Search results for: remote monitoring system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19930

Search results for: remote monitoring system

19300 Cost-Effective Indoor-Air Quality (IAQ) Monitoring via Cavity Enhanced Photoacoustic Technology

Authors: Jifang Tao, Fei Gao, Hong Cai, Yuan Jin Zheng, Yuan Dong Gu

Abstract:

Photoacoustic technology is used to measure effect absorption of a light by means of acoustic detection, which provides a high sensitive, low-cross response, cost-effective solution for gas molecular detection. In this paper, we proposed an integrated photoacoustic sensor for Indoor-air quality (IAQ) monitoring. The sensor consists of an acoustically resonant cavity, a high silicon acoustic transducer chip, and a low-cost light source. The light is modulated at the resonant frequency of the cavity to create an enhanced periodic heating and result in an amplified acoustic pressure wave. The pressure is readout by a novel acoustic transducer with low noise. Based on this photoacoustic sensor, typical indoor gases, including CO2, CO, O2, and H2O have been successfully detected, and their concentration are also evaluated with very high accuracy. It has wide potential applications in IAQ monitoring for agriculture, food industry, and ventilation control systems used in public places, such as schools, hospitals and airports.

Keywords: indoor-air quality (IAQ) monitoring, photoacoustic gas sensor, cavity enhancement, integrated gas sensor

Procedia PDF Downloads 653
19299 A DOE Study of Ultrasound Intensified Removal of Phenol

Authors: P. R. Rahul, A. Kannan

Abstract:

Ultrasound-aided adsorption of phenol by Granular Activated Carbon (GAC) was investigated at different frequencies ranging from 35 kHz, 58 kHz, and 192 kHz. Other factors influencing adsorption such as Adsorbent dosage (g/L), the initial concentration of the phenol solution (ppm) and RPM was also considered along with the frequency variable. However, this study involved calorimetric measurements which helped is determining the effect of frequency on the % removal of phenol from the power dissipated to the system was normalized. It was found that low frequency (35 kHz) cavitation effects had a profound influence on the % removal of phenol per unit power. This study also had cavitation mapping of the ultrasonic baths, and it showed that the effect of cavitation on the adsorption system is irrespective of the position of the vessel. Hence, the vessel was placed at the center of the bath. In this study, novel temperature control and monitoring system to make sure that the system is under proper condition while operations. From the BET studies, it was found that there was only 5% increase in the surface area and hence it was concluded that ultrasound doesn’t profoundly alter the equilibrium value of the adsorption system. DOE studies indicated that adsorbent dosage has a higher influence on the % removal in comparison with other factors.

Keywords: ultrasound, adsorption, granulated activated carbon, phenol

Procedia PDF Downloads 280
19298 A Machine Learning Approach for Anomaly Detection in Environmental IoT-Driven Wastewater Purification Systems

Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

Abstract:

The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

Procedia PDF Downloads 145
19297 Improvement of Environment and Climate Change Canada’s Gem-Hydro Streamflow Forecasting System

Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

Abstract:

A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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19296 Relocation of the Air Quality Monitoring Stations Network for Aburrá Valley Based on Local Climatic Zones

Authors: Carmen E. Zapata, José F. Jiménez, Mauricio Ramiréz, Natalia A. Cano

Abstract:

The majority of the urban areas in Latin America face the challenges associated with city planning and development problems, attributed to human, technical, and economical factors; therefore, we cannot ignore the issues related to climate change because the city modifies the natural landscape in a significant way transforming the radiation balance and heat content in the urbanized areas. These modifications provoke changes in the temperature distribution known as “the heat island effect”. According to this phenomenon, we have the need to conceive the urban planning based on climatological patterns that will assure its sustainable functioning, including the particularities of the climate variability. In the present study, it is identified the Local Climate Zones (LCZ) in the Metropolitan Area of the Aburrá Valley (Colombia) with the objective of relocate the air quality monitoring stations as a partial solution to the problem of how to measure representative air quality levels in a city for a local scale, but with instruments that measure in the microscale.

