Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

Cilj ovog istraživanja je procena različitih low-cost senzora za merenje visine leta bespilotne letelice sa više rotora na malim visinama. Primenjene su metode filtriranja podataka i druge metode u cilju optimizacije performansi i tačnosti merenja senzora. Izvšrena su merenja visine leta, a podaci su uskladišteni za kasniju analizu u odnosu na stvarnu visinu leta. Izračunati su stepeni korelacije i srednja kvadratna greška u merenju senzora sa ciljem procene rada senzora. Na osnovu rezultata istraživanja moguće je odrediti izbor adekvatnog senzora za ovu specifičnu primenu. Ovo istraživanje je pokazalo da je u uslovima ovog eksperimenta najbolje rezultate imao lidar senzor Garmin LIDAR-Lite V3HP i senzor Bosch Sensortech BME280 sa mogućnošću istovremenog merenja vlažnosti vazduha, atmosferskog pritiska i temperature.The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor

Quadcopter altitude estimation using low-cost barometric, infrared, ultrasonic and LIDAR sensors

Cilj ovog istraživanja je procena različitih low-cost senzora za merenje visine leta bespilotne letelice sa više rotora na malim visinama. Primenjene su metode filtriranja podataka i druge metode u cilju optimizacije performansi i tačnosti merenja senzora. Izvšrena su merenja visine leta, a podaci su uskladišteni za kasniju analizu u odnosu na stvarnu visinu leta. Izračunati su stepeni korelacije i srednja kvadratna greška u merenju senzora sa ciljem procene rada senzora. Na osnovu rezultata istraživanja moguće je odrediti izbor adekvatnog senzora za ovu specifičnu primenu. Ovo istraživanje je pokazalo da je u uslovima ovog eksperimenta najbolje rezultate imao lidar senzor Garmin LIDAR-Lite V3HP i senzor Bosch Sensortech BME280 sa mogućnošću istovremenog merenja vlažnosti vazduha, atmosferskog pritiska i temperature.The goal of this research is to assess the different low-cost sensors for flight altitude measuring of a multirotor UAV at low altitude flight. For optimizing the sensor performances and accuracy, data filtering and other methods were applied. The flight altitude data were collected and stored for later analysis with reference to the true altitude. The correlation coefficient and the mean squared error were calculated in order to assess the sensors' performance. On the basis of the results of the study, it was possible to determine the choice of the adequate sensor for this specific use. The study showed that the best characteristics for this experiment conditions had the Garmin LIDAR-Lite V3HP sensor and the Bosch Sensortech BME280 that combined air humidity, atmospheric pressure, and air temperature sensor

Modern Telemetry

Telemetry is based on knowledge of various disciplines like Electronics, Measurement, Control and Communication along with their combination. This fact leads to a need of studying and understanding of these principles before the usage of Telemetry on selected problem solving. Spending time is however many times returned in form of obtained data or knowledge which telemetry system can provide. Usage of telemetry can be found in many areas from military through biomedical to real medical applications. Modern way to create a wireless sensors remotely connected to central system with artificial intelligence provide many new, sometimes unusual ways to get a knowledge about remote objects behaviour. This book is intended to present some new up to date accesses to telemetry problems solving by use of new sensors conceptions, new wireless transfer or communication techniques, data collection or processing techniques as well as several real use case scenarios describing model examples. Most of book chapters deals with many real cases of telemetry issues which can be used as a cookbooks for your own telemetry related problems

Selected Papers from the 5th International Electronic Conference on Sensors and Applications

This Special Issue comprises selected papers from the proceedings of the 5th International Electronic Conference on Sensors and Applications, held on 15–30 November 2018, on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups. In this 5th edition of the electronic conference, contributors were invited to provide papers and presentations from the field of sensors and applications at large, resulting in a wide variety of excellent submissions and topic areas. Papers which attracted the most interest on the web or that provided a particularly innovative contribution were selected for publication in this collection. These peer-reviewed papers are published with the aim of rapid and wide dissemination of research results, developments, and applications. We hope this conference series will grow rapidly in the future and become recognized as a new way and venue by which to (electronically) present new developments related to the field of sensors and their applications

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

Advanced structural health monitoring strategies for condition-based maintenance planning of offshore wind turbine support structures

Condition-based maintenance strategies need to be adopted as distance-to-shore and water depth increase in the offshore wind industry. The aim of the research presented herein is to develop advance structural health monitoring strategies that enhance the condition-based maintenance of offshore wind turbine support structures. The focus is on the selection of technologies, the implementation process, the analysis of the asset’s structural response under complex loading, the economic justification for structural health monitoring implementation and the effective structural health monitoring data analysis. Research activities consist of the provision of a comprehensive study for structural health monitoring technologies’ utilisation in the offshore wind industry. This is followed by parametric structural modelling, simulation and validation of an operational offshore wind turbine tower, support structure and soil-structure interaction, using commercial software. The evaluation of the asset’s response under complex loading subject to design changes and failure mechanisms is also undertaken. A combination of existing and newly developed methodologies is deployed for the effective data management of structural health monitoring systems and validated with industrial data for the case of strain monitoring. These include unsupervised learning algorithms (neural networks), deterministic and probabilistic methods for noise cleansing and missing data imputation. Guidelines for the structural health monitoring implementation from design stage of a wind farm are proposed and applied to a baseline scenario. This is utilised to assess the economic impact that structural health monitoring has in the lifecycle of the assets. The achieved results show that the implementation of structural health monitoring in offshore wind turbine following the Statistical Pattern Recognition paradigm and the proposed guidelines has the potential to reduce the Operational Expenditure. This reduction is much greater than the cost associated with the implementation of these systems. Monitoring from the commissioning of the assets is crucial for the system’s calibration and establishing thresholds. The developed noise cleansing and missing data imputation methodologies can successfully be employed together to produce more complete low-disturbed datasets