Search results for: proximity sensors
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1581

Search results for: proximity sensors

1161 Security Issues on Smart Grid and Blockchain-Based Secure Smart Energy Management Systems

Authors: Surah Aldakhl, Dafer Alali, Mohamed Zohdy

Abstract:

The next generation of electricity grid infrastructure, known as the "smart grid," integrates smart ICT (information and communication technology) into existing grids in order to alleviate the drawbacks of existing one-way grid systems. Future power systems' efficiency and dependability are anticipated to significantly increase thanks to the Smart Grid, especially given the desire for renewable energy sources. The security of the Smart Grid's cyber infrastructure is a growing concern, though, as a result of the interconnection of significant power plants through communication networks. Since cyber-attacks can destroy energy data, beginning with personal information leaking from grid members, they can result in serious incidents like huge outages and the destruction of power network infrastructure. We shall thus propose a secure smart energy management system based on the Blockchain as a remedy for this problem. The power transmission and distribution system may undergo a transformation as a result of the inclusion of optical fiber sensors and blockchain technology in smart grids. While optical fiber sensors allow real-time monitoring and management of electrical energy flow, Blockchain offers a secure platform to safeguard the smart grid against cyberattacks and unauthorized access. Additionally, this integration makes it possible to see how energy is produced, distributed, and used in real time, increasing transparency. This strategy has advantages in terms of improved security, efficiency, dependability, and flexibility in energy management. An in-depth analysis of the advantages and drawbacks of combining blockchain technology with optical fiber is provided in this paper.

Keywords: smart grids, blockchain, fiber optic sensor, security

Procedia PDF Downloads 120
1160 Optimizing Load Shedding Schedule Problem Based on Harmony Search

Authors: Almahd Alshereef, Ahmed Alkilany, Hammad Said, Azuraliza Abu Bakar

Abstract:

From time to time, electrical power grid is directed by the National Electricity Operator to conduct load shedding, which involves hours' power outages on the area of this study, Southern Electrical Grid of Libya (SEGL). Load shedding is conducted in order to alleviate pressure on the National Electricity Grid at times of peak demand. This approach has chosen a set of categories to study load-shedding problem considering the effect of the demand priorities on the operation of the power system during emergencies. Classification of category region for load shedding problem is solved by a new algorithm (the harmony algorithm) based on the "random generation list of category region", which is a possible solution with a proximity degree to the optimum. The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on SEGL.

Keywords: optimization, harmony algorithm, load shedding, classification

Procedia PDF Downloads 396
1159 Real-Time Monitoring of Drinking Water Quality Using Advanced Devices

Authors: Amani Abdallah, Isam Shahrour

Abstract:

The quality of drinking water is a major concern of public health. The control of this quality is generally performed in the laboratory, which requires a long time. This type of control is not adapted for accidental pollution from sudden events, which can have serious consequences on population health. Therefore, it is of major interest to develop real-time innovative solutions for the detection of accidental contamination in drinking water systems This paper presents researches conducted within the SunRise Demonstrator for ‘Smart and Sustainable Cities’ with a particular focus on the supervision of the water quality. This work aims at (i) implementing a smart water system in a large water network (Campus of the University Lille1) including innovative equipment for real-time detection of abnormal events, such as those related to the contamination of drinking water and (ii) develop a numerical modeling of the contamination diffusion in the water distribution system. The first step included verification of the water quality sensors and their effectiveness on a network prototype of 50m length. This part included the evaluation of the efficiency of these sensors in the detection both bacterial and chemical contamination events in drinking water distribution systems. An on-line optical sensor integral with a laboratory-scale distribution system (LDS) was shown to respond rapidly to changes in refractive index induced by injected loads of chemical (cadmium, mercury) and biological contaminations (Escherichia coli). All injected substances were detected by the sensor; the magnitude of the response depends on the type of contaminant introduced and it is proportional to the injected substance concentration.