Keywords: air quality, monitoring, local climatic zones, valley, monitoring stations

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19295 Multi-Temporal Remote Sensing of landscape Dynamics and Pattern Changes in Dire District, Southern Oromia, Ethiopia

Authors: K. Berhanu

Abstract:

Improper land use results in land degradation and decline in agricultural productivity. Hence, in order to get maximum benefits out of land, proper utilization of its resources is inevitable. The present study was aimed at identifying the landcover changes in the study area in the last 25 years and determines the extent and direction of change that has occurred. The study made use of Landsat TM 1986 and 2011 Remote Sensing Satellite Image for analysis to determine the extent and pattern of rangeland change. The results of the landuse/landcover change detection showed that in the last 25 years, 3 major changes were observed, grassland and open shrub-land resource significantly decreased at a rate of 17.1km2/year and 12 km2/year/, respectively. On the other hand in 25 years dense bushland, open bush land, dense shrubland and cultivated land has shown increment in size at a rate of 0.23km2/year,13.5 km2/year, 6.3 km2/year and 0.2 km2/year, respectively within 25 years. The expansion of unpalatable woody species significantly reduced the rangeland size and availability of grasses. The consequence of the decrease in herbaceous biomass production might result in high risk of food insecurity in the area unless proper interventions are made in time.

Keywords: GIS and remote sensing, Dire District, land use/land cover, land sat TM

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19294 Agile Real-Time Field Programmable Gate Array-Based Image Processing System for Drone Imagery in Digital Agriculture

Authors: Sabiha Shahid Antora, Young Ki Chang

Abstract:

Along with various farm management technologies, imagery is an important tool that facilitates crop assessment, monitoring, and management. As a consequence, drone imaging technology is playing a vital role to capture the state of the entire field for yield mapping, crop scouting, weed detection, and so on. Although it is essential to inspect the cultivable lands in real-time for making rapid decisions regarding field variable inputs to combat stresses and diseases, drone imagery is still evolving in this area of interest. Cost margin and post-processing complexions of the image stream are the main challenges of imaging technology. Therefore, this proposed project involves the cost-effective field programmable gate array (FPGA) based image processing device that would process the image stream in real-time as well as providing the processed output to support on-the-spot decisions in the crop field. As a result, the real-time FPGA-based image processing system would reduce operating costs while minimizing a few intermediate steps to deliver scalable field decisions.

Keywords: real-time, FPGA, drone imagery, image processing, crop monitoring

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19293 Metal-Oxide-Semiconductor-Only Process Corner Monitoring Circuit

Authors: Davit Mirzoyan, Ararat Khachatryan

Abstract:

A process corner monitoring circuit (PCMC) is presented in this work. The circuit generates a signal, the logical value of which depends on the process corner only. The signal can be used in both digital and analog circuits for testing and compensation of process variations (PV). The presented circuit uses only metal-oxide-semiconductor (MOS) transistors, which allow increasing its detection accuracy, decrease power consumption and area. Due to its simplicity the presented circuit can be easily modified to monitor parametrical variations of only n-type and p-type MOS (NMOS and PMOS, respectively) transistors, resistors, as well as their combinations. Post-layout simulation results prove correct functionality of the proposed circuit, i.e. ability to monitor the process corner (equivalently die-to-die variations) even in the presence of within-die variations.

Keywords: detection, monitoring, process corner, process variation

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19292 Automated Feature Extraction and Object-Based Detection from High-Resolution Aerial Photos Based on Machine Learning and Artificial Intelligence

Authors: Mohammed Al Sulaimani, Hamad Al Manhi

Abstract:

With the development of Remote Sensing technology, the resolution of optical Remote Sensing images has greatly improved, and images have become largely available. Numerous detectors have been developed for detecting different types of objects. In the past few years, Remote Sensing has benefited a lot from deep learning, particularly Deep Convolution Neural Networks (CNNs). Deep learning holds great promise to fulfill the challenging needs of Remote Sensing and solving various problems within different fields and applications. The use of Unmanned Aerial Systems in acquiring Aerial Photos has become highly used and preferred by most organizations to support their activities because of their high resolution and accuracy, which make the identification and detection of very small features much easier than Satellite Images. And this has opened an extreme era of Deep Learning in different applications not only in feature extraction and prediction but also in analysis. This work addresses the capacity of Machine Learning and Deep Learning in detecting and extracting Oil Leaks from Flowlines (Onshore) using High-Resolution Aerial Photos which have been acquired by UAS fixed with RGB Sensor to support early detection of these leaks and prevent the company from the leak’s losses and the most important thing environmental damage. Here, there are two different approaches and different methods of DL have been demonstrated. The first approach focuses on detecting the Oil Leaks from the RAW Aerial Photos (not processed) using a Deep Learning called Single Shoot Detector (SSD). The model draws bounding boxes around the leaks, and the results were extremely good. The second approach focuses on detecting the Oil Leaks from the Ortho-mosaiced Images (Georeferenced Images) by developing three Deep Learning Models using (MaskRCNN, U-Net and PSP-Net Classifier). Then, post-processing is performed to combine the results of these three Deep Learning Models to achieve a better detection result and improved accuracy. Although there is a relatively small amount of datasets available for training purposes, the Trained DL Models have shown good results in extracting the extent of the Oil Leaks and obtaining excellent and accurate detection.

