Search results for: driving monitoring

Authors: Xiaobo Liu, Rakesh Mishra, Yun Zhang

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Continuous monitoring of forest canopy height with large coverage is essential for obtaining forest carbon stocks and emissions, quantifying biomass estimation, analyzing vegetation coverage, and determining biodiversity. LiDAR can be used to collect accurate woody vegetation structure such as canopy height. However, LiDAR’s coverage is usually limited because of its high cost and limited maneuverability, which constrains its use for dynamic and large area forest canopy monitoring. On the other hand, optical satellite images, like Sentinel-2, have the ability to cover large forest areas with a high repeat rate, but they do not have height information. Hence, exploring the solution of integrating LiDAR data and Sentinel-2 images to enlarge the coverage of forest canopy height prediction and increase the prediction repeat rate has been an active research topic in the environmental remote sensing community. In this study, we explore the potential of training a Random Forest Regression (RFR) model and a Convolutional Neural Network (CNN) model, respectively, to develop two predictive models for predicting and validating the forest canopy height of the Acadia Forest in New Brunswick, Canada, with a 10m ground sampling distance (GSD), for the year 2018 and 2021. Two 10m airborne LiDAR-derived canopy height models, one for 2018 and one for 2021, are used as ground truth to train and validate the RFR and CNN predictive models. To evaluate the prediction performance of the trained RFR and CNN models, two new predicted canopy height maps (CHMs), one for 2018 and one for 2021, are generated using the trained RFR and CNN models and 10m Sentinel-2 images of 2018 and 2021, respectively. The two 10m predicted CHMs from Sentinel-2 images are then compared with the two 10m airborne LiDAR-derived canopy height models for accuracy assessment. The validation results show that the mean absolute error (MAE) for year 2018 of the RFR model is 2.93m, CNN model is 1.71m; while the MAE for year 2021 of the RFR model is 3.35m, and the CNN model is 3.78m. These demonstrate the feasibility of using the RFR and CNN models developed in this research for predicting large-coverage forest canopy height at 10m spatial resolution and a high revisit rate.

Keywords: remote sensing, forest canopy height, LiDAR, Sentinel-2, artificial intelligence, random forest regression, convolutional neural network

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Authors: James Skon, Irina Beshentseva, Michelle Polak

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Wifi solutions come in two major classes. Small Office/Home Office (SOHO) WiFi, characterized by inexpensive WiFi routers, with one or two service set identifiers (SSIDs), and a single shared passphrase. These access points provide no significant user management or monitoring, and no aggregation of monitoring and control for multiple routers. The other solution class is managed enterprise WiFi solutions, which involve expensive Access Points (APs), along with (also costly) local or cloud based management components. These solutions typically provide portal based login, per user virtual local area networks (VLANs), and sophisticated monitoring and control across a large group of APs. The cost for deploying and managing such managed enterprise solutions is typically about 10 fold that of inexpensive consumer APs. Low revenue organizations, such as schools, non-profits, non-government organizations (NGO's), small businesses, and even homes cannot easily afford quality enterprise WiFi solutions, though they may need to provide quality WiFi access to their population. Using available lower cost Wifi solutions can significantly reduce their ability to provide reliable, secure network access. This project explored and created a new approach for providing secured managed enterprise WiFi based on low cost hardware combined with both new and existing (but modified) open source software. The solution provides a cloud based management interface which allows organizations to aggregate the configuration and management of small, medium and large WiFi solutions. It utilizes a novel approach for user management, giving each user a unique passphrase. It provides unlimited SSID's across an unlimited number of WiFI zones, and the ability to place each user (and all their devices) on their own VLAN. With proper configuration it can even provide user local services. It also allows for users' usage and quality of service to be monitored, and for users to be added, enabled, and disabled at will. As inferred above, the ultimate goal is to free organizations with limited resources from the expense of a commercial enterprise WiFi, while providing them with most of the qualities of such a more expensive managed solution at a fraction of the cost.

Keywords: wifi, enterprise, cloud, managed

Procedia PDF Downloads 97

Authors: Norbert Szulc, Cezary Wieczorkowski, Igor Baranowski

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In this paper, a control system that bridges the gap in support for Unmanned Surface Vessels in the PX4 Opensource Autopilot was developed. The system is designed for an omnidirectional water craft with four motors. A modular autopilot architecture design centred around publish-subscribe interprocess communication was used. The paper presents the implementation and integration process of a generic surface vehicle controller capable of driving any configuration of motors through the recently introduced in control allocator in PX4 autopilot. The proposed approach was successfully tested in a case study through implementation on the ASV Perkoz.

