biofilm growth. The sensor, an open-ended coaxial probe, offers enhanced monitoring of bacterial development stages. Tested on a biological model of bacteria and bacteriophages, our results indicate the limitations of traditional OD measurements, influenced by factors like sedimented cell fragments and biofilm formation on well walls. While confocal microscopy provides detailed 3D biofilm architecture, its real-time monitoring application is limited. Our novel approach using radio frequency measurements (300 MHz) overcomes these shortcomings. It facilitates a finer analysis of the dynamic interaction between bacterial populations and phages, detecting real-time subtle changes. This method reveals distinct phases and breakpoints in biofilm formation and virion interaction not captured by conventional techniques. This study underscores the sensor’s potential in detecting irregular viral activity and assessing the efficacy of anti-biofilm treatments, contributing significantly to the understanding of biofilm dynamics. This research is vital in developing effective monitoring tools, guiding therapeutic strategies, and combating AMR.