Search results for: leakage gas monitoring

Authors: Bing-Bing E. Goh

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Plant counting is a labour intensive and time-consuming task for the farmers. However, it is an important indicator for farmers to make decisions on subsequent field management. This study is to evaluate the potential of Sentinel-2 images using statistical analysis to retrieve information on plant density for monitoring, especially during critical period at the beginning of March. The model was calibrated with in-situ data from 19 winter wheat fields in Republic of Ireland during the crop growing season in 2019-2020. The model for plant density resulted in R2 = 0.77, RMSECV = 103 and NRMSE = 14%. This study has shown the potential of using Sentinel-2 to estimate plant density and quantify plant establishment to effectively monitor crop progress and to ensure proper field management.

Keywords: winter wheat, remote sensing, crop monitoring, multivariate analysis

Procedia PDF Downloads 138

Authors: Mahdi Ghasemi-Varnamkhasti, Ayat Mohammad-Razdari, Seyedeh-Hoda Yoosefian

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Taste is an important sensory property governing acceptance of products for administration through mouth. The advent of artificial sensorial systems as non-destructive tools able to mimic chemical senses such as those known as electronic tongue (ET) has open a variety of practical applications and new possibilities in many fields where the presence of taste is the phenomenon under control. In recent years, electronic tongue technology opened the possibility to exploit information on taste attributes of fruits providing real time information about quality and ripeness. Electronic tongue systems have received considerable attention in the field of sensor technology during the last two decade because of numerous applications in diverse fields of applied sciences. This paper deals with some facets of this technology in the quality monitoring of fruits along with more recent its applications.

Keywords: fruit, electronic tongue, non-destructive, taste machine, horticultural

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Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

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DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

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Authors: S. Y. Cicekli

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In this study, tree-dimensional model of tree was created by using terrestrial close range photogrammetry. For this close range photos were taken. Photomodeler Pro 5 software was used for camera calibration and create three-dimensional model of trees. In first test, three-dimensional model of a tree was created, in the second test three-dimensional model of three trees were created. This study aim is creating three-dimensional model of trees and indicate the use of close-range photogrammetry in forestry. At the end of the study, three-dimensional model of tree and three trees were created. This study showed that usability of close-range photogrammetry for monitoring tree and forests three-dimensional model.

Keywords: close- range photogrammetry, forest, tree, three-dimensional model

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Authors: Ramachandra C. G., Amarnath. M., Prashanth Pai M., Nagesh S. N.

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The machine's performance level drops down over a period of time due to the wear and tear of its components. The early detection of an emergent fault becomes very vital in order to obtain uninterrupted production in a plant. Maintenance is an activity that helps to keep the machine's performance at an anticipated level, thereby ensuring the availability of the machine to perform its intended function. At present, a number of modern maintenance techniques are available, such as preventive maintenance, predictive maintenance, condition-based maintenance, total productive maintenance, etc. Condition-based maintenance or condition monitoring is one such modern maintenance technique in which the machine's condition or health is checked by the measurement of certain parameters such as sound level, temperature, velocity, displacement, vibration, etc. It can recognize most of the factors restraining the usefulness and efficacy of the total manufacturing unit. This research work is conducted on a Batch Mill in a tire production unit located in the Southern Karnataka region. The health of the mill is assessed using amplitude of vibration as a parameter of measurement. Most commonly, the vibration level is assessed using various points on the machine bearing. The normal or standard level is fixed using reference materials such as manuals or catalogs supplied by the manufacturers and also by referring vibration standards. The Rio-Vibro meter is placed in different locations on the batch-off mill to record the vibration data. The data collected are analyzed to identify the malfunctioning components in the batch off the mill, and corrective measures are suggested.

Keywords: availability, displacement, vibration, rio-vibro, condition monitoring

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Authors: Sarah Odofin, Zhiwei Gao, Sun Kai

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Operations, maintenance and reliability of wind turbines have received much attention over the years due to rapid expansion of wind farms. This paper explores early fault diagnosis scale technique based on a unique scheme of a 5MW wind turbine system that is optimized by genetic algorithm to be very sensitive to faults and resilient to disturbances. A quantitative model based analysis is pragmatic for primary fault diagnosis monitoring assessment to minimize downtime mostly caused by components breakdown and exploit productivity consistency. Simulation results are computed validating the wind turbine model which demonstrates system performance in a practical application of fault type examples. The results show the satisfactory effectiveness of the applied performance investigated in a Matlab/Simulink/Gatool environment.

