Search results for: thermal remote sensing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5093

Search results for: thermal remote sensing

4823 An Attempt to Improve Student´s Understanding on Thermal Conductivity Using Thermal Cameras

Authors: Mariana Faria Brito Francisquini

Abstract:

Many thermal phenomena are present and play a substantial role in our daily lives. This presence makes the study of this area at both High School and University levels a very widely explored topic in the literature. However, a lot of important concepts to a meaningful understanding of the world are neglected at the expense of a traditional approach with senseless algebraic problems. In this work, we intend to show how the introduction of new technologies in the classroom, namely thermal cameras, can work in our favor to make a clearer understanding of many of these concepts, such as thermal conductivity. The use of thermal cameras in the classroom tends to diminish the everlasting abstractness in thermal phenomena as they enable us to visualize something that happens right before our eyes, yet we cannot see it. In our study, we will provide the same amount of heat to metallic cylindrical rods of the same length, but different materials in order to study the thermal conductivity of each one. In this sense, the thermal camera allows us to visualize the increase in temperature along each rod in real time enabling us to infer how heat is being transferred from one part of the rod to another. Therefore, we intend to show how this approach can contribute to the exposure of students to more enriching, intellectually prolific, scenarios than those provided by traditional approaches.

Keywords: teaching physics, thermal cameras, thermal conductivity, thermal physics

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4822 Comparati̇ve Study of Pi̇xel and Object-Based Image Classificati̇on Techni̇ques for Extracti̇on of Land Use/Land Cover Informati̇on

Authors: Mahesh Kumar Jat, Manisha Choudhary

Abstract:

Rapid population and economic growth resulted in changes in large-scale land use land cover (LULC) changes. Changes in the biophysical properties of the Earth's surface and its impact on climate are of primary concern nowadays. Different approaches, ranging from location-based relationships or modelling earth surface - atmospheric interaction through modelling techniques like surface energy balance (SEB) have been used in the recent past to examine the relationship between changes in Earth surface land cover and climatic characteristics like temperature and precipitation. A remote sensing-based model i.e., Surface Energy Balance Algorithm for Land (SEBAL), has been used to estimate the surface heat fluxes over Mahi Bajaj Sagar catchment (India) from 2001 to 2020. Landsat ETM and OLI satellite data are used to model the SEB of the area. Changes in observed precipitation and temperature, obtained from India Meteorological Department (IMD) have been correlated with changes in surface heat fluxes to understand the relative contributions of LULC change in changing these climatic variables. Results indicate a noticeable impact of LULC changes on climatic variables, which are aligned with respective changes in SEB components. Results suggest that precipitation increases at a rate of 20 mm/year. The maximum and minimum temperature decreases and increases at 0.007 ℃ /year and 0.02 ℃ /year, respectively. The average temperature increases at 0.009 ℃ /year. Changes in latent heat flux and sensible heat flux positively correlate with precipitation and temperature, respectively. Variation in surface heat fluxes influences the climate parameters and is an adequate reason for climate change. So, SEB modelling is helpful to understand the LULC change and its impact on climate.

Keywords: remote sensing, GIS, object based, classification

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4821 Distributed Optical Fiber Vibration Sensing Using Phase Generated Carrier Demodulation Algorithm

Authors: Zhihua Yu, Qi Zhang, Mingyu Zhang, Haolong Dai

Abstract:

Distributed fiber-optic vibration sensors are gaining extensive attention, for the advantages of high sensitivity, accurate location, light weight, large-scale monitoring, good concealment, and etc. In this paper, a novel optical fiber distributed vibration sensing system is proposed, which is based on self-interference of Rayleigh backscattering with phase generated carrier (PGC) demodulation algorithm. Pulsed lights are sent into the sensing fiber and the Rayleigh backscattering light from a certain position along the sensing fiber would interfere through an unbalanced Michelson Interferometry (MI) to generate the interference light. An improved PGC demodulation algorithm is carried out to recover the phase information of the interference signal, which carries the sensing information. Three vibration events were applied simultaneously to different positions over 2000m sensing fiber and demodulated correctly. Experiments show that the spatial resolution of is 10 m, and the noise level of the Φ-OTDR system is about 10-3 rad/√Hz, and the signal to noise ratio (SNR) is about 30.34dB. This vibration measurement scheme can be applied at surface, seabed or downhole for vibration measurements or distributed acoustic sensing (DAS).