Keywords: distribution system, drinking water, refraction index, sensor, real-time

Procedia PDF Downloads 354
1158 Human-Centred Data Analysis Method for Future Design of Residential Spaces: Coliving Case Study

Authors: Alicia Regodon Puyalto, Alfonso Garcia-Santos

Abstract:

This article presents a method to analyze the use of indoor spaces based on data analytics obtained from inbuilt digital devices. The study uses the data generated by the in-place devices, such as smart locks, Wi-Fi routers, and electrical sensors, to gain additional insights on space occupancy, user behaviour, and comfort. Those devices, originally installed to facilitate remote operations, report data through the internet that the research uses to analyze information on human real-time use of spaces. Using an in-place Internet of Things (IoT) network enables a faster, more affordable, seamless, and scalable solution to analyze building interior spaces without incorporating external data collection systems such as sensors. The methodology is applied to a real case study of coliving, a residential building of 3000m², 7 floors, and 80 users in the centre of Madrid. The case study applies the method to classify IoT devices, assess, clean, and analyze collected data based on the analysis framework. The information is collected remotely, through the different platforms devices' platforms; the first step is to curate the data, understand what insights can be provided from each device according to the objectives of the study, this generates an analysis framework to be escalated for future building assessment even beyond the residential sector. The method will adjust the parameters to be analyzed tailored to the dataset available in the IoT of each building. The research demonstrates how human-centered data analytics can improve the future spatial design of indoor spaces.

Keywords: in-place devices, IoT, human-centred data-analytics, spatial design

Procedia PDF Downloads 197
1157 Using Equipment Telemetry Data for Condition-Based maintenance decisions

Authors: John Q. Todd

Abstract:

Given that modern equipment can provide comprehensive health, status, and error condition data via built-in sensors, maintenance organizations have a new and valuable source of insight to take advantage of. This presentation will expose what these data payloads might look like and how they can be filtered, visualized, calculated into metrics, used for machine learning, and generate alerts for further action.

Keywords: condition based maintenance, equipment data, metrics, alerts

Procedia PDF Downloads 188
1156 Assessment of the CSR of Telecom Operators in Cote d’Ivoire

Authors: Odile Amoncou, Djedje-Kossu Zahui

Abstract:

The integration of a Corporate Social Responsibility (CSR) approach within a company appears nowadays as a fundamental system of response to the different problems that threaten our planet. The abusive exploitation of natural resources, social inequalities, discrimination and poverty are some examples. Thus, faced with these different global problems, each company must include in its operating system measures or actions with the aim not only of achieving Sustainable Development Goals (SDGs) but also for the improvement of its performance and its brand internationally. The objective of this article is to assess the implementation of CSR by telecommunication companies. It is our belief that given its high energy consumption and proximity to society, the telecom sector must pay particular attention to environmental and social issues. Our study examines the CSR of three Ivorian telecom operators, namely ORANGE CI, MOOV Africa and MTN, by applying a series of performance indicators related to CSR management. We hope that our study will raise awareness about sustainability issues for all other Ivorian companies but also sub-Sahara African companies in general in order to encourage CEOs to make CSR concept a top priority.

Keywords: CSR, telecom, SDGs, cote d’Ivoire

Procedia PDF Downloads 80
1155 A Structure-Switching Electrochemical Aptasensor for Rapid, Reagentless and Single-Step, Nanomolar Detection of C-Reactive Protein

Authors: William L. Whitehouse, Louisa H. Y. Lo, Andrew B. Kinghorn, Simon C. C. Shiu, Julian. A. Tanner

Abstract:

C-reactive protein (CRP) is an acute-phase reactant and sensitive indicator for sepsis and other life-threatening pathologies, including systemic inflammatory response syndrome (SIRS). Currently, clinical turn-around times for established CRP detection methods take between 30 minutes to hours or even days from centralized laboratories. Here, we report the development of an electrochemical biosensor using redox probe-tagged DNA aptamers functionalized onto cheap, commercially available screen-printed electrodes. Binding-induced conformational switching of the CRP-targeting aptamer induces a specific and selective signal-ON event, which enables single-step and reagentless detection of CRP in as little as 1 minute. The aptasensor dynamic range spans 5-1000nM (R=0.97) or 5-500nM (R=0.99) in 50% diluted human serum, with a LOD of 3nM, corresponding to 2-orders of magnitude sensitivity under the clinically relevant cut-off for CRP. The sensor is stable for up to one week and can be reused numerous times, as judged from repeated real-time dosing and dose-response assays. By decoupling binding events from the signal induction mechanism, structure-switching electrochemical aptamer-based sensors (SS-EABs) provide considerable advantages over their adsorption-based counterparts. Our work expands on the retinue of such sensors reported in the literature and is the first instance of an SS-EAB for reagentless CRP detection. We hope this study can inspire further investigations into the suitability of SS-EABs for diagnostics, which will aid translational R&D toward fully realized devices aimed at point-of-care applications or for use more broadly by the public.