Keywords: disturbance robustness, fault monitoring and detection, genetic algorithm, observer technique

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Authors: Zama Mahmood

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The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

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Authors: Nadeem Qaiser, Sherjeel Munsif Khan, Muhammad Mustafa Hussian, Vincent Tung

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One of the emerging fields in the detection of chronic diseases is based on the point-of-care (POC) early monitoring of the symptoms and thus provides a state-of-the-art personalized healthcare system. Nowadays, wearable and flexible sensors are being used for analyzing sweat, glucose, blood pressure, and other skin conditions. However, localized jaw-bone swelling called parotid-swelling caused by some viruses has never been tracked before. To track physical motion or deformations, strain sensors, especially piezoresistive ones, are widely used. This work, for the first time, reports carbon nanotubes (CNTs)-based piezoresistive sensing patch that is highly flexible and stretchable and can record muscle deformations in real-time. The developed patch offers an excellent gauge factor for in-plane stretching and spatial expansion with low hysteresis. To calibrate the volumetric muscle expansion, we fabricated the pneumatic actuator that experienced volumetric expansion and thus redefined the gauge factor. Moreover, we employ a Bluetooth-low-energy system that can send information about muscle activity in real-time to a smartphone app. We utilized COMSOL calculations to reveal the mechanical robustness of the patch. The experiments showed the sensing patch's greater cyclability, making it a patch for personal healthcare and an excellent choice for monitoring the real-time POC monitoring of the human muscle swelling.

Keywords: piezoresistive strain sensor, FEM simulations, CNTs sensor, flexible

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Authors: Arnaldo G. de Oliveira, Jr, Matthieu Tubino

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The transesterification process of triglycerides with alcohols that occurs during the biodiesel synthesis causes continuous changes in several physical properties of the reaction mixture, such as refractive index, viscosity and density. Amongst them, density can be an useful parameter to monitor the reaction, in order to predict the composition of the reacting mixture and to verify the conversion of the oil into biodiesel. In this context, a system was constructed in order to continuously determine changes in the density of the reacting mixture containing soybean oil, methanol and sodium methoxide (30 % w/w solution in methanol), stirred at 620 rpm at room temperature (about 27 °C). A polyethylene pipe network connected to a peristaltic pump was used in order to collect the mixture and pump it through a coil fixed on the plate of an analytical balance. The collected mass values were used to trace a curve correlating the mass of the system to the reaction time. The density variation profile versus the time clearly shows three different steps: 1) the dispersion of methanol in oil causes a decrease in the system mass due to the lower alcohol density followed by stabilization; 2) the addition of the catalyst (sodium methoxide) causes a larger decrease in mass compared to the first step (dispersion of methanol in oil) because of the oil conversion into biodiesel; 3) the final stabilization, denoting the end of the reaction. This density variation profile provides information that was used to predict the composition of the mixture over the time and the reaction rate. The precise knowledge of the duration of the synthesis means saving time and resources on a scale production system. This kind of monitoring provides several interesting features such as continuous measurements without collecting aliquots.

Keywords: biodiesel, density measurements, online continuous monitoring, synthesis

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Authors: Samir Hessas

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Modern medicine is witnessing a profound transformation as advanced technology reshapes surgical environments. Hybrid operating rooms, where state-of-the-art medical equipment, advanced imaging solutions, and Artificial Intelligence (AI) converge, are at the forefront of this revolution. In this comprehensive exploration, we scrutinize the multifaceted facets of AI and delve into an array of groundbreaking technologies. We also discuss visionary concepts that hold the potential to revolutionize hybrid operating rooms, making them more efficient and patient-centered. These innovations encompass real-time imaging, surgical simulation, IoT and remote monitoring, 3D printing, telemedicine, quantum computing, and nanotechnology. The outcome of this fusion of technology and imagination is a promising future of surgical precision, individualized patient care, and unprecedented medical advances in hybrid operating rooms.