Keywords: fiber optics sensors, Michelson interferometry, MI, phase-sensitive optical time domain reflectometry, Φ-OTDR, phase generated carrier, PGC

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4820 Investigation of Different Machine Learning Algorithms in Large-Scale Land Cover Mapping within the Google Earth Engine

Authors: Amin Naboureh, Ainong Li, Jinhu Bian, Guangbin Lei, Hamid Ebrahimy

Abstract:

Large-scale land cover mapping has become a new challenge in land change and remote sensing field because of involving a big volume of data. Moreover, selecting the right classification method, especially when there are different types of landscapes in the study area is quite difficult. This paper is an attempt to compare the performance of different machine learning (ML) algorithms for generating a land cover map of the China-Central Asia–West Asia Corridor that is considered as one of the main parts of the Belt and Road Initiative project (BRI). The cloud-based Google Earth Engine (GEE) platform was used for generating a land cover map for the study area from Landsat-8 images (2017) by applying three frequently used ML algorithms including random forest (RF), support vector machine (SVM), and artificial neural network (ANN). The selected ML algorithms (RF, SVM, and ANN) were trained and tested using reference data obtained from MODIS yearly land cover product and very high-resolution satellite images. The finding of the study illustrated that among three frequently used ML algorithms, RF with 91% overall accuracy had the best result in producing a land cover map for the China-Central Asia–West Asia Corridor whereas ANN showed the worst result with 85% overall accuracy. The great performance of the GEE in applying different ML algorithms and handling huge volume of remotely sensed data in the present study showed that it could also help the researchers to generate reliable long-term land cover change maps. The finding of this research has great importance for decision-makers and BRI’s authorities in strategic land use planning.

Keywords: land cover, google earth engine, machine learning, remote sensing

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4819 Thermal Stability and Insulation of a Cement Mixture Using Graphene Oxide Nanosheets

Authors: Nasser A. M. Habib

Abstract:

The impressive physical properties of graphene derivatives, including thermal properties, have made them an attractive addition to advanced construction nanomaterial. In this study, we investigated the impact of incorporating low amounts of graphene oxide (GO) into cement mixture nanocomposites on their heat storage and thermal stability. The composites were analyzed using Fourier transmission infrared, thermo-gravimetric analysis, and field emission scanning electron microscopy. Results showed that GO significantly improved specific heat by 30%, reduced thermal conductivity by 15%, and reduced thermal decomposition to only 3% at a concentration of 1.2 wt%. These findings suggest that the cement mixture can withstand high temperatures and may be suitable for specific applications requiring thermal stability and insulation properties.

Keywords: cement mixture composite, graphene oxide, thermal decomposition, thermal conductivity

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4818 Field Study for Evaluating Winter Thermal Performance of Auckland School Buildings

Authors: Bin Su

Abstract:

Auckland has a temperate climate with comfortable warm, dry summers and mild, wet winters. An Auckland school normally does not need air conditioning for cooling during the summer and only needs heating during the winter. The Auckland school building thermal design should more focus on winter thermal performance and indoor thermal comfort for energy efficiency. This field study of testing indoor and outdoor air temperatures, relative humidity and indoor surface temperatures of three classrooms with different envelopes were carried out in the Avondale College during the winter months in 2013. According to the field study data, this study is to compare and evaluate winter thermal performance and indoor thermal conditions of school buildings with different envelopes.

Keywords: building envelope, building mass effect, building thermal comfort, building thermal performance, school building

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4817 Thermal Fatigue Behavior of Austenitic Stainless Steels

Authors: Jung-Ho Moon, Tae Kwon Ha

Abstract:

Continually increasing working temperature and growing need for greater efficiency and reliability of automotive exhaust require systematic investigation into the thermal fatigue properties especially of high temperature stainless steels. In this study, thermal fatigue properties of 300 series austenitic stainless steels have been evaluated in the temperature ranges of 200-800°C and 200-900°C. Systematic methods for control of temperatures within the predetermined range and measurement of load applied to specimens as a function of temperature during thermal cycles have been established. Thermal fatigue tests were conducted under fully constrained condition, where both ends of specimens were completely fixed. Load relaxation behavior at the temperatures of thermal cycle was closely related with the thermal fatigue property.