Keywords: control system, PX4, drones, rovers, surface vessels, omnidirectional

Procedia PDF Downloads 87

Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

Procedia PDF Downloads 72

Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

Procedia PDF Downloads 139

Authors: Victor Lopez-Richard, Rafael Schio Wengenroth Silva, Fabian Hartmann

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Memcomputing is a computational paradigm that combines information processing and storage on the same physical platform. Key elements for this topic are devices with an inherent memory, such as memristors, memcapacitors, and meminductors. Despite the widespread emergence of memory effects in various solid systems, a clear understanding of the basic microscopic mechanisms that trigger them is still a puzzling task. We report basic ingredients of the theory of solid-state transport, intrinsic to a wide range of mechanisms, as sufficient conditions for a memristive response that points to the natural emergence of memory. This emergence should be discernible under an adequate set of driving inputs, as highlighted by our theoretical prediction and general common trends can be thus listed that become a rule and not the exception, with contrasting signatures according to symmetry constraints, either built-in or induced by external factors at the microscopic level. Explicit analytical figures of merit for the memory modulation of the conductance are presented, unveiling very concise and accessible correlations between general intrinsic microscopic parameters such as relaxation times, activation energies, and efficiencies (encountered throughout various fields in Physics) with external drives: voltage pulses, temperature, illumination, etc. These building blocks of memory can be extended to a vast universe of materials and devices, with combinations of parallel and independent transport channels, providing an efficient and unified physical explanation for a wide class of resistive memory devices that have emerged in recent years. Its simplicity and practicality have also allowed a direct correlation with reported experimental observations with the potential of pointing out the optimal driving configurations. The main methodological tools used to combine three quantum transport approaches, Drude-like model, Landauer-Buttiker formalism, and field-effect transistor emulators, with the microscopic characterization of nonequilibrium dynamics. Both qualitative and quantitative agreements with available experimental responses are provided for validating the main hypothesis. This analysis also shades light on the basic universality of complex natural impedances of systems out of equilibrium and might help pave the way for new trends in the area of memory formation as well as in its technological applications.

Keywords: memories, memdevices, memristors, nonequilibrium states

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Authors: M. Moreno, M. Alique, D. Otero, C. Delgado, P. Lacharmoise, L. Gracia, L. Pires, A. Moya

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Marine environments are increasingly threatened by heavy metal contamination, including mercury (Hg), lead (Pb), and cadmium (Cd), posing significant risks to ecosystems and human health. Traditional monitoring techniques often fail to provide the spatial and temporal resolution needed for real-time detection of these contaminants, especially in remote or harsh environments. SEAWIZARD addresses these challenges by leveraging the flexibility, adaptability, and cost-effectiveness of printed electronics, with the integration of microfluidics to develop a compact, portable, and reusable sensor platform designed specifically for real-time monitoring of heavy metal ions in seawater. The SEAWIZARD sensor is a multiparametric Lab-on-Chip (LoC) device, a miniaturized system that integrates several laboratory functions into a single chip, drastically reducing sample volumes and improving adaptability. This platform integrates three printed graphene electrodes for the simultaneous detection of Hg, Cd and Pb via square wave voltammetry. These electrodes share the reference and the counter electrodes to improve space efficiency. Additionally, it integrates printed pH and temperature sensors to correct environmental interferences that may impact the accuracy of metal detection. The pH sensor is based on a carbon electrode with iridium oxide electrodeposited while the temperature sensor is graphene based. A protective dielectric layer is printed on top of the sensor to safeguard it in harsh marine conditions. The use of flexible polyethylene terephthalate (PET) as the substrate enables the sensor to conform to various surfaces and operate in challenging environments. One of the key innovations of SEAWIZARD is its integrated microfluidic layer, fabricated from cyclic olefin copolymer (COC). This microfluidic component allows a controlled flow of seawater over the sensing area, allowing for significant improved detection limits compared to direct water sampling. The system’s dual-channel design separates the detection of heavy metals from the measurement of pH and temperature, ensuring that each parameter is measured under optimal conditions. In addition, the temperature sensor is finely tuned with a serpentine-shaped microfluidic channel to ensure precise thermal measurements. SEAWIZARD also incorporates custom electronics that allow for wireless data transmission via Bluetooth, facilitating rapid data collection and user interface integration. Embedded artificial intelligence further enhances the platform by providing an automated alarm system, capable of detecting predefined metal concentration thresholds and issuing warnings when limits are exceeded. This predictive feature enables early warnings of potential environmental disasters, such as industrial spills or toxic levels of heavy metal pollutants, making SEAWIZARD not just a detection tool, but a comprehensive monitoring and early intervention system. In conclusion, SEAWIZARD represents a significant advancement in printed electronics applied to environmental sensing. By combining flexible, low-cost materials with advanced microfluidics, custom electronics, and AI-driven intelligence, SEAWIZARD offers a highly adaptable and scalable solution for real-time, high-resolution monitoring of heavy metals in marine environments. Its compact and portable design makes it an accessible, user-friendly tool with the potential to transform water quality monitoring practices and provide critical data to protect marine ecosystems from contamination-related risks.