Keywords: artificial intelligence, hybrid operating rooms, telemedicine, monitoring

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Authors: M. Bassoui, M. Ferfra, M. Chrayagne

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This paper presents a qualitative modeling for the nonlinear B-H curve of the saturable magnetic materials for a transformer with shunts used in the power supply for the magnetron. This power supply is composed of a single phase leakage flux transformer supplying a cell composed of a capacitor and a diode, which double the voltage and stabilize the current, and a single magnetron at the output of the cell. A procedure consisting of a fuzzy clustering method and a rule processing algorithm is then employed for processing the constructed fuzzy modeling rules to extract the qualitative properties of the curve.

Keywords: B(H) curve, fuzzy clustering, magnetron, power supply

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Authors: Sarah Odofin, Zhiwei Gao

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Operations and maintenance of wind turbine have received much attention by researcher due to rapid expansion of wind farms. This paper explores a novel fault diagnosis that is designed and optimized to be very sensitive to faults and robust to disturbances. The faults considered are the sensor faults of which the augmented observer is considered to enlarge faults and to be robust to disturbance. A qualitative model based analysis is proposed for early fault diagnosis to minimize downtime mostly caused by components breakdown and exploit productivity. Simulation results are computed validating the models provided which demonstrates system performance using practical application of fault type examples. The results demonstrate the effectiveness of the developed techniques investigated in a Matlab/Simulink environment.

Keywords: wind turbine, condition monitoring, genetic algorithm, fault diagnosis, augmented observer, disturbance robustness, fault estimation, sensor monitoring

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Authors: Abdulla Almulla, Wafaa Mahdi

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Building materials can make a significant contribution to the level of natural radioactivity in closed dwelling areas. Therefore, developing an expert system for monitoring the activity concentrations (ACs) of naturally occurring radioactive materials (NORMs) existing in building materials is useful for limiting the population’s exposure to gamma radiation emitted from those materials. The present work not only is aimed at examining the indoor radon concentration emitted by the building materials that are originated from various countries but are commercially available in Kuwait, but also is aimed at developing an expert system for monitoring the radiation emitted from these materials and classifying it as normal (acceptable) or dangerous (unacceptable). This system makes it possible to always monitor any radiological risks to human health. When detecting high doses of radiation, the system gives warning messages.

Keywords: building materials, NORMs, HNBRA, radionuclides, activity concentrations, expert systems

Procedia PDF Downloads 138

Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Manikandan S. P., Sharmila N.

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Pain in the neck, intermediate and anterior, and even low back may occur in one or more locations. Numerous factors can lead to back discomfort, which can manifest into sensations in the other parts of your body. Up to 80% of people will have low back problems at a certain stage of their lives, making spine-related pain a highly prevalent ailment. Roughly twice as commonly as neck pain, low back discomfort also happens about as often as knee pain. According to current studies, using digital devices for extended periods of time and poor sitting posture are the main causes of neck and low back pain. There are numerous monitoring techniques provided to enhance the sitting posture for the aforementioned problems. A sophisticated technique to monitor the extended sitting position is suggested in this research based on this problem. The system is made up of an inertial measurement unit, a T-shirt, an Arduino board, a buzzer, and a mobile app with cloud services. Based on the anatomical position of the spinal cord, the inertial measurement unit was positioned on the inner back side of the T-shirt. The IMU (inertial measurement unit) sensor will evaluate the hip position, imbalanced shoulder, and bending angle. Based on the output provided by the IMU, the data will be analyzed by Arduino, supplied through the cloud, and shared with a mobile app for continuous monitoring. The buzzer will sound if the measured data is mismatched with the human body's natural position. The implementation and data prediction with design to identify balanced and unbalanced posture using a posture monitoring t-shirt will be further discussed in this research article.

Keywords: IMU, posture, IOT, textile

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Authors: Manuel Rosales, Francisco Agrela, Julia Rosales

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The development of concrete pavements that include recycled waste with active and predictive safety features is a possible approach to mitigate the harmful impacts of the construction industry, such as CO2 emissions and the consumption of energy and natural resources during the construction and maintenance of road infrastructure. This study establishes the basis for formulating new smart materials for concrete pavements and carrying out the in-situ implementation of an experimental road section. To this end, a comprehensive recycled pavement solution is developed that combines eco-hybrid cement made with 25% mixed recycled aggregate powder (pMRA) and biomass bottom ash powder (pBBA) and a 30% substitution of natural aggregate by MRA and BBA. This work is grouped in three lines. 1) construction materials with high rates of use of recycled material, 2) production processes with efficient consumption of natural resources and use of cleaner energies, and 3) implementation and monitoring of road section with sustainable concrete made from waste. The objective of this study is to ensure satisfactory rheology, mechanical strength, durability, and CO2 capture of pavement concrete manufactured from waste and its subsequent application in real road section as well as its monitoring to establish the optimal range of recycled material. The concrete developed during this study are aimed at the reuse of waste, promoting the circular economy. For this purpose, and after having carried out different tests in the laboratory, three mixtures were established to be applied on the experimental road.