Keywords: austenitic stainless steel, automotive exhaust, thermal fatigue, microstructure, load relaxation

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4816 Linear Frequency Modulation-Frequency Shift Keying Radar with Compressive Sensing

Authors: Ho Jeong Jin, Chang Won Seo, Choon Sik Cho, Bong Yong Choi, Kwang Kyun Na, Sang Rok Lee

Abstract:

In this paper, a radar signal processing technique using the LFM-FSK (Linear Frequency Modulation-Frequency Shift Keying) is proposed for reducing the false alarm rate based on the compressive sensing. The LFM-FSK method combines FMCW (Frequency Modulation Continuous Wave) signal with FSK (Frequency Shift Keying). This shows an advantage which can suppress the ghost phenomenon without the complicated CFAR (Constant False Alarm Rate) algorithm. Moreover, the parametric sparse algorithm applying the compressive sensing that restores signals efficiently with respect to the incomplete data samples is also integrated, leading to reducing the burden of ADC in the receiver of radars. 24 GHz FMCW signal is applied and tested in the real environment with FSK modulated data for verifying the proposed algorithm along with the compressive sensing.

Keywords: compressive sensing, LFM-FSK radar, radar signal processing, sparse algorithm

Procedia PDF Downloads 457
4815 Modern Spectrum Sensing Techniques for Cognitive Radio Networks: Practical Implementation and Performance Evaluation

Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

Abstract:

Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

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4814 Membrane Spanning DNA Origami Nanopores for Protein Translocation

Authors: Genevieve Pugh, Johnathan Burns, Stefan Howorka

Abstract:

Single-molecule sensing via protein nanopores has achieved a step-change in portable and label-free DNA sequencing. However, protein pores of both natural or engineered origin are not able to produce the tunable diameters needed for effective protein sensing. Here, we describe a generic strategy to build synthetic DNA nanopores that are wide enough to accommodate folded protein. The pores are composed of interlinked DNA duplexes and carry lipid anchors to achieve the required membrane insertion. Our demonstrator pore has a contiguous cross-sectional channel area of 50 nm2 which is 6-times larger than the largest protein pore. Consequently, transport of folded protein across bilayers is possible. The modular design is amenable for different pore dimensions and can be adapted for protein sensing or to create molecular gates in synthetic biology.

Keywords: biosensing, DNA nanotechnology, DNA origami, nanopore sensing

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4813 Classification Method for Turnover While Sleeping Using Multi-Point Unconstrained Sensing Devices

Authors: K. Shiba, T. Kobayashi, T. Kaburagi, Y. Kurihara

Abstract:

Elderly population in the world is increasing, and consequently, their nursing burden is also increasing. In such situations, monitoring and evaluating their daily action facilitates efficient nursing care. Especially, we focus on an unconscious activity during sleep, i.e. turnover. Monitoring turnover during sleep is essential to evaluate various conditions related to sleep. Bedsores are considered as one of the monitoring conditions. Changing patient’s posture every two hours is required for caregivers to prevent bedsore. Herein, we attempt to develop an unconstrained nocturnal monitoring system using a sensing device based on piezoelectric ceramics that can detect the vibrations owing to human body movement on the bed. In the proposed method, in order to construct a multi-points sensing, we placed two sensing devices under the right and left legs at the head-side of an ordinary bed. Using this equipment, when a subject lies on the bed, feature is calculated from the output voltages of the sensing devices. In order to evaluate our proposed method, we conducted an experiment with six healthy male subjects. Consequently, the period during which turnover occurs can be correctly classified as the turnover period with 100% accuracy.

Keywords: turnover, piezoelectric ceramics, multi-points sensing, unconstrained monitoring system

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4812 Total Thermal Resistance of Graphene-Oxide-Substrate Stack: Role of Interfacial Thermal Resistance in Heat Flow of 2D Material Based Devices

Authors: Roisul H. Galib, Prabhakar R. Bandaru

Abstract:

In 2D material based device, an interface between 2D materials and substrates often limits the heat flow through the device. In this paper, we quantify the total thermal resistance of a graphene-based device by series resistance model and show that the thermal resistance at the interface of graphene and substrate contributes to more than 50% of the total resistance. Weak Van der Waals interactions at the interface and dissimilar phonon vibrational modes create this thermal resistance, allowing less heat to flow across the interface. We compare our results with commonly used materials and interfaces, demonstrating the role of the interface as a potential application for heat guide or block in a 2D material-based device.