Keywords: lab-on-chip, printed electronics, real-time monitoring, microfluidics, heavy metal contamination

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Authors: Xinyi Zhao, Furong Tian

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Mycotoxins are secondary metabolic products of fungi. These are poisonous, carcinogens and mutagens in nature and pose a serious health threat to both humans and animals, causing severe illnesses and even deaths. The rapid, simple and cheap detection methods of mycotoxins are of immense importance and in great demand in the food and beverage industry as well as in agriculture and environmental monitoring. Lateral flow immunochromatographic strips (ICSTs) have been widely used in food safety, environment monitoring. Forty-six papers were identified and reviewed on Google Scholar and Scopus for their limit of detection and nanomaterial on Lateral flow immunochromatographic strips on different types of mycotoxins. The papers were dated 2001-2021. Twenty five papers were compared to identify the lowest limit of detection of among different mycotoxins (Aflatoxin B1: 10, Zearalenone:5, Fumonisin B1: 5, Trichothecene-A: 5). Most of these highly sensitive strips are competitive. Sandwich structure are usually used in large scale detection. In conclusion, the mycotoxin receives that most researches is aflatoxin B1 and its limit of detection is the lowest. Gold-nanopaticle based immunochromatographic test strips has the lowest limit of detection. Five papers involve smartphone detection and they all detect aflatoxin B1 with gold nanoparticles. In these papers, quantitative concentration results can be obtained when the user uploads the photograph of test lines using the smartphone application.

Keywords: aflatoxin B1, limit of detection, gold nanoparticle, lateral flow immunochromatographic strips, mycotoxins

Procedia PDF Downloads 195

Authors: Santos Cabrera, Halbert Yesid, Moncada Nino, Alvaro Fernando, Rincon Cuta, Yeisson Alexis

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The present work evaluates the feasibility of implementing a health and use monitoring system (HUMS), based on vibration analysis as a condition-based maintenance program for the UH60L 'Blackhawk' helicopters. The mixed approach used consists of contributions from national and international experts, the analysis of data extracted from the software (Meridium), the correlation of variables derived from the diagnosis of availability, the development, and application of the HUMS system, the evaluation of the latter through of the use of instruments designed for the collection of information using the DELPHI method and data capture with the device installed in the helicopter studied. The results obtained in the investigation reflect the context of maintenance in aerial operations, a reduction of operation and maintenance costs of over 2%, better use of human resources, improvement in availability (5%), and fulfillment of the aircraft’s security standards, enabling the implementation of the monitoring system (HUMS) in the condition-based maintenance program. New elements are added to the study of maintenance based on condition -specifically, in the determination of viability based on qualitative and quantitative data according to the methodology. The use of condition-based maintenance will allow organizations to adjust and reconfigure their strategic, logistical, and maintenance capabilities, aligning them with their strategic objectives of responding quickly and adequately to changes in the environment and operational requirements.

Keywords: air transportation sustainability, HUMS, maintenance based condition, maintenance blackhawk capability

Procedia PDF Downloads 157

Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

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Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

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Authors: Łukasz Grabowski, Michał Gęca, Mirosław Wendeker

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This paper presents the simulation results of a new opposed piston diesel engine to power a light aircraft. Created in the AVL Boost, the model covers the entire charge passage, from the inlet up to the outlet. The model shows fuel injection into cylinders and combustion in cylinders. The calculation uses the module for two-stroke engines. The model was created using sub-models available in this software that structure the model. Each of the sub-models is complemented with parameters in line with the design premise. Since engine weight resulting from geometric dimensions is fundamental in aircraft engines, two configurations of stroke were studied. For each of the values, there were calculated selected operating conditions defined by crankshaft speed. The required power was achieved by changing air fuel ratio (AFR). There was also studied brake specific fuel consumption (BSFC). For stroke S1, the BSFC was lowest at all of the three operating points. This difference is approximately 1-2%, which means higher overall engine efficiency but the amount of fuel injected into cylinders is larger by several mg for S1. The cylinder maximum pressure is lower for S2 due to the fact that compressor gear driving remained the same and boost pressure was identical in the both cases. Calculations for various values of boost pressure were the next stage of the study. In each of the calculation case, the amount of fuel was changed to achieve the required engine power. In the former case, the intake system dimensions were modified, i.e. the duct connecting the compressor and the air cooler, so its diameter D = 40 mm was equal to the diameter of the compressor outlet duct. The impact of duct length was also examined to be able to reduce the flow pulsation during the operating cycle. For the so selected geometry of the intake system, there were calculations for various values of boost pressure. The boost pressure was changed by modifying the gear driving the compressor. To reach the required level of cruising power N = 68 kW. Due to the mechanical power consumed by the compressor, high pressure ratio results in a worsened overall engine efficiency. The figure on the change in BSFC from 210 g/kWh to nearly 270 g/kWh shows this correlation and the overall engine efficiency is reduced by about 8%. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: aircraft, diesel, engine, simulation