Keywords: structure-switching, C-reactive protein, electrochemical, biosensor, aptasensor.

Procedia PDF Downloads 70
1154 Classification of Coughing and Breathing Activities Using Wearable and a Light-Weight DL Model

Authors: Subham Ghosh, Arnab Nandi

Abstract:

Background: The proliferation of Wireless Body Area Networks (WBAN) and Internet of Things (IoT) applications demonstrates the potential for continuous monitoring of physical changes in the body. These technologies are vital for health monitoring tasks, such as identifying coughing and breathing activities, which are necessary for disease diagnosis and management. Monitoring activities such as coughing and deep breathing can provide valuable insights into a variety of medical issues. Wearable radio-based antenna sensors, which are lightweight and easy to incorporate into clothing or portable goods, provide continuous monitoring. This mobility gives it a substantial advantage over stationary environmental sensors like as cameras and radar, which are constrained to certain places. Furthermore, using compressive techniques provides benefits such as reduced data transmission speeds and memory needs. These wearable sensors offer more advanced and diverse health monitoring capabilities. Methodology: This study analyzes the feasibility of using a semi-flexible antenna operating at 2.4 GHz (ISM band) and positioned around the neck and near the mouth to identify three activities: coughing, deep breathing, and idleness. Vector network analyzer (VNA) is used to collect time-varying complex reflection coefficient data from perturbed antenna nearfield. The reflection coefficient (S11) conveys nuanced information caused by simultaneous variations in the nearfield radiation of three activities across time. The signatures are sparsely represented with gaussian windowed Gabor spectrograms. The Gabor spectrogram is used as a sparse representation approach, which reassigns the ridges of the spectrogram images to improve their resolution and focus on essential components. The antenna is biocompatible in terms of specific absorption rate (SAR). The sparsely represented Gabor spectrogram pictures are fed into a lightweight deep learning (DL) model for feature extraction and classification. Two antenna locations are investigated in order to determine the most effective localization for three different activities. Findings: Cross-validation techniques were used on data from both locations. Due to the complex form of the recorded S11, separate analyzes and assessments were performed on the magnitude, phase, and their combination. The combination of magnitude and phase fared better than the separate analyses. Various sliding window sizes, ranging from 1 to 5 seconds, were tested to find the best window for activity classification. It was discovered that a neck-mounted design was effective at detecting the three unique behaviors.

Keywords: activity recognition, antenna, deep-learning, time-frequency

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1153 Digital Twin for a Floating Solar Energy System with Experimental Data Mining and AI Modelling

Authors: Danlei Yang, Luofeng Huang

Abstract:

The integration of digital twin technology with renewable energy systems offers an innovative approach to predicting and optimising performance throughout the entire lifecycle. A digital twin is a continuously updated virtual replica of a real-world entity, synchronised with data from its physical counterpart and environment. Many digital twin companies today claim to have mature digital twin products, but their focus is primarily on equipment visualisation. However, the core of a digital twin should be its model, which can mirror, shadow, and thread with the real-world entity, which is still underdeveloped. For a floating solar energy system, a digital twin model can be defined in three aspects: (a) the physical floating solar energy system along with environmental factors such as solar irradiance and wave dynamics, (b) a digital model powered by artificial intelligence (AI) algorithms, and (c) the integration of real system data with the AI-driven model and a user interface. The experimental setup for the floating solar energy system, is designed to replicate real-ocean conditions of floating solar installations within a controlled laboratory environment. The system consists of a water tank that simulates an aquatic surface, where a floating catamaran structure supports a solar panel. The solar simulator is set up in three positions: one directly above and two inclined at a 45° angle in front and behind the solar panel. This arrangement allows the simulation of different sun angles, such as sunrise, midday, and sunset. The solar simulator is positioned 400 mm away from the solar panel to maintain consistent solar irradiance on its surface. Stability for the floating structure is achieved through ropes attached to anchors at the bottom of the tank, which simulates the mooring systems used in real-world floating solar applications. The floating solar energy system's sensor setup includes various devices to monitor environmental and operational parameters. An irradiance sensor measures solar irradiance on the photovoltaic (PV) panel. Temperature sensors monitor ambient air and water temperatures, as well as the PV panel temperature. Wave gauges measure wave height, while load cells capture mooring force. Inclinometers and ultrasonic sensors record heave and pitch amplitudes of the floating system’s motions. An electric load measures the voltage and current output from the solar panel. All sensors collect data simultaneously. Artificial neural network (ANN) algorithms are central to developing the digital model, which processes historical and real-time data, identifies patterns, and predicts the system’s performance in real time. The data collected from various sensors are partly used to train the digital model, with the remaining data reserved for validation and testing. The digital twin model combines the experimental setup with the ANN model, enabling monitoring, analysis, and prediction of the floating solar energy system's operation. The digital model mirrors the functionality of the physical setup, running in sync with the experiment to provide real-time insights and predictions. It provides useful industrial benefits, such as informing maintenance plans as well as design and control strategies for optimal energy efficiency. In long term, this digital twin will help improve overall solar energy yield whilst minimising the operational costs and risks.

Keywords: digital twin, floating solar energy system, experiment setup, artificial intelligence

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1152 Development of an Autonomous Automated Guided Vehicle with Robot Manipulator under Robot Operation System Architecture

Authors: Jinsiang Shaw, Sheng-Xiang Xu

Abstract:

This paper presents the development of an autonomous automated guided vehicle (AGV) with a robot arm attached on top of it within the framework of robot operation system (ROS). ROS can provide libraries and tools, including hardware abstraction, device drivers, libraries, visualizers, message-passing, package management, etc. For this reason, this AGV can provide automatic navigation and parts transportation and pick-and-place task using robot arm for typical industrial production line use. More specifically, this AGV will be controlled by an on-board host computer running ROS software. Command signals for vehicle and robot arm control and measurement signals from various sensors are transferred to respective microcontrollers. Users can operate the AGV remotely through the TCP / IP protocol and perform SLAM (Simultaneous Localization and Mapping). An RGBD camera and LIDAR sensors are installed on the AGV, using these data to perceive the environment. For SLAM, Gmapping is used to construct the environment map by Rao-Blackwellized particle filter; and AMCL method (Adaptive Monte Carlo localization) is employed for mobile robot localization. In addition, current AGV position and orientation can be visualized by ROS toolkit. As for robot navigation and obstacle avoidance, A* for global path planning and dynamic window approach for local planning are implemented. The developed ROS AGV with a robot arm on it has been experimented in the university factory. A 2-D and 3-D map of the factory were successfully constructed by the SLAM method. Base on this map, robot navigation through the factory with and without dynamic obstacles are shown to perform well. Finally, pick-and-place of parts using robot arm and ensuing delivery in the factory by the mobile robot are also accomplished.

Keywords: automated guided vehicle, navigation, robot operation system, Simultaneous Localization and Mapping

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1151 Review of the Software Used for 3D Volumetric Reconstruction of the Liver

Authors: P. Strakos, M. Jaros, T. Karasek, T. Kozubek, P. Vavra, T. Jonszta

Abstract:

In medical imaging, segmentation of different areas of human body like bones, organs, tissues, etc. is an important issue. Image segmentation allows isolating the object of interest for further processing that can lead for example to 3D model reconstruction of whole organs. Difficulty of this procedure varies from trivial for bones to quite difficult for organs like liver. The liver is being considered as one of the most difficult human body organ to segment. It is mainly for its complexity, shape versatility and proximity of other organs and tissues. Due to this facts usually substantial user effort has to be applied to obtain satisfactory results of the image segmentation. Process of image segmentation then deteriorates from automatic or semi-automatic to fairly manual one. In this paper, overview of selected available software applications that can handle semi-automatic image segmentation with further 3D volume reconstruction of human liver is presented. The applications are being evaluated based on the segmentation results of several consecutive DICOM images covering the abdominal area of the human body.