Keywords: GIS, remote sensing, oil leak detection, machine learning, aerial photos, unmanned aerial systems

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19291 Performance of the Aptima® HIV-1 Quant Dx Assay on the Panther System

Authors: Siobhan O’Shea, Sangeetha Vijaysri Nair, Hee Cheol Kim, Charles Thomas Nugent, Cheuk Yan William Tong, Sam Douthwaite, Andrew Worlock

Abstract:

The Aptima® HIV-1 Quant Dx Assay is a fully automated assay on the Panther system. It is based on Transcription-Mediated Amplification and real time detection technologies. This assay is intended for monitoring HIV-1 viral load in plasma specimens and for the detection of HIV-1 in plasma and serum specimens. Nine-hundred and seventy nine specimens selected at random from routine testing at St Thomas’ Hospital, London were anonymised and used to compare the performance of the Aptima HIV-1 Quant Dx assay and Roche COBAS® AmpliPrep/COBAS® TaqMan® HIV-1 Test, v2.0. Two-hundred and thirty four specimens gave quantitative HIV-1 viral load results in both assays. The quantitative results reported by the Aptima Assay were comparable those reported by the Roche COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 with a linear regression slope of 1.04 and an intercept on -0.097. The Aptima assay detected HIV-1 in more samples than the Roche assay. This was not due to lack of specificity of the Aptima assay because this assay gave 99.83% specificity on testing plasma specimens from 600 HIV-1 negative individuals. To understand the reason for this higher detection rate a side-by-side comparison of low level panels made from the HIV-1 3rd international standard (NIBSC10/152) and clinical samples of various subtypes were tested in both assays. The Aptima assay was more sensitive than the Roche assay. The good sensitivity, specificity and agreement with other commercial assays make the HIV-1 Quant Dx Assay appropriate for both viral load monitoring and detection of HIV-1 infections.

Keywords: HIV viral load, Aptima, Roche, Panther system

Procedia PDF Downloads 367
19290 Parameter Measurement Systems to Evaluate Performance of Archers

Authors: Muhammad Zikril Hakim Md. Azizi, Norhafizan Ahmad, Raja Ariffin Raja Ghazilla

Abstract:

Postural stability, attention level of the archer and particularly the vibrations of the bow itself plays a prominent role in determining the athletes performance. Many techniques and systems had been developing to monitor the parameters of the archers during training. In Malaysia, archery coaches tend to use non-scientific ways that they are familiar with, to evaluate archer performance. An approach that provides more affordable yet accurate systems to the masses and relatively easy system deployment procedure need to be proposed. Hence, this project will address to fulfil the needs. Three area of the archer parameter were included for data monitoring sensors. Attention level can be measured using EEG sensor, centre of mass linked to the postural stability can be measured by foot pressure sensor, and the bow vibrations in three axis will be relayed by the vibrations sensors placed directly on the bow using wireless sensors. Arduino based microcontroller used to relay all the data back to the interfacing systems. Interface systems will be using Python language and C++ framework for user interface and hardware interfacing systems. All sensor data can be observed in real time using the in-house applications, and each sessions can be saved to common files so that coach and the team can have a further discussion and comparisons.

Keywords: archery, graphical user interface, microcontroller, wireless sensor, monitoring system

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19289 A Versatile Data Processing Package for Ground-Based Synthetic Aperture Radar Deformation Monitoring

Authors: Zheng Wang, Zhenhong Li, Jon Mills

Abstract:

Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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19288 Networked Radar System to Increase Safety of Urban Railroad Crossing

Authors: Sergio Saponara, Luca Fanucci, Riccardo Cassettari, Ruggero Piernicola, Marco Righetto

Abstract:

The paper presents an innovative networked radar system for detection of obstacles in a railway level crossing scenario. This Monitoring System (MS) is able to detect moving or still obstacles within the railway level crossing area automatically, avoiding the need of human presence for surveillance. The MS is also connected to the National Railway Information and Signaling System to communicate in real-time the level crossing status. The architecture is compliant with the highest Safety Integrity Level (SIL4) of the CENELEC standard. The number of radar sensors used is configurable at set-up time and depends on how large the level crossing area can be. At least two sensors are expected and up four can be used for larger areas. The whole processing chain that elaborates the output sensor signals, as well as the communication interface, is fully-digital, was designed in VHDL code and implemented onto a Xilinx Virtex 6.