Procedia PDF Downloads 207

Authors: Danijela Vuković, Radovan Čobanović, Milorad Plačkić

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The expansion of population imposes increase in usage of animal meat, on whose quality directly affects the quality of the feed that the animals are fed with. The selection of raw materials, hygiene during the technological process, various hydrothermal treatments, methods of mixing etc. have an influence on the quality of feed. Monitoring of the feed is very important to obtain information about the quality of feed and the possible prevention of animal diseases which can lead to different human diseases outbreaks. In this study parameters of feed safety were monitored. According to the mentioned, the goal of this study was to evaluate microbiological safety of feed (feedstuffs and complete mixtures). Total number of analyzed samples was 4399. Analyzed feed samples were collected in various retail shops and feed factories during the period of 44 months (from January 2013 untill September 2017). Samples were analyzed on Salmonella spp. and Clostridium perfringens in quantity of 50g according to Serbian regulation. All microorganisms were tested according to ISO methodology: Salmonella spp. ISO 6579:2002 and Clostridium perfringens ISO 7937:2004. Out of 4399 analyzed feed samples 97,5% were satisfactory and 2,5% unsatisfactory concerning Salmonella spp. As far as Clostridium perfringens is concerned 100% of analyzed samples were satisfactory. The obtained results suggest that technological processing of feed in Serbia is at high level when it comes to safety and hygiene of the products, but there are still possibilities for progress and improvement which only can be reached trough the permanent monitoring of feed.

Keywords: microbiology, safety, hygiene, feed

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Authors: Emanuele Bonamente, Andrea Aquino, Franco Cotana

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The exploitation of the low-temperature geothermal resource via ground-source heat pumps is often limited by the high investment cost mainly due to borehole drilling. From the monitoring of a prototypal system currently used by a commercial building, it was found that a simple upgrade of the conventional layout, obtained including a thermal storage between the ground-source heat exchangers and the heat pump, can optimize the ground energy exploitation requiring for shorter/fewer boreholes. For typical applications, a reduction of up to 66% with respect to the conventional layout can be easily achieved. Results from the monitoring campaign of the prototype are presented in this paper, and upgrades of the thermal storage using phase change materials (PCMs) are proposed using computational fluid dynamics simulations. The PCM thermal storage guarantees an improvement of the system coefficient of performance both for summer cooling and winter heating (up to 25%). A drastic reduction of the storage volume (approx. 1/10 of the original size) is also achieved, making it possible to easily place it within the technical room, avoiding extra costs for underground displacement. A preliminary optimization of the PCM geometry is finally proposed.

Keywords: computational fluid dynamics (CFD), geothermal energy, ground-source heat pumps, phase change materials (PCM)

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Authors: Nassouh K. Jaber

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Supercapacitors (S.C.) are presently attracting attention for driving general purpose (12VDC to 220VAC) inverters in renewable energy systems. Unfortunately, when the voltage of the S.C supplying the inverter reaches the minimal threshold of 7-8VDC the inverter shuts down leaving the remaining 40% of the valuable energy stored inside the ultracapacitor un-usable. In this work a power electronic circuit is proposed which switches 2 banks of supercapacitors from parallel connection when both are fully charged at 14VDC to serial connection when their voltages drop down to 7 volts, thus keeping the inverter working within its operating limits for a longer time and advantageously tapping almost 92% of the stored energy in the supercapacitors.

Keywords: ultra capacitor, switched ultracapacitors, inverter, supercapacitor, parallel connection, serial connection, battery limitation

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Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

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Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: driver, fuzzy logic, perception reaction time, premise variable

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Authors: George N. Zaimes, Valasia Iakovoglou, Paschalis Koutalakis, Konstantinos Ioannou, Ioannis Kosmadakis, Panagiotis Tsardaklis, Theodoros Laopoulos

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The advancements in technology allow the development of a new system that can continuously measure surface soil erosion. Continuous soil erosion measurements are required in order to comprehend the erosional processes and propose effective and efficient conservation measures to mitigate surface erosion. Mitigating soil erosion, especially in Mediterranean countries such as Greece, is essential in order to maintain environmental and agricultural sustainability. In this paper, we present the Automated Soil Erosion Monitoring System (ASEMS) that measures surface soil erosion along with other factors that impact erosional process. Specifically, this system measures ground level changes (surface soil erosion), rainfall, air temperature, soil temperature and soil moisture. Another important innovation is that the data will be collected by remote communication. In addition, stakeholder’s awareness is a key factor to help reduce any environmental problem. The different dissemination activities that were utilized are described. The overall outcomes were the development of an innovative system that can measure erosion very accurately. These data from the system help study the process of erosion and find the best possible methods to reduce erosion. The dissemination activities enhance the stakeholder's and public's awareness on surface soil erosion problems and will lead to the adoption of more effective soil erosion conservation practices in Greece.

Keywords: soil management, climate change, new technologies, conservation practices

Procedia PDF Downloads 345

Authors: Anand K. Patel

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Background: Patients with COPD have decreased pulmonary functions, which in turn reflect on their day-to-day activities. Objectives: To assess the correlation between functional vital capacity (FVC) and forced expiratory volume in one second (FEV1) with 6 minutes walk test (6MWT). To correlate the Borg rating for perceived exertion scale (Borg scale) and Modified medical research council (MMRC) dyspnea scale with the 6MWT, FVC and FEV1. Method: In this prospective study total 72 patients with COPD diagnosed by the GOLD guidelines were enrolled after taking written consent. They were first asked to rate physical exertion on the Borg scale as well as the modified medical research council dyspnea scale and then were subjected to perform pre and post bronchodilator spirometry followed by 6 minute walk test. The findings were correlated by calculating the Pearson coefficient for each set and obtaining the p-values, with a p < 0.05 being clinically significant. Result: There was a significant correlation between spirometry and 6MWT suggesting that patients with lower measurements were unable to walk for longer distances. However, FVC had the stronger correlation than FEV1. MMRC scale had a stronger correlation with 6MWT as compared to the Borg scale. Conclusion: The study suggests that 6MWT is a better test for monitoring the patients of COPD. In spirometry, FVC should be used in monitoring patients with COPD, instead of FEV1. MMRC scale shows a stronger correlation than the Borg scale, and we should use it more often.