Keywords: image segmentation, semi-automatic, software, 3D volumetric reconstruction

Procedia PDF Downloads 290
1150 An Overview of Sustainable Development for Greening Roadmap in Asia

Authors: Robby Dwiko Juliardi, Queena K. Qian

Abstract:

Economic, environmental, and human considerations, as sustainable building design principles, are to be balanced and integrated into building design strategy. Building codes often suggest the efficient and sustainable building products, such as energy-efficient fixtures. However, building departments sometimes fail to manage the full range of requirements in the building assessment, such as siting, neighborhood proximity, and public facility, etc. Hence, it shows roadmap develops the future, an extended look at the future of a chosen field of inquiry composed from the collective knowledge and imagination of the brightest drivers of change in that field. This paper is taken from the best practice of green building implementation in a few countries of Asia (China, Malaysia, and India). Sustainable development will be presented on developing the roadmap of sustainability development of a country. Findings on the similarities and dissimilarities of those countries will show: (1) A general knowledge development on the sustainable green roadmap in Asia, (2) What are the components of developing the roadmap, and (3) What affects the government regulation in a political ecology.

Keywords: developing roadmap, green building, political ecology, sustainable development

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1149 University Students Sport’s Activities Assessment in Harsh Weather Conditions

Authors: Ammar S. M. Moohialdin, Bambang T. Suhariadi, Mohsin Siddiqui

Abstract:

This paper addresses the application of physiological status monitoring (PSM) for assessing the impact of harsh weather conditions on sports activities in universities in Saudi Arabia. Real sports measurement was conducted during sports activities such that the physiological status (HR and BR) of five students were continuously monitored by using Zephyr BioHarnessTM 3.0 sensors in order to identify the physiological bonds and zones. These bonds and zones were employed as indicators of the associated physiological risks of the performed sports activities. Furthermore, a short yes/no questionnaire was applied to collect information on participants’ health conditions and opinions of the applied PSM sensors. The results show the absence of a warning system as a protective aid for the hazardous levels of extremely hot and humid weather conditions that may cause dangerous and fatal circumstances. The applied formulas for estimating maximum HR provides accurate estimations for Maximum Heart Rate (HRmax). The physiological results reveal that the performed activities by the participants are considered the highest category (90–100%) in terms of activity intensity. This category is associated with higher HR, BR and physiological risks including losing the ability to control human body behaviors. Therefore, there is a need for immediate intervention actions to reduce the intensity of the performed activities to safer zones. The outcomes of this study assist the safety improvement of sports activities inside universities and athletes performing their sports activities. To the best of our knowledge, this is the first paper to represent a special case of the application of PSM technology for assessing sports activities in universities considering the impacts of harsh weather conditions on students’ health and safety.

Keywords: physiological status monitoring (PSM), heart rate (HR), breathing rate (BR), Arabian Gulf

Procedia PDF Downloads 199
1148 Using Pump as Turbine in Drinking Water Networks to Monitor and Control Water Processes Remotely

Authors: Sara Bahariderakhshan, Morteza Ahmadifar

Abstract:

Leakage is one of the most important problems that water distribution networks face which first reason is high-pressure existence. There are many approaches to control this excess pressure, which using pressure reducing valves (PRVs) or reducing pipe diameter are ones. In the other hand, Pumps are using electricity or fossil fuels to supply needed pressure in distribution networks but excess pressure are made in some branches due to topology problems and water networks’ variables therefore using pressure valves will be inevitable. Although using PRVs is inevitable but it leads to waste electricity or fuels used by pumps because PRVs just waste excess hydraulic pressure to lower it. Pumps working in reverse or Pumps as Turbine (called PaT in this article) are easily available and also effective sources of reducing the equipment cost in small hydropower plants. Urban areas of developing countries are facing increasing in area and maybe water scarcity in near future. These cities need wider water networks which make it hard to predict, control and have a better operation in the urban water cycle. Using more energy and, therefore, more pollution, slower repairing services, more user dissatisfaction and more leakage are these networks’ serious problems. Therefore, more effective systems are needed to monitor and act in these complicated networks than what is used now. In this article a new approach is proposed and evaluated: Using PAT to produce enough energy for remote valves and sensors in the water network. These sensors can be used to determine the discharge, pressure, water quality and other important network characteristics. With the help of remote valves pipeline discharge can be controlled so Instead of wasting excess hydraulic pressure which may be destructive in some cases, obtaining extra pressure from pipeline and producing clean electricity used by remote instruments is this articles’ goal. Furthermore due to increasing the area of the network there is unwanted high pressure in some critical points which is not destructive but lowering the pressure results to longer lifetime for pipeline networks without users’ dissatisfaction. This strategy proposed in this article, leads to use PaT widely for pressure containment and producing energy needed for remote valves and sensors like what happens in supervisory control and data acquisition (SCADA) systems which make it easy for us to monitor, receive data from urban water cycle and make any needed changes in discharge and pressure of pipelines easily and remotely. This is a clean project of energy production without significant environmental impacts and can be used in urban drinking water networks, without any problem for consumers which leads to a stable and dynamic network which lowers leakage and pollution.

Keywords: new energies, pump as turbine, drinking water, distribution network, remote control equipments

Procedia PDF Downloads 463
1147 Using Pump as Turbine in Urban Water Networks to Control, Monitor, and Simulate Water Processes Remotely

Authors: Morteza Ahmadifar, Sarah Bahari Derakhshan

Abstract:

Leakage is one of the most important problems that water distribution networks face which first reason is high-pressure existence. There are many approaches to control this excess pressure, which using pressure reducing valves (PRVs) or reducing pipe diameter are ones. On the other hand, Pumps are using electricity or fossil fuels to supply needed pressure in distribution networks but excess pressure are made in some branches due to topology problems and water networks’ variables, therefore using pressure valves will be inevitable. Although using PRVs is inevitable but it leads to waste electricity or fuels used by pumps because PRVs just waste excess hydraulic pressure to lower it. Pumps working in reverse or Pumps as Turbine (called PAT in this article) are easily available and also effective sources of reducing the equipment cost in small hydropower plants. Urban areas of developing countries are facing increasing in area and maybe water scarcity in near future. These cities need wider water networks which make it hard to predict, control and have a better operation in the urban water cycle. Using more energy and therefore more pollution, slower repairing services, more user dissatisfaction and more leakage are these networks’ serious problems. Therefore, more effective systems are needed to monitor and act in these complicated networks than what is used now. In this article a new approach is proposed and evaluated: Using PAT to produce enough energy for remote valves and sensors in the water network. These sensors can be used to determine the discharge, pressure, water quality and other important network characteristics. With the help of remote valves pipeline discharge can be controlled so Instead of wasting excess hydraulic pressure which may be destructive in some cases, obtaining extra pressure from pipeline and producing clean electricity used by remote instruments is this articles’ goal. Furthermore, due to increasing the area of network there is unwanted high pressure in some critical points which is not destructive but lowering the pressure results to longer lifetime for pipeline networks without users’ dissatisfaction. This strategy proposed in this article, leads to use PAT widely for pressure containment and producing energy needed for remote valves and sensors like what happens in supervisory control and data acquisition (SCADA) systems which make it easy for us to monitor, receive data from urban water cycle and make any needed changes in discharge and pressure of pipelines easily and remotely. This is a clean project of energy production without significant environmental impacts and can be used in urban drinking water networks, without any problem for consumers which leads to a stable and dynamic network which lowers leakage and pollution.