Keywords: biomass bottom ash, construction and demolition waste, recycled concrete pavements, full-scale experimental road, monitoring

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Authors: Andrew Youssef, David Matthews, Jie Pan

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Identifying the magnitude and direction of a force on an elastic solid is highly desirable, as this allows for investigation and continual monitoring of the dynamic loading. This was traditionally conducted by connecting the solid to the supporting structure by multi-axial force transducer, providing that the transducer will not change the mounting conditions. Polyvinylidene fluoride (PVDF) film is a versatile force transducer that can be easily embedded in structures. Here a PVDF sensor array is embedded inside a simple structure in an effort to determine the force vector applied to the structure is an inverse problem. In this paper, forces of different magnitudes and directions where applied to the structure with an impact hammer, and the output of the PVDF was captured and processed to gain an estimate of the forces applied by the hammer. The outcome extends the scope of application of PVDF sensors for measuring the external or contact force vectors.

Keywords: embedded sensor, monitoring, PVDF, vibration

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Authors: Chen Zhang, Nan Chen

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High-dimensional process monitoring becomes increasingly important in many application domains, where usually the process distribution is unknown and much more complicated than the normal distribution, and the between-stream correlation can not be neglected. However, since the process dimension is generally much bigger than the reference sample size, most traditional nonparametric multivariate control charts fail in high-dimensional cases due to the curse of dimensionality. Furthermore, when the process goes out of control, the influenced variables are quite sparse compared with the whole dimension, which increases the detection difficulty. Targeting at these issues, this paper proposes a new nonparametric monitoring scheme for high-dimensional processes. This scheme first projects the high-dimensional process into several subprocesses using random projections for dimension reduction. Then, for every subprocess with the dimension much smaller than the reference sample size, a local nonparametric control chart is constructed based on the spatial rank test to detect changes in this subprocess. Finally, the results of all the local charts are fused together for decision. Furthermore, after an out-of-control (OC) alarm is triggered, a diagnostic framework is proposed. using the square-root LASSO. Numerical studies demonstrate that the chart has satisfactory detection power for sparse OC changes and robust performance for non-normally distributed data, The diagnostic framework is also effective to identify truly changed variables. Finally, a real-data example is presented to demonstrate the application of the proposed method.

Keywords: random projection, high-dimensional process control, spatial rank, sequential change detection

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Authors: Vladislav Grigorovitch, Marina Grigorovitch, David Pearlmutter, Erez Gal

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The concept of “electric island” is involved with achieving the balance between the self-power generation ability of each educational institution and energy consumption demand. Photo-Voltaic (PV) solar system installed on the roofs of educational buildings is a common way to absorb the available solar energy and generate electricity for self-consumption and even for returning to the grid. The main objective of this research is to develop and implement an “electric island” monitoring infrastructure for promoting energy efficiency in educational buildings. A microscale monitoring methodology will be developed to provide a platform to estimate energy consumption performance classified by rooms and subspaces rather than the more common macroscale monitoring of the whole building. The monitoring platform will be established on the experimental sites, enabling an estimation and further analysis of the variety of environmental and physical conditions. For each building, separate measurement configurations will be applied taking into account the specific requirements, restrictions, location and infrastructure issues. The direct results of the measurements will be analyzed to provide deeper understanding of the impact of environmental conditions and sustainability construction standards, not only on the energy demand of public building, but also on the energy consumption habits of the children that study in those schools and the educational and administrative staff that is responsible for providing the thermal comfort conditions and healthy studying atmosphere for the children. A monitoring methodology being developed in this research is providing online access to real-time data of Interferential Therapy (IFTs) from any mobile phone or computer by simply browsing the dedicated website, providing powerful tools for policy makers for better decision making while developing PV production infrastructure to achieve “electric islands” in educational buildings. A detailed measurement configuration was technically designed based on the specific conditions and restriction of each of the pilot buildings. A monitoring and analysis methodology includes a large variety of environmental parameters inside and outside the schools to investigate the impact of environmental conditions both on the energy performance of the school and educational abilities of the children. Indoor measurements are mandatory to acquire the energy consumption data, temperature, humidity, carbon dioxide and other air quality conditions in different parts of the building. In addition to that, we aim to study the awareness of the users to the energy consideration and thus the impact on their energy consumption habits. The monitoring of outdoor conditions is vital for proper design of the off-grid energy supply system and validation of its sufficient capacity. The suggested outcomes of this research include: 1. both experimental sites are designed to have PV production and storage capabilities; 2. Developing an online information feedback platform. The platform will provide consumer dedicated information to academic researchers, municipality officials and educational staff and students; 3. Designing an environmental work path for educational staff regarding optimal conditions and efficient hours for operating air conditioning, natural ventilation, closing of blinds, etc.