Keywords: spirometry, 6 minute walk test, MMRC, Borg scale

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Authors: Guezouli Larbi, Belkacem Soundes

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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

Procedia PDF Downloads 83

Authors: Altab Hossain, Shakerul Islam, Golamur R. Khan, Abu Zafar M. Salahuddin

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An effective identification of breakdowns is of premier importance for the safe and reliable operation of Nuclear Power Plants (NPP) and its associated facilities. A great number of monitoring and diagnosis methodologies are applied and used worldwide in areas such as industry, automobiles, hospitals, and power plant to detect and reduce human disasters. The potential consequences of several hazardous activities may harm the society using nuclear and its associated facilities. Hence, one of the most popular and effective methods to ensure safety and monitor the entire nuclear facility and imply risk-free operation without human interference during the hazardous situation is using a robot. Therefore, in this study, an advanced autonomous robot has been designed and developed that can monitor several parameters in the NPP to ensure the safety and do some risky job in case of nuclear disaster. The robot consisted of autonomous track following unit, data processing and transmitting unit can follow a straight line and take turn as the bank greater than 90 degrees. The developed robot can analyze various parameters such as temperature, altitude, radiation, obstacle, humidity, detecting fire, measuring distance, ultrasonic scan and taking the heat of any particular object. It has an ability to broadcast live stream and can record the document to its own server memory. There is a separate control unit constructed with a baseboard which processes the recorded data and a transmitter which transmits the processed data. To make the robot user-friendly, the code is developed such a way that a user can control any of robotic arm as per types of work. To control at any place and without the track, there is an advanced code has been developed to take manual overwrite. Through this process, administrator who has logged in permission to Dynamic Host Client Protocol (DHCP) can make the handover of the control of the robot. In this process, this robot is provided maximum nuclear security from being hacked. Not only NPP, this robot can be used to maximize the real-time monitoring system of any nuclear facility as well as nuclear material transportation and decomposition system.

Keywords: nuclear power plant, radiation, dynamic host client protocol, nuclear security

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Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

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Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform

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Authors: Yuguang Wang, Chuanjun Wang

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At present, many coastal areas around the world suffer from seawater intrusion. Seawater intrusion is the superimposed result of two factors which are nature and human social economical activities in particular area. In recent years, due to excessive exploitation of groundwater, the seawater intrusion phenomenon aggravate in coastal zone of the Bohai and Huanghai seas in our country. Moreover, with sea-level rising, the original hydrodynamic equilibrium between saltwater and freshwater has been damaged to a certain extent, and it will further aggravate seawater intrusion in the land plains. In addition, overexploitation of groundwater declined groundwater level and increase saltwater intrusion in coastal areas. Therefore, in view of the sensitivity and vulnerability of the impact of sea-level rise in the future, the risk of sea-level rise in coastal zone should be considered, reasonable exploitation, utilization and management of coastal zone’s groundwater should be formulated. The response mechanism of sea-level rise should be studied to prevent and reduce the harm of seawater intrusion, which has important theoretical and realistic significances. In this paper, through the long-term monitoring of groundwater level and conductibility in the transition region of seawater intrusion for the sand coast area, realtimely master the situation of seawater intrusion. Combined with the seasonal exploitation station of groundwater and sea level variation, early alert the seawater intrusion to prevent and reduce the harm of seawater intrusion.

Keywords: groundwater level, sea level, seawater intrusion, sand coast

Procedia PDF Downloads 469

Authors: Esra Yuksel, Dilek Duman, Levent Yeniay, Sezgin Ulukaya

Abstract:

Sentinel lymph node biopsy (SLNB) is a minimal invasive technique with lower morbidity in axillary staging of breast cancer. Isosulfan blue stain is frequently used in SLNB and regarded as safe. The present case report aimed to report severe decrement in SpO2 following isosulfan blue administration, as well as skin and urine signs and inconsistency with clinical picture in a 67-year-old ,77 kg, ASA II female case that underwent SLNB under general anesthesia. Ten minutes after subcutaneous administration of 10 ml 1% isosulfan blue by the surgeons into the patient, who were hemodynamically stable, SpO2 first reduced to 87% from 99%, and then to 75% in minutes despite 100% oxygen support. Meanwhile, blood pressure and EtCO2 monitoring was unremarkable. After specifying that anesthesia device worked normally, airway pressure did not increase and the endotracheal tube has been placed accurately, the blood sample was taken from the patient for arterial gas analysis. A severe increase was thought in MetHb concentration since SpO2 persisted to be 75% although the concentration of inspired oxygen was 100%, and solution of 2500 mg ascorbic acid in 500 ml 5% Dextrose was given to the patient via intravenous route until the results of arterial blood gas were obtained. However, arterial blood gas results were as follows: pH: 7.54, PaCO2: 23.3 mmHg, PaO2: 281 mmHg, SaO2: %99, and MetHb: %2.7. Biochemical analysis revealed a blood MetHb concentration of 2%.However, since arterial blood gas parameters were good, hemodynamics of the patient was stable and methemoglobin concentration was not so high, the patient was extubated after surgery when she was relaxed, cooperated and had adequate respiration. Despite the absence of respiratory or neurological distress, SpO2 value was increased only up to 85% within 2 hours with 5 L/min oxygen support via face mask in the surgery room as the patient was extubated. At that time, the skin of particularly the upper part of her body has turned into blue, more remarkable on the face. The color of plasma of the blood taken from the patient for biochemical analysis was blue. The color of urine coming throughout the urinary catheter placed in intensive care unit was also blue. Twelve hours after 5 L/min. oxygen inhalation via a mask, the SpO2 reached to 90%. During monitoring in intensive care unit on the postoperative 1st day, facial color and urine color of the patient was still blue, SpO2 was 92%, and arterial blood gas levels were as follows: pH: 7.44, PaO2: 76.1 mmHg, PaCO2: 38.2 mmHg, SaO2: 99%, and MetHb 1%. During monitoring in clinic on the postoperative 2nd day, SpO2 was 95% without oxygen support and her facial and urine color turned into normal. The patient was discharged on the 3rd day without any problem.In conclusion, SLNB is a less invasive alternative to axillary dissection. However, false pulse oximeter reading due to pigment interference is a rare complication of this procedure. Arterial blood gas analysis should be used to confirm any fall in SpO2 reading during monitoring.

Keywords: isosulfan blue, pulse oximetry, SLNB, methemoglobinemia

Procedia PDF Downloads 315

Authors: A. Casale, J. Alessi, C. N. Bianchi, G. Bozzini, M. Brunoldi, V. Cappanera, P. Corvisiero, G. Fanciulli, D. Grosso, N. Magnoli, A. Mandich, C. Melchiorre, C. Morri, P. Povero, N. Stasi, M. Taiuti, G. Viano, M. Wurtz

Abstract:

This work describes a real-time algorithm for detecting, tracking and classifying single motorboats, developed using the acoustic data recorded by a hydrophone array within the framework of EU LIFE + project ARION (LIFE09NAT/IT/000190). The project aims to improve the conservation status of bottlenose dolphins through a real-time simultaneous monitoring of their population and surface ship traffic. A Passive Acoustic Monitoring (PAM) system is installed on two autonomous permanent marine buoys, located close to the boundaries of the Marine Protected Area (MPA) of Portofino (Ligurian Sea- Italy). Detecting surface ships is also a necessity in many other sensible areas, such as wind farms, oil platforms, and harbours. A PAM system could be an effective alternative to the usual monitoring systems, as radar or active sonar, for localizing unauthorized ship presence or illegal activities, with the advantage of not revealing its presence. Each ARION buoy consists of a particular type of structure, named meda elastica (elastic beacon) composed of a main pole, about 30-meter length, emerging for 7 meters, anchored to a mooring of 30 tons at 90 m depth by an anti-twist steel wire. Each buoy is equipped with a floating element and a hydrophone tetrahedron array, whose raw data are send via a Wi-Fi bridge to a ground station where real-time analysis is performed. Bottlenose dolphin detection algorithm and ship monitoring algorithm are operating in parallel and in real time. Three modules were developed and commissioned for ship monitoring. The first is the detection algorithm, based on Time Difference Of Arrival (TDOA) measurements, i.e., the evaluation of angular direction of the target respect to each buoy and the triangulation for obtaining the target position. The second is the tracking algorithm, based on a Kalman filter, i.e., the estimate of the real course and speed of the target through a predictor filter. At last, the classification algorithm is based on the DEMON method, i.e., the extraction of the acoustic signature of single vessels. The following results were obtained; the detection algorithm succeeded in evaluating the bearing angle with respect to each buoy and the position of the target, with an uncertainty of 2 degrees and a maximum range of 2.5 km. The tracking algorithm succeeded in reconstructing the real vessel courses and estimating the speed with an accuracy of 20% respect to the Automatic Identification System (AIS) signals. The classification algorithm succeeded in isolating the acoustic signature of single vessels, demonstrating its temporal stability and the consistency of both buoys results. As reference, the results were compared with the Hilbert transform of single channel signals. The algorithm for tracking multiple targets is ready to be developed, thanks to the modularity of the single ship algorithm: the classification module will enumerate and identify all targets present in the study area; for each of them, the detection module and the tracking module will be applied to monitor their course.