Keywords: radar for safe mobility, railroad crossing, railway, transport safety

Procedia PDF Downloads 476
19287 The System-Dynamic Model of Sustainable Development Based on the Energy Flow Analysis Approach

Authors: Inese Trusina, Elita Jermolajeva, Viktors Gopejenko, Viktor Abramov

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Global challenges require a transition from the existing linear economic model to a model that will consider nature as a life support system for the development of the way to social well-being in the frame of the ecological economics paradigm. The objective of the article is to present the results of the analysis of socio-economic systems in the context of sustainable development using the systems power (energy flows) changes analyzing method and structural Kaldor's model of GDP. In accordance with the principles of life's development and the ecological concept was formalized the tasks of sustainable development of the open, non-equilibrium, stable socio-economic systems were formalized using the energy flows analysis method. The methodology of monitoring sustainable development and level of life were considered during the research of interactions in the system ‘human - society - nature’ and using the theory of a unified system of space-time measurements. Based on the results of the analysis, the time series consumption energy and economic structural model were formulated for the level, degree and tendencies of sustainable development of the system and formalized the conditions of growth, degrowth and stationarity. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. During the research, the authors calculated and used a system of universal indicators of sustainable development in the invariant coordinate system in energy units. In order to design the future state of socio-economic systems, a concept was formulated, and the first models of energy flows in systems were created using the tools of system dynamics. In the context of the proposed approach and methods, universal sustainable development indicators were calculated as models of development for the USA and China. The calculations used data from the World Bank database for the period from 1960 to 2019. Main results: 1) In accordance with the proposed approach, the heterogeneous energy resources of countries were reduced to universal power units, summarized and expressed as a unified number. 2) The values of universal indicators of the life’s level were obtained and compared with generally accepted similar indicators.3) The system of indicators in accordance with the requirements of sustainable development can be considered as a basis for monitoring development trends. This work can make a significant contribution to overcoming the difficulties of forming socio-economic policy, which is largely due to the lack of information that allows one to have an idea of the course and trends of socio-economic processes. The existing methods for the monitoring of the change do not fully meet this requirement since indicators have different units of measurement from different areas and, as a rule, are the reaction of socio-economic systems to actions already taken and, moreover, with a time shift. Currently, the inconsistency or inconsistency of measures of heterogeneous social, economic, environmental, and other systems is the reason that social systems are managed in isolation from the general laws of living systems, which can ultimately lead to a systemic crisis.

Keywords: sustainability, system dynamic, power, energy flows, development

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19286 Fourier Transform and Machine Learning Techniques for Fault Detection and Diagnosis of Induction Motors

Authors: Duc V. Nguyen

Abstract:

Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest bene t based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

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19285 Time-Frequency Modelling and Analysis of Faulty Rotor

Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

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In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub

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19284 A Leaf-Patchable Reflectance Meter for in situ Continuous Monitoring of Chlorophyll Content

Authors: Kaiyi Zhang, Wenlong Li, Haicheng Li, Yifei Luo, Zheng Li, Xiaoshi Wang, Xiaodong Chen

Abstract:

Plant wearable sensors facilitate the real-time monitoring of plant physiological status. In situ monitoring of the plant chlorophyll content over days could provide valuable information on the photosynthetic capacity, nitrogen content, and general plant health. However, it cannot be achieved by current chlorophyll measuring methods. Here, a miniaturized and plant-wearable chlorophyll meter was developed for rapid, non-destructive, in situ, and long-term chlorophyll monitoring. This reflectance-based chlorophyll sensor with 1.5 mm thickness and 0.2 g weight (1000 times lighter than the commercial chlorophyll meter), includes a light emitting diode (LED) and two symmetric photodetectors (PDs) on a flexible substrate and is patched onto the leaf upper epidermis with a conformal light guiding layer. A chlorophyll content index (CCI) calculated based on this sensor shows a better linear relationship with the leaf chlorophyll content (r² > 0.9) than the traditional chlorophyll meter. This meter can wirelessly communicate with a smartphone to monitor the leaf chlorophyll change under various stresses and indicate the unhealthy status of plants for long-term application of plants under various stresses earlier than chlorophyll meter and naked-eye observation. This wearable chlorophyll sensing patch is promising in smart and precision agriculture.