Keywords: sustainability, electric island, IOT, smart building

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Authors: Ming-Kwei Lee, Chih-Feng Yen

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The electrical characteristics of liquid phase deposited silicon oxynitride film on ammonium sulfide treated p-type (100) gallium arsenide substrate were investigated. Hydrofluosilicic acid, ammonia and boric acid aqueous solutions were used as precursors. The electrical characteristics of silicon oxynitride film are much improved on gallium arsenide substrate with ammonium sulfide treatment. With post-metallization annealing, hydrogen ions can further passivate defects in SiON/GaAs film and interface. The leakage currents can reach 7.1 × 10-8 and 1.8 × 10-7 at ± 2 V. The dielectric constant and effective oxide charges are 5.6 and -5.3 × 1010 C/cm2, respectively. The hysteresis offset of hysteresis loop is merely 0.09 V.

Keywords: liquid phase deposition, SiON, GaAs, PMA, (NH4)2S

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Authors: Rahil Samani, Saeed Soleimani, Ehsan Adib, Majid Pahlevani

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This paper presents an inverting high step-up DC/DC converter. Basically, this high step-up DC/DC converter is an appealing interface for solar applications. The proposed topology takes advantage of using coupled inductors. Due to the leakage inductances of these coupled inductors, the power MOSFET has the zero current switching (ZCS) condition, which results in decreased switching losses. This will substantially improve the overall efficiency of the power converter. Furthermore, employing coupled inductors has led to a higher voltage gain. Theoretical analysis and experimental results of a 100W 20V/220V prototype are presented to verify the superior performance of the proposed DC/DC converter.

Keywords: coupled inductors, high step-up DC/DC converter, zero-current switching, Cuk converter, SEPIC converter

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Authors: Sherif Keddis, Rafik Mitry, Norbert Schwesinger

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Intelligent networking of devices has rapidly been gaining importance over the past years and with recent advances in the fields of microcontrollers, integrated circuits and wireless communication, low power applications have emerged, enabling this trend even more. Connected devices provide a much larger database thus enabling highly intelligent and accurate systems. Ensuring safe drinking water is one of the fields that require constant monitoring and can benefit from an increased accuracy. Monitoring is mainly achieved either through complex measures, such as collecting samples from the points of use, or through metering systems typically distant to the points of use which deliver less accurate assessments of the quality of water. Constant metering near the points of use is complicated due to their inaccessibility; e.g. buried water pipes, locked spaces, which makes system maintenance extremely difficult and often unviable. The research presented here attempts to overcome this challenge by providing these systems with enough energy through a flow harvester inside the pipe thus eliminating the maintenance requirements in terms of battery replacements or containment of leakage resulting from wiring such systems. The proposed flow harvester exploits the piezoelectric properties of polyvinylidene difluoride (PVDF) films to convert turbulence induced oscillations into electrical energy. It is intended to be used in standard water pipes with diameters between 0.5 and 1 inch. The working principle of the harvester uses a ring shaped bluff body inside the pipe to induce pressure fluctuations. Additionally the bluff body houses electronic components such as storage, circuitry and RF-unit. Placing the piezoelectric films downstream of that bluff body causes their oscillation which generates electrical charge. The PVDF-film is placed as a multilayered wrap fixed to the pipe wall leaving the top part to oscillate freely inside the flow. The warp, which allows for a larger active, consists of two layers of 30µm thick and 12mm wide PVDF layered alternately with two centered 6µm thick and 8mm wide aluminum foil electrodes. The length of the layers depends on the number of windings and is part of the investigation. Sealing the harvester against liquid penetration is achieved by wrapping it in a ring-shaped LDPE-film and welding the open ends. The fabrication of the PVDF-wraps is done by hand. After validating the working principle using a wind tunnel, experiments have been conducted in water, placing the harvester inside a 1 inch pipe at water velocities of 0.74m/s. To find a suitable placement of the wrap inside the pipe, two forms of fixation were compared regarding their power output. Further investigations regarding the number of windings required for efficient transduction were made. Best results were achieved using a wrap with 3 windings of the active layers which delivers a constant power output of 0.53µW at a 2.3MΩ load and an effective voltage of 1.1V. Considering the extremely low power requirements of sensor applications, these initial results are promising. For further investigations and optimization, machine designs are currently being developed to automate the fabrication and decrease tolerance of the prototypes.