Keywords: acoustic-noise, bottlenose-dolphin, hydrophone, motorboat

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Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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Authors: Harvey Hyman, Thomas Hull

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As one of the largest cancer treatment centers in the United States, we continuously confront the challenge of how to leverage the best possible technological solutions, in order to provide the highest quality of service to our customers – the doctors, nurses and patients at Moffitt who are fighting every day for the prevention and cure of cancer. This paper reports on the transition from a vertical to a horizontal IT infrastructure. We discuss how the new frameworks and methods such as public, private and hybrid cloud, brokering cloud services are replacing the traditional vertical paradigm for computing. We also report on the impact of containers, micro services, and the shift to continuous integration/continuous delivery. These impacts and changes in delivery methodology for computing are driving how we accomplish our strategic IT goals across the enterprise.

Keywords: cloud computing, IT infrastructure, IT architecture, healthcare

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Authors: Mandeep Kataria, Ritu Narula, Navneet Kaur

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Asparagine is vital amino acid which is required for the development of brain and it regulates the equilibrium of central nervous system. Asparagine is the chief amino acid that forms acrylamide in baked food by reacting with reducing sugars at high temperature ( Millard Reaction i.e. amino acids and sugars give new flavors at high temperature). It can also be a parameter of freshness in fruit juices because on storage of juices at 37°C caused an 87% loss in the total free amino acids and major decrease was recorded in asparagine contents. With this significance of monitoring asparagine, in the present work a biosensor for determining asparagine in fruit juices is developed. For the construction of biosensor L-asparaginase enzyme (0.5 IU) was co-immobilized with phenol red on TEOS chitosan sol-gel plastic disc and fixed on the fiber optic tip. Tip was immersed in a cell having 5ml of substrate and absorption was noted at response time of 5 min with 10-1 - 10-10 M concentrations of asparagine at 538 nm. L-asparaginase was extracted and from Solanum nigrum Asparagine biosensor was applied fruit juices on the monitoring asparagine contents. L-asparagine concentration found to be present in fruit juices like Guava Juice, Apple Juice, Mango Juice, Litchi juice, Strawberry juice, Pineapple juice Lemon juice, and Orange juice. Hence the developed biosensor has commercial aspects in quality insurance of fruit juices.

Keywords: fiber optic biosensor, chitosan, teos, l-asparaginase

Procedia PDF Downloads 289

Authors: Ugur Fidan, Naim Karasekreter

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Healthy and clean water should not contain disease-causing micro-organisms and toxic chemicals and must contain the necessary minerals in a balanced manner. Today, water resources have a limited and strategic importance, necessitating the management of water reserves. Water tanks meet the water needs of people and should be regularly chlorinated to prevent waterborne diseases. For this purpose, automatic chlorination systems placed in water tanks for killing bacteria. However, the regular operation of automatic chlorination systems depends on refilling the chlorine tank when it is empty. For this reason, there is a need for a stock control system, in which chlorine levels are regularly monitored and supplied. It has become imperative to take urgent measures against epidemics caused by the fact that most of our country is not aware of the end of chlorine. The aim of this work is to rehabilitate existing water tanks and to provide a method for a modern water storage system in which chlorination is digitally monitored by turning the newly established water tanks into a closed system. A sensor network structure using GSM/GPRS communication infrastructure has been developed in the study. The system consists of two basic units: hardware and software. The hardware includes a chlorine level sensor, an RFID interlock system for authorized personnel entry into water tank, a motion sensor for animals and other elements, and a camera system to ensure process safety. It transmits the data from the hardware sensors to the host server software via the TCP/IP protocol. The main server software processes the incoming data through the security algorithm and informs the relevant unit responsible (Security forces, Chlorine supply unit, Public health, Local Administrator) by e-mail and SMS. Since the software is developed base on the web, authorized personnel are also able to monitor drinking water tank and report data on the internet. When the findings and user feedback obtained as a result of the study are evaluated, it is shown that closed drinking water tanks are built with GRP type material, and continuous monitoring in digital environment is vital for sustainable health water supply for people.

Keywords: wireless sensor networks (WSN), monitoring, chlorine, water tank, security

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Authors: Lorenza Abbracciavento, Valerio De Biagi

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Infrastructures are key elements to ensure the operational functionality of the transport system. The collapse of a single bridge or, equivalently, a tunnel can leads an entire motorway to be considered completely inaccessible. As a consequence, the paralysis of the communications network determines several important drawbacks for the community. Recent chronicle events have demonstrated that ensuring the functional continuity of the strategic infrastructures during and after a catastrophic event makes a significant difference in terms of life and economical losses. Moreover, it has been observed that RC structures located in mountain environments show a worst state of conservation compared to the same typology and aging structures located in temperate climates. Because of its morphology, in fact, the mountain environment is particularly exposed to severe collapse and deterioration phenomena, generally: natural hazards, e.g. rock falls, and meteorological hazards, e.g. freeze-thaw cycles or heavy snows. For these reasons, deep investigation on the characteristics of these processes becomes of fundamental importance to provide smart and sustainable solutions and make the infrastructure system more resilient. In this paper, the design of a monitoring system in mountainous environments is presented and analyzed in its parts. The method not only takes into account the peculiar climatic conditions, but it is integrated and interacts with the environment surrounding.