Keywords: plant wearable sensors, reflectance-based measurements, chlorophyll content monitoring, smart agriculture

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19283 Identification of Flood Prone Areas in Adigrat Town Using Boolean Logic with GIS and Remote Sensing Technique

Authors: Fikre Belay Tekulu

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The Adigrat town lies in the Tigray region of Ethiopia. This region is mountainous and experiences a semiarid type of climate. Most of the rainfall occurs in four months of the year, which are June to September. During this season, flood is a common natural disaster, especially in urban areas. In this paper, an attempt is made to identify flood-prone areas in Adigrat town using Boolean logic with GIS and remote sensing techniques. Three parameters were incorporated as land use type, elevation, and slope. Boolean logic was used as land use equal to buildup land, elevation less than 2430 m, and slope less than 5 degrees. As a result, 0.575 km² was identified severely affected by floods during the rainy season.

Keywords: flood, GIS, hydrology, Adigrat

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19282 Transitioning Teacher Identity during COVID-19: An Australian Early Childhood Education Perspective

Authors: J. Jebunnesa, Y. Budd, T. Mason

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COVID-19 changed the pedagogical expectations of early childhood education as many teachers across Australia had to quickly adapt to new teaching practices such as remote teaching. An important factor in the successful implementation of any new teaching and learning approach is teacher preparation, however, due to the pandemic, the transformation to remote teaching was immediate. A timely question to be asked is how early childhood teachers managed the transition from face-to-face teaching to remote teaching and what was learned through this time. This study explores the experiences of early childhood educators in Australia during COVID-19 lockdowns. Data were collected from an online survey conducted through the official Facebook forum of “Early Childhood Education and Care Australia,” and a constructivist grounded theory methodology was used to analyse the data. Initial research results suggest changing expectations of teachers’ roles and responsibilities during the lockdown, with a significant category related to transitioning teacher identities emerging. The concept of transitioning represents the shift from the role of early childhood educator to educational innovator, essential worker, social worker, and health officer. The findings illustrate the complexity of early childhood educators’ roles during the pandemic.

Keywords: changing role of teachers, constructivist grounded theory, lessons learned, teaching during COVID-19

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19281 Normalized Difference Vegetation Index and Hyperspectral: Plant Health Assessment

Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

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The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

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19280 Design of a Mhealth Therapy Management to Maintain Therapy Outcomes after Bariatric Surgery

Authors: A. Dudek, P. Tylec, G. Torbicz, P. Duda, K. Proniewska, P. Major, M. Pedziwiatr

Abstract:

Background: Conservative treatments of obesity, based only on a proper diet and physical activity, without the support of an interdisciplinary team of specialist does not bring satisfactory bariatric results. Long-term maintenance of a proper metabolic results after rapid weight loss due to bariatric surgery requires engagement from patients. Mobile health tool may offer alternative model that enhance participant engagement in keeping the therapy. Objective: We aimed to assess the influence of constant monitoring and subsequent motivational alerts in perioperative period and on post-operative effects in the bariatric patients. As well as the study was designed to identify factors conductive urge to change lifestyle after surgery. Methods: This prospective clinical control study was based on a usage of a designed prototype of bariatric mHealth system. The prepared application comprises central data management with a comprehensible interface dedicated for patients and data transfer module as a physician’s platform. Motivation system of a platform consist of motivational alerts, graphic outcome presentation, and patient communication center. Generated list of patients requiring urgent consultation and possibility of a constant contact with a specialist provide safety zone. 31 patients were enrolled in continuous monitoring program during a 6-month period along with typical follow-up visits. After one year follow-up, all patients were examined. Results: There were 20 active users of the proposed monitoring system during the entire duration of the study. After six months, 24 patients took a part in a control by telephone questionnaires. Among them, 75% confirmed that the application concept was an important element in the treatment. Active users of the application indicated as the most valuable features: motivation to continue treatment (11 users), graphical presentation of weight loss, and other parameters (7 users), the ability to contact a doctor (3 users). The three main drawbacks are technical errors (9 users), tedious questionnaires inside the application (5 users), and time-consuming tasks inside the system (2 users). Conclusions: Constant monitoring and successive motivational alerts to continue treatment is an appropriate tool in the treatment after bariatric surgery, mainly in the early post-operative period. Graphic presentation of data and continuous connection with a clinical staff seemed to be an element of motivation to continue treatment and a sense of security.