Keywords: maintenance-free sensors, measurements at point of use, piezoelectric flow harvesting, universal micro generator, wireless metering systems

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Authors: T. V. Dinh, I. Y. Choi, J. W. Ahn, Y. H. Oh, G. Bo, J. Y. Lee, J. C. Kim

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A Non-Dispersive Infrared (NDIR) multi-gas analyzer has been developed to monitor the emission of carbon monoxide (CO) and sulfur dioxide (SO2) from various industries. The NDIR technique for gas measurement is based on the wavelength absorption in the infrared spectrum as a way to detect particular gasses. NDIR analyzers have popularly applied in the Tele-Monitoring System (TMS). The advantage of the NDIR analyzer is low energy consumption and cost compared with other spectroscopy methods. However, zero/span drift and interference are its urgent issues to be solved. Multi-pathway technique based on optical White cell was employed to improve the sensitivity of the analyzer in this work. A pyroelectric detector was used to detect the Infrared radiation. The analytical range of the analyzer was 0 ~ 200 ppm. The instrument response time was < 2 min. The detection limits of CO and SO2 were < 4 ppm and < 6 ppm, respectively. The zero and span drift of 24 h was less than 3%. The linearity of the analyzer was less than 2.5% of reference values. The precision and accuracy of both CO and SO2 channels were < 2.5% of relative standard deviation. In general, the analyzer performed well. However, the detection limit and 24h drift should be improved to be a more competitive instrument.

Keywords: analyzer, CEMS, monitoring, NDIR, TMS

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Authors: Wojciech Dąbrowski, Joanna Bąk, Laurent Solliec

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Nowadays technical and technological progress and constant development of methods and devices applied to sanitary engineering is indispensable. Issues related to sanitary engineering involve flow measurements for water and wastewater. The precise measurement is very important and pivotal for further actions, like monitoring. There are many methods and techniques of flow measurement in the area of sanitary engineering. Weirs and flumes are well–known methods and common used. But also there are alternative methods. Some of them are very simple methods, others are solutions using high technique. The old–time method combined with new technique could be more useful than earlier. Paper describes substitute method of flow gauging (California pipe method) and proposal of modification of this method used for inclined pipe. Examination of possibility of improving and developing old–time methods is direction of the investigation.

Keywords: California pipe, sewerage, flow rate measurement, water, wastewater, improve, modification, hydraulic monitoring, stream

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Authors: Tasnuva Tamanna, Aimin Yu

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Application of nanoscience in biomedical field has come across as a new era. This study involves the synthesis of nano drug carrier with antibiotic loading. Based on the founding that polydopamine (PDA) nanoparticles could be formed via self-polymerization of dopamine at alkaline pH, one-step synthesis of rifampicin coupled polydopamine (PDA-R) nanoparticles was achieved by adding rifampicin into the dopamine solution. The successful yield of PDA nanoparticles with or without the presence of rifampicin during the polymerization process was characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, and Raman spectroscopy. Drug loading was monitored by UV-vis spectroscopy and the loading efficiency of rifampicin was calculated to be 76%. Such highly capacious nano-reservoir was found very stable with little drug leakage at pH 3.