Keywords: 2D material, graphene, thermal conductivity, thermal conductance, thermal resistance

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4811 Identification and Analysis of Supports Required for Teachers Moving to Remote Teaching and Learning during Disasters and Pandemics

Authors: Susan Catapano, Meredith Jones, Carol McNulty

Abstract:

Analysis of one state’s collaborative effort to support teachers, in both public and private schools, as they moved from face-to-face teaching to remote teaching during the Covid pandemic to identify lessons learned and materials put into place to support teachers and families. Surveys were created, distributed, and analyzed throughout the three months of remote teaching, documents and lesson plans were developed, and training materials were created. All data collected and materials developed were analyzed to identify supports teachers used and needed for successful remote teaching. Researchers found most teachers easily moved to online teaching; however, many families did not have access to technology, so teachers needed to develop non-technology-based access and support for remote teaching. Teachers also reported the need to prepare to teach remotely as part of their teaching training, so they were prepared in the future. Finally, data indicated teachers were able to establish stronger relationships with families than usual as a result of remote teaching. The lessons learned and support developed are part of the state’s ongoing policy for online teaching in the event of disasters and pandemics in the future.

Keywords: remote learning, teacher education, pandemic, families

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4810 Using Geographic Information Systems Techniques and Multi-Source Earth Observation Data to Study the Trends of Urban Expansion in Welayat Barka Sultanate of Oman during the Period from 2002 to 2019

Authors: Eyad H. R. Fadda, Jawaher K. Al Rashdieah, Aysha H. Al Rashdieh

Abstract:

Urban Sprawl is a phenomenon that many regions in the Sultanate of Oman suffer from in general and in Welayat Barka in particular. It is considered a human phenomenon that causes many negative effects as it has increased in the last time clearly, and this study aims to diagnose the current status of urban growth taking place in Walayat Barka. The objective of this study is to monitor and follow up on the most prominent changes and developments taking place in Barka in the period from 2002 to 2019 and provide suggestions to the decision-makers to reduce the negative effects of the phenomenon. The study methodology depends on the descriptive and analytical approach to describe the phenomenon and its analysis and knowledge of the factors that helped in urban expansion in the Barka, using a number of studies and interviews with the specialists, both in governmental and private institutions, as well as with individuals who own land, real estate, and others. Geographic Information Systems (GIS) and Remote Sensing (ERDAS software) have been used to analyze the satellite images that helped in obtaining results that reflect the changes Barka, in addition to knowing the natural and human determinants that stand on Urban Sprawl Expansion. The study concluded that the geographical location of Barka has a significant role in its urban expansion, as it is the closest state to the capital Muscat, as this expansion continues toward the southern and south-western directions, as this expansion has significant negative effects represented in the low number of agricultural lands due to the continuous change in land use. In addition, it was found that there are two types of natural determinants of urban expansion in Barka, which are consumed land from the Sea of Oman and from the western sands.

Keywords: GIS applications, remote sensing, urbanization, urban sprawl expansion trends

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4809 Realization of Wearable Inertial Measurement Units-Sensor-Fusion Harness to Control Therapeutic Smartphone Applications

Authors: Svilen Dimitrov, Manthan Pancholi, Norbert Schmitz, Didier Stricker

Abstract:

This paper presents the end-to-end development of a wearable motion sensing harness consisting of computational unit and four inertial measurement units to control three smartphone therapeutic games for children. The inertial data is processed in real time to obtain lower body motion information like knee raises, feet taps and squads. By providing a Wi-Fi connection interface the sensor harness acts wireless remote control for smartphone applications. By performing various lower body movements the users provoke corresponding game state changes. In contrary to the current similar offers, like Nintendo Wii Remote, Xbox Kinect and Playstation Move, this product, consisting of the sensor harness and the applications on top of it, are fully wearable, which means they do not rely on the user to be bound to concrete soft- or hardwareequipped space.

Keywords: wearable harness, inertial measurement units, smartphone therapeutic games, motion tracking, lower-body activity monitoring

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4808 Doped and Co-doped ZnO Based Nanoparticles and their Photocatalytic and Gas Sensing Property

Authors: Neha Verma, Manik Rakhra

Abstract:

Statement of the Problem: Nowadays, a tremendous increase in population and advanced industrialization augment the problems related to air and water pollutions. Growing industries promoting environmental danger, which is an alarming threat to the ecosystem. For safeguard, the environment, detection of perilous gases and release of colored wastewater is required for eutrophication pollution. Researchers around the globe are trying their best efforts to save the environment. For this remediation advanced oxidation process is used for potential applications. ZnO is an important semiconductor photocatalyst with high photocatalytic and gas sensing activities. For efficient photocatalytic and gas sensing properties, it is necessary to prepare a doped/co-doped ZnO compound to decrease the electron-hole recombination rates. However, lanthanide doped and co-doped metal oxide is seldom studied for photocatalytic and gas sensing applications. The purpose of this study is to describe the best photocatalyst for the photodegradation of dyes and gas sensing properties. Methodology & Theoretical Orientation: Economical framework has to be used for the synthesis of ZnO. In the depth literature survey, a simple combustion method is utilized for gas sensing and photocatalytic activities. Findings: Rare earth doped and co-doped ZnO nanoparticles were the best photocatalysts for photodegradation of organic dyes and different gas sensing applications by varying various factors such as pH, aging time, and different concentrations of doping and codoping metals in ZnO. Complete degradation of dye was observed only in min. Gas sensing nanodevice showed a better response and quick recovery time for doped/co-doped ZnO. Conclusion & Significance: In order to prevent air and water pollution, well crystalline ZnO nanoparticles were synthesized by rapid and economic method, which is used as photocatalyst for photodegradation of organic dyes and gas sensing applications to sense the release of hazardous gases from the environment.

Keywords: ZnO, photocatalyst, photodegradation of dye, gas sensor

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4807 Geospatial Techniques for Impact Assessment of Canal Rehabilitation Program in Sindh, Pakistan

Authors: Sumaira Zafar, Arjumand Zaidi, Muhammad Arslan Hafeez

Abstract:

Indus Basin Irrigation System (IBIS) is the largest contiguous irrigation system of the world comprising Indus River and its tributaries, canals, distributaries, and watercourses. A big challenge faced by IBIS is transmission losses through seepage and leaks that account to 41 percent of the total water derived from the river and about 40 percent of that is through watercourses. Irrigation system rehabilitation programs in Pakistan are focused on improvement of canal system at the watercourse level (tertiary channels). Under these irrigation system management programs more than 22,800 watercourses have been improved or lined out of 43,000 (12,900 Kilometers) watercourses. The evaluation of the improvement work is required at this stage to testify the success of the programs. In this paper, emerging technologies of GIS and satellite remote sensing are used for impact assessment of watercourse rehabilitation work in Sindh. To evaluate the efficiency of the improved watercourses, few parameters are selected like soil moisture along watercourses, availability of water at tail end and changes in cultivable command areas. Improved watercourses details and maps are acquired from National Program for Improvement of Watercourses (NPIW) and Space and Upper Atmospheric Research Commission (SUPARCO). High resolution satellite images of Google Earth for the year of 2004 to 2013 are used for digitizing command areas. Temporal maps of cultivable command areas show a noticeable increase in the cultivable land served by improved watercourses. Field visits are conducted to validate the results. Interviews with farmers and landowners also reveal their overall satisfaction in terms of availability of water at the tail end and increased crop production.

Keywords: geospatial, impact assessment, watercourses, GIS, remote sensing, seepage, canal lining

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4806 Application of Compressed Sensing Method for Compression of Quantum Data

Authors: M. Kowalski, M. Życzkowski, M. Karol

Abstract:

Current quantum key distribution systems (QKD) offer low bit rate of up to single MHz. Compared to conventional optical fiber links with multiple GHz bitrates, parameters of recent QKD systems are significantly lower. In the article we present the conception of application of the Compressed Sensing method for compression of quantum information. The compression methodology as well as the signal reconstruction method and initial results of improving the throughput of quantum information link are presented.

Keywords: quantum key distribution systems, fiber optic system, compressed sensing

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4805 Modified Silicates as Dissolved Oxygen Sensors in Water: Structural and Optical Properties

Authors: Andile Mkhohlakali, Tien-Chien Jen, James Tshilongo, Happy Mabowa

Abstract:

Among different parameters, oxygen is one of the most important analytes of interest, dissolved oxygen (DO) concentration is very crucial and significant for various areas of physical, chemical, and environmental monitoring. Herein we report oxygen-sensitive luminophores -based lanthanum(III) trifluoromethanesulfonate), [La]³⁺ was encapsulated into SiO₂-based xerogel matrix. The nanosensor is composed of organically modified silica nanoparticles, doped with the luminescent oxygen–sensitive lanthanum(III) trifluoromethanesulfonate complex. The precursor materials used for sensing film were triethyl ethoxy silane (TEOS) and (3-Mercaptopropyltriethoxysilane) (MPTMS- TEOS) used for SiO2-baed matrices. Brunauer–Emmett–Teller (BET), and BJH indicate that the SiO₂ transformed from microporous to mesoporous upon the addition of La³⁺ luminophore with increased surface area (SBET). The typical amorphous SiO₂ based xerogels were revealed with X-Ray diffraction (XRD) and Selected Area Electron Diffraction (SAED) analysis. Scanning electron microscope- (SEM) and transmission electron microscope (TEM) showed the porous morphology and reduced particle for SiO₂ and La-SiO₂ xerogels respectively. The existence of elements, siloxane networks, and thermal stability of xerogel was confirmed by energy dispersive spectroscopy (EDS), Fourier-transform infrared spectroscopy (FTIR), and Thermographic analysis (TGA). UV-Vis spectroscopy and photoluminescence (PL) have been used to characterize the optical properties of xerogels. La-SiO₂ demonstrates promising characteristic features of an active sensing film for dissolved oxygen in the water. Keywords: Sol-gel, ORMOSILs, encapsulation, Luminophores quenching, O₂-sensing

Keywords: sol-gel, ORMOSILs, luminophores quenching, O₂-sensing

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4804 Remote Video Supervision via DVB-H Channels

Authors: Hanen Ghabi, Youssef Oudhini, Hassen Mnif

Abstract:

By reference to recent publications dealing with the same problem, and as a follow-up to this research work already published, we propose in this article a new original idea of tele supervision exploiting the opportunities offered by the DVB-H system. The objective is to exploit the RF channels of the DVB-H network in order to insert digital remote monitoring images dedicated to a remote solar power plant. Indeed, the DVB-H (Digital Video Broadcast-Handheld) broadcasting system was designed and deployed for digital broadcasting on the same platform as the parent system, DVB-T. We claim to be able to exploit this approach in order to satisfy the operator of remote photovoltaic sites (and others) in order to remotely control the components of isolated installations by means of video surveillance.

Keywords: video surveillance, digital video broadcast-handheld, photovoltaic sites, AVC

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4803 Remote Sensing and Geographic Information Systems for Identifying Water Catchments Areas in the Northwest Coast of Egypt for Sustainable Agricultural Development

Authors: Mohamed Aboelghar, Ayman Abou Hadid, Usama Albehairy, Asmaa Khater

Abstract:

Sustainable agricultural development of the desert areas of Egypt under the pressure of irrigation water scarcity is a significant national challenge. Existing water harvesting techniques on the northwest coast of Egypt do not ensure the optimal use of rainfall for agricultural purposes. Basin-scale hydrology potentialities were studied to investigate how available annual rainfall could be used to increase agricultural production. All data related to agricultural production included in the form of geospatial layers. Thematic classification of Sentinal-2 imagery was carried out to produce the land cover and crop maps following the (FAO) system of land cover classification. Contour lines and spot height points were used to create a digital elevation model (DEM). Then, DEM was used to delineate basins, sub-basins, and water outlet points using the Soil and Water Assessment Tool (Arc SWAT). Main soil units of the study area identified from Land Master Plan maps. Climatic data collected from existing official sources. The amount of precipitation, surface water runoff, potential, and actual evapotranspiration for the years (2004 to 2017) shown as results of (Arc SWAT). The land cover map showed that the two tree crops (olive and fig) cover 195.8 km2 when herbaceous crops (barley and wheat) cover 154 km2. The maximum elevation was 250 meters above sea level when the lowest one was 3 meters below sea level. The study area receives a massive variable amount of precipitation; however, water harvesting methods are inappropriate to store water for purposes.

Keywords: water catchements, remote sensing, GIS, sustainable agricultural development

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4802 Optimization of Fused Deposition Modeling 3D Printing Process via Preprocess Calibration Routine Using Low-Cost Thermal Sensing

Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

Abstract:

This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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4801 From the Bright Lights of the City to the Shadows of the Bush: Expanding Knowledge through a Case-Based Teaching Approach

Authors: Henriette van Rensburg, Betty Adcock

Abstract:

Concern about the lack of knowledge of quality teaching and teacher retention in rural and remote areas of Australia, has caused academics to improve pre-service teachers’ understanding of this problem. The participants in this study were forty students enrolled in an undergraduate educational course (EDO3341 Teaching in rural and remote communities) at the University of Southern Queensland in Toowoomba in 2012. This study involved an innovative case-based teaching approach in order to broaden their generally under-informed understanding of teaching in a rural and remote area. Three themes have been identified through analysing students’ critical reflections: learning expertise, case-based learning support and authentic learning. The outcomes identified the changes in pre-service teachers’ understanding after they have deepened their knowledge of the realities of teaching in rural and remote areas.