Keywords: bariatric surgery, mHealth, mobile health tool, obesity

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19279 To Identify the Importance of Telemedicine in Diabetes and Its Impact on Hba1c

Authors: Sania Bashir

Abstract:

A promising approach to healthcare delivery, telemedicine makes use of communication technology to reach out to remote regions of the world, allowing for beneficial interactions between diabetic patients and healthcare professionals as well as the provision of affordable and easily accessible medical care. The emergence of contemporary care models, fueled by the pervasiveness of mobile devices, provides better information, offers low cost with the best possible outcomes, and is known as digital health. It involves the integration of collected data using software and apps, as well as low-cost, high-quality outcomes. The goal of this study is to assess how well telemedicine works for diabetic patients and how it impacts their HbA1c levels. A questionnaire-based survey of 300 diabetics included 150 patients in each of the groups receiving usual care and via telemedicine. A descriptive and observational study that lasted from September 2021 to May 2022 was conducted. HbA1c has been gathered for both categories every three months. A remote monitoring tool has been used to assess the efficacy of telemedicine and continuing therapy instead of the customary three monthly meetings like in-person consultations. The patients were (42.3) 18.3 years old on average. 128 men were outnumbered by 172 women (57.3% of the total). 200 patients (66.6%) have type 2 diabetes, compared to over 100 (33.3%) candidates for type 1. Despite the average baseline BMI being within normal ranges at 23.4 kg/m², the mean baseline HbA1c (9.45 1.20) indicates that glycemic treatment is not well-controlled at the time of registration. While patients who use telemedicine experienced a mean percentage change of 10.5, those who visit the clinic experienced a mean percentage change of 3.9. Changes in HbA1c are dependent on several factors, including improvements in BMI (61%) after 9 months of research and compliance with healthy lifestyle recommendations for diet and activity. More compliance was achieved by the telemedicine group. It is an undeniable reality that patient-physician communication is crucial for enhancing health outcomes and avoiding long-term issues. Telemedicine has shown its value in the management of diabetes and holds promise as a novel technique for improved clinical-patient communication in the twenty-first century.

Keywords: diabetes, digital health, mobile app, telemedicine

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19278 The Visualization of Hydrological and Hydraulic Models Based on the Platform of Autodesk Civil 3D

Authors: Xiyue Wang, Shaoning Yan

Abstract:

Cities in China today is faced with an increasingly serious river ecological crisis accompanying with the development of urbanization: waterlogging on account of the fragmented urban natural hydrological system; the limited ecological function of the hydrological system caused by a destruction of water system and waterfront ecological environment. Additionally, the eco-hydrological processes of rivers are affected by various environmental factors, which are more complex in the context of urban environment. Therefore, efficient hydrological monitoring and analysis tools, accurate and visual hydrological and hydraulic models are becoming more important basis for decision-makers and an important way for landscape architects to solve urban hydrological problems, formulating sustainable and forward-looking schemes. The study mainly introduces the river and flood analysis model based on the platform of Autodesk Civil 3D. Taking the Luanhe River in Qian'an City of Hebei Province as an example, the 3D models of the landform, river, embankment, shoal, pond, underground stream and other land features were initially built, with which the water transfer simulation analysis, river floodplain analysis, and river ecology analysis were carried out, ultimately the real-time visualized simulation and analysis of rivers in various hypothetical scenarios were realized. Through the establishment of digital hydrological and hydraulic model, the hydraulic data can be accurately and intuitively simulated, which provides basis for rational water system and benign urban ecological system design. Though, the hydrological and hydraulic model based on Autodesk Civil3D own its boundedness: the interaction between the model and other data and software is unfavorable; the huge amount of 3D data and the lack of basic data restrict the accuracy and application range. The hydrological and hydraulic model based on Autodesk Civil3D platform provides more possibility to access convenient and intelligent tool for urban planning and monitoring, a solid basis for further urban research and design.

Keywords: visualization, hydrological and hydraulic model, Autodesk Civil 3D, urban river

Procedia PDF Downloads 289
19277 The Complementary Effect of Internal Control System and Whistleblowing Policy on Prevention and Detection of Fraud in Nigerian Deposit Money Banks

Authors: Dada Durojaye Joshua

Abstract:

The study examined the combined effect of internal control system and whistle blowing policy while it pursues the following specific objectives, which are to: examine the relationship between monitoring activities and fraud’s detection and prevention; investigate the effect of control activities on fraud’s detection and prevention in Nigerian Deposit Money Banks (DMBs). The population of the study comprises the 89,275 members of staff in the 20 DMBs in Nigeria as at June 2019. Purposive and convenient sampling techniques were used in the selection of the 80 members of staff at the supervisory level of the Internal Audit Departments of the head offices of the sampled banks, that is, selecting 4 respondents (Audit Executive/Head, Internal Control; Manager, Operation Risk Management; Head, Financial Crime Control; the Chief Compliance Officer) from each of the 20 DMBs in Nigeria. A standard questionnaire was adapted from 2017/2018 Internal Control Questionnaire and Assessment, Bureau of Financial Monitoring and Accountability Florida Department of Economic Opportunity. It was modified to serve the purpose for which it was meant to serve. It was self-administered to gather data from the 80 respondents at the respective headquarters of the sampled banks at their respective locations across Nigeria. Two likert-scales was used in achieving the stated objectives. A logit regression was used in analysing the stated hypotheses. It was found that effect of monitoring activities using the construct of conduct of ongoing or separate evaluation (COSE), evaluation and communication of deficiencies (ECD) revealed that monitoring activities is significant and positively related to fraud’s detection and prevention in Nigerian DMBS. So also, it was found that control activities using selection and development of control activities (SDCA), selection and development of general controls over technology to prevent financial fraud (SDGCTF), development of control activities that gives room for transparency through procedures that put policies into actions (DCATPPA) contributed to influence fraud detection and prevention in the Nigerian DMBs. In addition, it was found that transparency, accountability, reliability, independence and value relevance have significant effect on fraud detection and prevention ibn Nigerian DMBs. The study concluded that the board of directors demonstrated independence from management and exercises oversight of the development and performance of internal control. Part of the conclusion was that there was accountability on the part of the owners and preparers of the financial reports and that the system gives room for the members of staff to account for their responsibilities. Among the recommendations was that the management of Nigerian DMBs should create and establish a standard Internal Control System strong enough to deter fraud in order to encourage continuity of operations by ensuring liquidity, solvency and going concern of the banks. It was also recommended that the banks create a structure that encourages whistleblowing to complement the internal control system.

Keywords: internal control, whistleblowing, deposit money banks, fraud prevention, fraud detection

Procedia PDF Downloads 74
19276 A Novel Spectral Index for Automatic Shadow Detection in Urban Mapping Based on WorldView-2 Satellite Imagery

Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh

Abstract:

In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically.

Keywords: spectral index, shadow detection, remote sensing images, World-View 2

Procedia PDF Downloads 525
19275 Delivering Safer Clinical Trials; Using Electronic Healthcare Records (EHR) to Monitor, Detect and Report Adverse Events in Clinical Trials

Authors: Claire Williams

Abstract:

Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

Procedia PDF Downloads 80
19274 Complementary Effect of Wistleblowing Policy and Internal Control System on Prevention and Detection of Fraud in Nigerian Deposit Money Banks

Authors: Dada Durojaye Joshua

Abstract:

The study examined the combined effect of internal control system and whistle blowing policy while it pursues the following specific objectives, which are to: examine the relationship between monitoring activities and fraud’s detection and prevention; investigate the effect of control activities on fraud’s detection and prevention in Nigerian Deposit Money Banks (DMBs). The population of the study comprises the 89,275 members of staff in the 20 DMBs in Nigeria as at June 2019. Purposive and convenient sampling techniques were used in the selection of the 80 members of staff at the supervisory level of the Internal Audit Departments of the head offices of the sampled banks, that is, selecting 4 respondents (Audit Executive/Head, Internal Control; Manager, Operation Risk Management; Head, Financial Crime Control; the Chief Compliance Officer) from each of the 20 DMBs in Nigeria. A standard questionnaire was adapted from 2017/2018 Internal Control Questionnaire and Assessment, Bureau of Financial Monitoring and Accountability Florida Department of Economic Opportunity. It was modified to serve the purpose for which it was meant to serve. It was self-administered to gather data from the 80 respondents at the respective headquarters of the sampled banks at their respective locations across Nigeria. Two likert-scales was used in achieving the stated objectives. A logit regression was used in analysing the stated hypotheses. It was found that effect of monitoring activities using the construct of conduct of ongoing or separate evaluation (COSE), evaluation and communication of deficiencies (ECD) revealed that monitoring activities is significant and positively related to fraud’s detection and prevention in Nigerian DMBS. So also, it was found that control activities using selection and development of control activities (SDCA), selection and development of general controls over technology to prevent financial fraud (SDGCTF), development of control activities that gives room for transparency through procedures that put policies into actions (DCATPPA) contributed to influence fraud detection and prevention in the Nigerian DMBs. In addition, it was found that transparency, accountability, reliability, independence and value relevance have significant effect on fraud detection and prevention ibn Nigerian DMBs. The study concluded that the board of directors demonstrated independence from management and exercises oversight of the development and performance of internal control. Part of the conclusion was that there was accountability on the part of the owners and preparers of the financial reports and that the system gives room for the members of staff to account for their responsibilities. Among the recommendations was that the management of Nigerian DMBs should create and establish a standard Internal Control System strong enough to deter fraud in order to encourage continuity of operations by ensuring liquidity, solvency and going concern of the banks. It was also recommended that the banks create a structure that encourages whistleblowing to complement the internal control system.