Keywords: structural health monitoring, resilience of bridges, mountain infrastructures, infrastructural network, maintenance

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Authors: Nabil Omar, Farah Jibril, Oraib Amjad

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Purpose: Trabecatine is a is a potent marine-derived antineoplastic drug which binds to the minor groove of the DNA, bending DNA towards the major groove resulting in a changed conformation that interferes with several DNA transcription factors, repair pathways and cell proliferation. Trabectedin was approved by the European Medicines Agency (EMA; London, UK) for the treatment of adult patients with advanced stage soft tissue sarcomas in whom treatment with anthracyclines and ifosfamide has failed, or for those who are not candidates for these therapies. The recommended dosing regimen is 1.5 mg/m2 IV over 24 hours every 3 weeks. The purpose of this study was to comprehensively review available data on the safety and efficacy of trabectedin used as indicated for patients at a Tertiary Cancer Center at Qatar. Methods: A medication administration report generated in the electronic health record identified all patients who received trabectedin between November 1, 2015 and November 1, 2017. This retrospective chart review evaluated the indication of trabectedin use, compliance to administration protocol and the recommended monitoring parameters, number of patients improved on the drug and continued treatment, number of patients discontinued treatment due to side-effects and the reported side effects. Progress and discharged notes were utilized to report experienced side effects during trabectedin therapy. A total of 3 patients were reviewed. Results: Total of 2 out of 3 patients who received trabectedin were receiving it for non-FDA and non-EMA, approved indications; metastatic rhabdomyosarcoma and ovarian cancer stage IV with poor prognosis. And only one patient received it as indicated for leiomyosarcoma of left ureter with metastases to liver, lungs and bone. None of the patients has continued the therapy due to development of serious side effects. One patient had stopped the medication after one cycle due to disease progression and transient hepatic toxicity, the other one had disease progression and developed 12 % reduction in LVEF after 12 cycles of trabectedin, and the third patient deceased, had disease progression on trabectedin after the 10th cycle that was received through peripheral line which resulted in developing extravasation and left arm cellulitis requiring debridement. Regarding monitoring parameters, at baseline the three patients had ECHO, and Creatine Phosphokinase (CPK) but it was not monitored during treatment as recommended. Conclusion: Utilizing this medication as indicated with performing the appropriate monitoring parameters as recommended can benefit patients who are receiving it. It is important to reinforce the intravenous administration via central intravenous line, the re-assessment of left ventricular ejection fraction (LVEF) by echocardiogram or multigated acquisition (MUGA) scan at 2- to 3-month intervals thereafter until therapy is discontinued, and CPK and LFTs levels prior to each administration of trabectedin.

Keywords: trabectedin, drug-use evaluation, safety, effectiveness, adverse drug reaction, monitoring

Procedia PDF Downloads 143

Authors: Shinji Kajiwara

Abstract:

The basic ability of a vehicle is the ability to “run”, “turn” and “stop”. The safeness and comfort during a drive on various road surfaces and speed depends on the performance of these basic abilities of the vehicle. Stability and maneuverability of a vehicle is vital in automotive engineering. Stability of a vehicle is the ability of the vehicle to revert back to a stable state during a drive when faced with crosswind and irregular road conditions. Maneuverability of a vehicle is the ability of the vehicle to change direction during a drive swiftly based on the steering of the driver. The stability and maneuverability of a vehicle can also be defined as the driving stability of the vehicle. Since fossil fueled vehicle is the main type of transportation today, the environmental factor in automotive engineering is also vital. By improving the fuel efficiency of the vehicle, the overall carbon emission will be reduced thus reducing the effect of global warming and greenhouse gas on the Earth. Another main focus of the automotive engineering is the safety performance of the vehicle especially with the worrying increase of vehicle collision every day. With better safety performance on a vehicle, every driver will be more confidence driving every day. Next, let us focus on the “turn” ability of a vehicle. By improving this particular ability of the vehicle, the cornering limit of the vehicle can be improved thus increasing the stability and maneuverability factor. In order to improve the cornering limit of the vehicle, a study to find the balance between the steering systems, the stability of the vehicle, higher lateral acceleration and the cornering limit detection must be conducted. The aim of this research is to study and develop a new suspension system that that will boost the lateral acceleration of the vehicle and ultimately improving the cornering limit of the vehicle. This research will also study environmental factor and the stability factor of the new suspension system. The double wishbone suspension system is widely used in four-wheel vehicle especially for high cornering performance sports car and racing car. The double wishbone designs allow the engineer to carefully control the motion of the wheel by controlling such parameters as camber angle, caster angle, toe pattern, roll center height, scrub radius, scuff and more. The development of the new suspension system will focus on the ability of the new suspension system to optimize the camber control and to improve the camber limit during a cornering motion. The research will be carried out using the CAE analysis tool. Using this analysis tool we will develop a JSAE Formula Machine equipped with the double wishbone system and also the new suspension system and conduct simulation and conduct studies on performance of both suspension systems.

Keywords: automobile, camber thrust, cornering force, suspension

Procedia PDF Downloads 323