Keywords: rural and remote education, case based teaching, innovative education approach, higher education

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4800 Study of Hydrothermal Behavior of Thermal Insulating Materials Based on Natural Fibers

Authors: J. Zach, J. Hroudova, J. Brozovsky

Abstract:

Thermal insulation materials based on natural fibers represent a very promising area of materials based on natural easy renewable row sources. These materials may be in terms of the properties of most competing synthetic insulations, but show somewhat higher moisture sensitivity and thermal insulation properties are strongly influenced by the density and orientation of fibers. The paper described the problem of hygrothermal behavior of thermal insulation materials based on natural plant and animal fibers. This is especially the dependence of the thermal properties of these materials on the type of fiber, bulk density, temperature, moisture and the fiber orientation.

Keywords: thermal insulating materials, hemp fibers, sheep wool fibers, thermal conductivity, moisture

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4799 Thermal Network Model for a Large Scale AC Induction Motor

Authors: Sushil Kumar, M. Dakshina Murty

Abstract:

Thermal network modelling has proven to be important tool for thermal analysis of electrical machine. This article investigates numerical thermal network model and experimental performance of a large-scale AC motor. Experimental temperatures were measured using RTD in the stator which have been compared with the numerical data. Thermal network modelling fairly predicts the temperature of various components inside the large-scale AC motor. Results of stator winding temperature is compared with experimental results which are in close agreement with accuracy of 6-10%. This method of predicting hot spots within AC motors can be readily used by the motor designers for estimating the thermal hot spots of the machine.

Keywords: AC motor, thermal network, heat transfer, modelling

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4798 3D Classification Optimization of Low-Density Airborne Light Detection and Ranging Point Cloud by Parameters Selection

Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

Abstract:

Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

Procedia PDF Downloads 137
4797 An Overview of Thermal Storage Techniques for Solar Thermal Applications

Authors: Talha Shafiq

Abstract:

The traditional electricity operation in solar thermal plants is designed to operate on a single path initiating at power plant and executes at the consumer. Due to lack of energy storage facilities during this operation, a decrease in the efficiency is often observed with the power plant performance. This paper reviews the significance of energy storage in supply design and elaborates various methods that can be adopted in this regard which are equally cost effective and environmental friendly. Moreover, various parameters in thermal storage technique are also critically analyzed to clarify the pros and cons in this facility. Discussing the different thermal storage system, their technical and economical evaluation has also been reviewed.

Keywords: thermal energy storage, sensible heat storage, latent heat storage, thermochemical heat storage

Procedia PDF Downloads 542
4796 Assessment of Environmental Implications of Rapid Population Growth on Land Use Dynamics: A Case Study of Eleme Local Government Area, Rivers State, Nigeria

Authors: Moses Obenade, Henry U. Okeke, Francis I. Okpiliya, Eugene J. Aniah

Abstract:

Population growth in Eleme has been rapid over the past 75 years with its attendant pressure on the natural resources of the area. Between 1937 and 2006 the population of Eleme grew from 2,528 to 190,194 and is projected to be above 265,707 in 2016 based on an annual growth rate of 3.4%. Using the combined technologies of Geographic Information Systems (GIS), remote sensing (RS) and Demography techniques as its methodology, this paper examines the environmental implications of rapid population growth on land use dynamics in Eleme between 1986 and 2015. The study reveals that between 1986 and 2006, Built-up area and Farmland increased by 72.67 and 12.77% respectively, while light and thick vegetation recorded a decrease of -6.92 and -61.64% respectively. Water body remains fairly constant with minimal changes. Also, between 2006 and 2015 covering a period of 9 years, Built-up area further increased by 53% with an annual growth rate of 2.32 km2 gaining more land area on the detriment of other land uses. Built-up area has an annual growth rate of 2.32km2 and is expected to increase from 18.67km2 in 2006 to 41.87km2 in 2016.The observed Land used/Land cover dynamics is derived by the demographic characteristics of the Study area. Eleme has a total area of 138km2 out of which the Federal Government of Nigeria compulsorily acquired an estimated area of 59.34km2 for industrial purposes excluding acquisitions by the Rivers State Government. It is evident from the findings of this study that the carrying capacity of Eleme ecosystem is under threat due to the current population growth and land consumption rates. Therefore, measures such as use of appropriate technologies in farming techniques, waste management; investment in family planning and female empowerment, maternal health and education, afforestation programs; and amendment of Land Use Act of 1978 are recommended.