Keywords: internal control, whistleblowing, deposit money banks, fraud prevention, fraud detection

Procedia PDF Downloads 68
19273 Development of a Non-Dispersive Infrared Multi Gas Analyzer for a TMS

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

Abstract:

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

Procedia PDF Downloads 248
19272 Perceived Barriers and Benefits of Technology-Based Progress Monitoring for Non-Academic Individual Education Program Goals

Authors: A. Drelick, T. Sondergeld, M. Decarlo-Tecce, K. McGinley

Abstract:

In 1975, a free, appropriate public education (FAPE) was granted for all students in the United States regardless of their disabilities. As a result, the special education landscape has been reshaped through new policies and legislation. Progress monitoring, a specific component of an Individual Education Program (IEP) calls, for the use of data collection to determine the appropriateness of services provided to students with disabilities. The recent US Supreme Court ruling in Endrew F. v. Douglas County warrants giving increased attention to student progress, specifically pertaining to improving functional, or non-academic, skills that are addressed outside the general education curriculum. While using technology to enhance data collection has become a common practice for measuring academic growth, its application for non-academic IEP goals is uncertain. A mixed-methods study examined current practices and rationales for implementing technology-based progress monitoring focused on non-academic IEP goals. Fifty-seven participants responded to an online survey regarding their progress monitoring programs for non-academic goals. After isolated analysis and interpretation of quantitative and qualitative results, data were synthesized to produce meta-inferences that drew broader conclusions on the topic. For the purpose of this paper, specific focus will be placed on the perceived barriers and benefits of implementing technology-based progress monitoring protocols for non-academic IEP goals. The findings of this study highlight facts impacting the use of technology-based progress monitoring. Perceived barriers to implementation include: (1) lack of training, (2) access to technology, (3) outdated or inoperable technology, (4) reluctance to change, (5) cost, (6) lack of individualization within technology-based programs, and (7) legal issues in special education; while perceived benefits include: (1) overall ease of use, (2) accessibility, (3) organization, (4) potential for improved presentation of data, (5) streamlining the progress-monitoring process, and (6) legal issues in special education. Based on these conclusions, recommendations are made to IEP teams, school districts, and software developers to improve the progress-monitoring process for functional skills.

Keywords: special education, progress monitoring, functional skills, technology

Procedia PDF Downloads 241
19271 Remote Controlled of In-Situ Forming Thermo-sensitive Hydrogel Nanocomposite for Hyperthermia Therapy Application: Synthesis and Characterizations

Authors: Elbadawy A. Kamoun

Abstract:

Magnetically responsive hydrogel nanocomposite (NCH) based on composites of superparamagnetic of Fe3O4 nano-particles and temperature responsive hydrogel matrices were developed. The nanocomposite hydrogel system based on the temperature sensitive N-isopropylacrylamide hydrogels crosslinked by poly(ethylene glycol)-400 dimethacrylate (PEG400DMA) incorporating with chitosan derivative, was synthesized and characterized. Likewise, the NCH system was synthesized by visible-light free radical photopolymerization, using carboxylated camphorquinone-amine system to avoid the common risks of the use of UV-light especially in hyperthermia treatment. Superparamagnetic of iron oxide nanoparticles were introduced into the hydrogel system by polymerizing mixture technique and monomer solution. FT-IR with Raman spectroscopy and Wide angle-XRD analysis were utilized to verify the chemical structure of NCH and exfoliation reaction for nanoparticles, respectively. Additionally, morphological structure of NCH was investigated using SEM and TEM photographs. The swelling responsive of the current nanocomposite hydrogel system with different crosslinking conditions, temperature, magnetic field efficiency, and the presence effect of magnetic nanoparticles were evaluated. Notably, hydrolytic degradation of this system was proved in vitro application. While, in-vivo release profile behavior is under investigation nowadays. Moreover, the compatibility and cytotoxicity tests were previously investigated in our studies for photoinitiating system. These systems show promised polymeric material candidate devices and are expected to have a wide applicability in various biomedical applications as mildly.

Keywords: hydrogel nanocomposites, tempretaure-responsive hydrogel, superparamagnetic nanoparticles, hyperthermia therapy

Procedia PDF Downloads 272