Keywords: drug loading, nanoparticles, polydopamine, rifampicin

Procedia PDF Downloads 453

Authors: Auwal Abubakar, Shazril Imran Shaukat, Noor Khairiah A. Karim, Mohammed Zakir Kassim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

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Background: Voluntary deep inspiration breath-hold radiotherapy (vDIBH-RT) is an effective cardiac dose reduction technique during left breast radiotherapy. This study aimed to assess the accuracy of the implementation of the vDIBH technique among left breast cancer patients without the use of a special device such as a surface-guided imaging system. Methods: The vDIBH-RT technique was implemented among thirteen (13) left breast cancer patients at the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia. Breath-hold monitoring was performed based on breath-hold skin marks and laser light congruence observed on zoomed CCTV images from the control console during each delivery. The initial setup was verified using cone beam computed tomography (CBCT) during breath-hold. Each field was delivered using multiple beam segments to allow a delivery time of 20 seconds, which can be tolerated by patients in breath-hold. The data were analysed using an in-house developed MATLAB algorithm. PTV margin was computed based on van Herk's margin recipe. Results: The setup error analysed from CBCT shows that the population systematic error in lateral (x), longitudinal (y), and vertical (z) axes was 2.28 mm, 3.35 mm, and 3.10 mm, respectively. Based on the CBCT image guidance, the Planning target volume (PTV) margin that would be required for vDIBH-RT using CCTV/Laser monitoring technique is 7.77 mm, 10.85 mm, and 10.93 mm in x, y, and z axes, respectively. Conclusion: It is feasible to safely implement vDIBH-RT among left breast cancer patients without special equipment. The breath-hold monitoring technique is cost-effective, radiation-free, easy to implement, and allows real-time breath-hold monitoring.

Keywords: vDIBH, cone beam computed tomography, radiotherapy, left breast cancer

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Authors: Catalina Albornoz, Giacomo Barbieri

Abstract:

Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

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Authors: Neda Navidi, Rene Jr. Landry

Abstract:

Vehicle tracking and accident recognizing are considered by many industries like insurance and vehicle rental companies. The main goal of this paper is to detect the location of a car accident by combining different methods. The methods, which are considered in this paper, are Global Navigation Satellite Systems/Inertial Measurement Units (GNSS/IMU)-based navigation and vehicle accident detection algorithms. They are expressed by a set of raw measurements, which are obtained from a designed integrator black box using GNSS and inertial sensors. Another concern of this paper is the definition of accident detection algorithm based on its jerk to identify the position of that accident. In fact, the results convinced us that, even in GNSS blockage areas, the position of the accident could be detected by GNSS/INS integration with 50% improvement compared to GNSS stand alone.

Keywords: driver behavior monitoring, integration, IMU, GNSS, monitoring, tracking

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Authors: Ritsuko Kawasaki, Takeshi Hiromatsu

Abstract:

Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

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Authors: Kholoud Abdulaziz, Kholoud Al-Najdi, Abdullah Kadri, Konstantinos E. Kakosimos

Abstract:

The Middle East area is highly affected by air pollution induced by anthropogenic and natural phenomena. There is evidence that air pollution, especially particulates, greatly affects the population health. Many studies have raised a warning of the high concentration of particulates and their affect not just around industrial and construction areas but also in the immediate working and living environment. One of the methods to study air quality is continuous and periodic monitoring using active or passive samplers. Active monitoring and sampling are the default procedures per the European and US standards. However, in many cases they have been inefficient to accurately capture the spatial variability of air pollution due to the small number of installations; which eventually is attributed to the high cost of the equipment and the limited availability of users with expertise and scientific background. Another alternative has been found to account for the limitations of the active methods that is the passive sampling. It is inexpensive, requires no continuous power supply, and easy to assemble which makes it a more flexible option, though less accurate. This study aims to investigate and evaluate the use of passive sampling for particulate matter pollution monitoring in dry tropical climates, like in the Middle East. More specifically, a number of field measurements have be conducted, both indoors and outdoors, at Qatar and the results have been compared with active sampling equipment and the reference methods. The samples have been analyzed, that is to obtain particle size distribution, by applying existing laboratory techniques (optical microscopy) and by exploring new approaches like the white light interferometry to. Then the new parameters of the well-established model have been calculated in order to estimate the atmospheric concentration of particulates. Additionally, an extended literature review will investigate for new and better models. The outcome of this project is expected to have an impact on the public, as well, as it will raise awareness among people about the quality of life and about the importance of implementing research culture in the community.

Keywords: air pollution, passive samplers, interferometry, indoor, outdoor

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