Keywords: population growth, Eleme, land use, GIS and remote sensing

Procedia PDF Downloads 366
4795 Monitoring of Rice Phenology and Agricultural Practices from Sentinel 2 Images

Authors: D. Courault, L. Hossard, V. Demarez, E. Ndikumana, D. Ho Tong Minh, N. Baghdadi, F. Ruget

Abstract:

In the global change context, efficient management of the available resources has become one of the most important topics, particularly for sustainable crop development. Timely assessment with high precision is crucial for water resource and pest management. Rice cultivated in Southern France in the Camargue region must face a challenge, reduction of the soil salinity by flooding and at the same time reduce the number of herbicides impacting negatively the environment. This context has lead farmers to diversify crop rotation and their agricultural practices. The objective of this study was to evaluate this crop diversity both in crop systems and in agricultural practices applied to rice paddy in order to quantify the impact on the environment and on the crop production. The proposed method is based on the combined use of crop models and multispectral data acquired from the recent Sentinel 2 satellite sensors launched by the European Space Agency (ESA) within the homework of the Copernicus program. More than 40 images at fine spatial resolution (10m in the optical range) were processed for 2016 and 2017 (with a revisit time of 5 days) to map crop types using random forest method and to estimate biophysical variables (LAI) retrieved by inversion of the PROSAIL canopy radiative transfer model. Thanks to the high revisit time of Sentinel 2 data, it was possible to monitor the soil labor before flooding and the second sowing made by some farmers to better control weeds. The temporal trajectories of remote sensing data were analyzed for various rice cultivars for defining the main parameters describing the phenological stages useful to calibrate two crop models (STICS and SAFY). Results were compared to surveys conducted with 10 farms. A large variability of LAI has been observed at farm scale (up to 2-3m²/m²) which induced a significant variability in the yields simulated (up to 2 ton/ha). Observations on more than 300 fields have also been collected on land use. Various maps were elaborated, land use, LAI, flooding and sowing, and harvest dates. All these maps allow proposing a new typology to classify these paddy crop systems. Key phenological dates can be estimated from inverse procedures and were validated against ground surveys. The proposed approach allowed to compare the years and to detect anomalies. The methods proposed here can be applied at different crops in various contexts and confirm the potential of remote sensing acquired at fine resolution such as the Sentinel2 system for agriculture applications and environment monitoring. This study was supported by the French national center of spatial studies (CNES, funded by the TOSCA).

Keywords: agricultural practices, remote sensing, rice, yield

Procedia PDF Downloads 265
4794 Comparative Analysis of Change in Vegetation in Four Districts of Punjab through Satellite Imagery, Land Use Statistics and Machine Learning

Authors: Mirza Waseem Abbas, Syed Danish Raza

Abstract:

For many countries agriculture is still the major force driving the economy and a critically important socioeconomic sector, despite exceptional industrial development across the globe. In countries like Pakistan, this sector is considered the backbone of the economy, and most of the economic decision making revolves around agricultural outputs and data. Timely and accurate facts and figures about this vital sector hold immense significance and have serious implications for the long-term development of the economy. Therefore, any significant improvements in the statistics and other forms of data regarding agriculture sector are considered important by all policymakers. This is especially true for decision making for the betterment of crops and the agriculture sector in general. Provincial and federal agricultural departments collect data for all cash and non-cash crops and the sector, in general, every year. Traditional data collection for such a large sector i.e. agriculture, being time-consuming, prone to human error and labor-intensive, is slowly but gradually being replaced by remote sensing techniques. For this study, remotely sensed data were used for change detection (machine learning, supervised & unsupervised classification) to assess the increase or decrease in area under agriculture over the last fifteen years due to urbanization. Detailed Landsat Images for the selected agricultural districts were acquired for the year 2000 and compared to images of the same area acquired for the year 2016. Observed differences validated through detailed analysis of the areas show that there was a considerable decrease in vegetation during the last fifteen years in four major agricultural districts of the Punjab province due to urbanization (housing societies).

Keywords: change detection, area estimation, machine learning, urbanization, remote sensing

Procedia PDF Downloads 239