Keywords: clean energies, pump as turbine, remote control, urban water distribution network

Procedia PDF Downloads 393
1146 Control and Automation of Sensors in Metering System of Fluid

Authors: Abdelkader Harrouz, Omar Harrouz, Ali Benatiallah

Abstract:

This paper is to present the essential definitions, roles and characteristics of automation of metering system. We discuss measurement, data acquisition and metrological control of a signal sensor from dynamic metering system. After that, we present control of instruments of metering system of fluid with more detailed discussions to the reference standards.

Keywords: communication, metering, computer, sensor

Procedia PDF Downloads 555
1145 Electrospun Conducting Polymer/Graphene Composite Nanofibers for Gas Sensing Applications

Authors: Aliaa M. S. Salem, Soliman I. El-Hout, Amira Gaber, Hassan Nageh

Abstract:

Nowadays, the development of poisonous gas detectors is considered to be an urgent matter to secure human health and the environment from poisonous gases, in view of the fact that even a minimal amount of poisonous gas can be fatal. Of these concerns, various inorganic or organic sensing materials have been used. Among these are conducting polymers, have been used as the active material in the gassensorsdue to their low-cost,easy-controllable molding, good electrochemical properties including facile fabrication process, inherent physical properties, biocompatibility, and optical properties. Moreover, conducting polymer-based chemical sensors have an amazing advantage compared to the conventional one as structural diversity, facile functionalization, room temperature operation, and easy fabrication. However, the low selectivity and conductivity of conducting polymers motivated the doping of it with varied materials, especially graphene, to enhance the gas-sensing performance under ambient conditions. There were a number of approaches proposed for producing polymer/ graphene nanocomposites, including template-free self-assembly, hard physical template-guided synthesis, chemical, electrochemical, and electrospinning...etc. In this work, we aim to prepare a novel gas sensordepending on Electrospun nanofibers of conducting polymer/RGO composite that is the effective and efficient expectation of poisonous gases like ammonia, in different application areas such as environmental gas analysis, chemical-,automotive- and medical industries. Moreover, our ultimate objective is to maximize the sensing performance of the prepared sensor and to check its recovery properties.

Keywords: electro spinning process, conducting polymer, polyaniline, polypyrrole, polythiophene, graphene oxide, reduced graphene oxide, functionalized reduced graphene oxide, spin coating technique, gas sensors

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1144 Fabrication of Silver Nanowire Based Low Temperature Conductive Ink

Authors: Merve Nur Güven Biçer

Abstract:

Conductive inks are used extensively in electronic devices like sensors, batteries, photovoltaic devices, antennae, and organic light-emitting diodes. These inks are typically made from silver. Wearable technology is another industry that requires inks to be flexible. The aim of this study is the fabrication of low-temperature silver paste by synthesis long silver nanowires.

Keywords: silver ink, conductive ink, low temperature conductive ink, silver nanowire

Procedia PDF Downloads 188
1143 Performance Evaluation of GPS/INS Main Integration Approach

Authors: Othman Maklouf, Ahmed Adwaib

Abstract:

This paper introduces a comparative study between the main GPS/INS coupling schemes, this will include the loosely coupled and tightly coupled configurations, several types of situations and operational conditions, in which the data fusion process is done using Kalman filtering. This will include the importance of sensors calibration as well as the alignment of the strap down inertial navigation system. The limitations of the inertial navigation systems are investigated.

Keywords: GPS, INS, Kalman filter, sensor calibration, navigation system

Procedia PDF Downloads 590
1142 Maximization of Lifetime for Wireless Sensor Networks Based on Energy Efficient Clustering Algorithm

Authors: Frodouard Minani

Abstract:

Since last decade, wireless sensor networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. Wireless Sensor Networks consist of a Base Station (BS) and more number of wireless sensors in order to monitor temperature, pressure, motion in different environment conditions. The key parameter that plays a major role in designing a protocol for Wireless Sensor Networks is energy efficiency which is a scarcest resource of sensor nodes and it determines the lifetime of sensor nodes. Maximizing sensor node’s lifetime is an important issue in the design of applications and protocols for Wireless Sensor Networks. Clustering sensor nodes mechanism is an effective topology control approach for helping to achieve the goal of this research. In this paper, the researcher presents an energy efficiency protocol to prolong the network lifetime based on Energy efficient clustering algorithm. The Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing protocol for clusters which is used to lower the energy consumption and also to improve the lifetime of the Wireless Sensor Networks. Maximizing energy dissipation and network lifetime are important matters in the design of applications and protocols for wireless sensor networks. Proposed system is to maximize the lifetime of the Wireless Sensor Networks by choosing the farthest cluster head (CH) instead of the closest CH and forming the cluster by considering the following parameter metrics such as Node’s density, residual-energy and distance between clusters (inter-cluster distance). In this paper, comparisons between the proposed protocol and comparative protocols in different scenarios have been done and the simulation results showed that the proposed protocol performs well over other comparative protocols in various scenarios.

Keywords: base station, clustering algorithm, energy efficient, sensors, wireless sensor networks

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1141 Geo-Spatial Methods to Better Understand Urban Food Deserts

Authors: Brian Ceh, Alison Jackson-Holland

Abstract:

Food deserts are a reality in some cities. These deserts can be described as a shortage of healthy food options within close proximity of consumers. The shortage in this case is typically facilitated by a lack of stores in an urban area that provide adequate fruit and vegetable choices. This study explores new avenues to better understand food deserts by examining modes of transportation that are available to shoppers or consumers, e.g. walking, automobile, or public transit. Further, this study is unique in that it not only explores the location of large grocery stores, but small grocery and convenience stores too. In this study, the relationship between some socio-economic indicators, such as personal income, are also explored to determine any possible association with food deserts. In addition, to help facilitate our understanding of food deserts, complex network spatial models that are built on adequate algorithms are used to investigate the possibility of food deserts in the city of Hamilton, Canada. It is found that Hamilton, Canada is adequate serviced by retailers who provide healthy food choices and that the food desert phenomena is almost absent.

Keywords: Canada, desert, food, Hamilton, store

Procedia PDF Downloads 241
1140 Remote Wireless Patient Monitoring System

Authors: Sagar R. Patil, Dinesh R. Gawade, Sudhir N. Divekar

Abstract:

One of the medical devices we found when we visit a hospital care unit such device is ‘patient monitoring system’. This device (patient monitoring system) informs doctors and nurses about the patient’s physiological signals. However, this device (patient monitoring system) does not have a remote monitoring capability, which is necessitates constant onsite attendance by support personnel (doctors and nurses). Thus, we have developed a Remote Wireless Patient Monitoring System using some biomedical sensors and Android OS, which is a portable patient monitoring. This device(Remote Wireless Patient Monitoring System) monitors the biomedical signals of patients in real time and sends them to remote stations (doctors and nurse’s android Smartphone and web) for display and with alerts when necessary. Wireless Patient Monitoring System different from conventional device (Patient Monitoring system) in two aspects: First its wireless communication capability allows physiological signals to be monitored remotely and second, it is portable so patients can move while there biomedical signals are being monitor. Wireless Patient Monitoring is also notable because of its implementation. We are integrated four sensors such as pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), heart rate and electrocardiogram (ECG) in this device (Wireless Patient Monitoring System) and Monitoring and communication applications are implemented on the Android OS using threads, which facilitate the stable and timely manipulation of signals and the appropriate sharing of resources. The biomedical data will be display on android smart phone as well as on web Using web server and database system we can share these physiological signals with remote place medical personnel’s or with any where in the world medical personnel’s. We verified that the multitasking implementation used in the system was suitable for patient monitoring and for other Healthcare applications.

Keywords: patient monitoring, wireless patient monitoring, bio-medical signals, physiological signals, embedded system, Android OS, healthcare, pulse oximeter (SPO2), thermometer, respiration, blood pressure (BP), heart rate, electrocardiogram (ECG)

Procedia PDF Downloads 571
1139 Nanowire Sensor Based on Novel Impedance Spectroscopy Approach

Authors: Valeriy M. Kondratev, Ekaterina A. Vyacheslavova, Talgat Shugabaev, Alexander S. Gudovskikh, Alexey D. Bolshakov

Abstract:

Modern sensorics imposes strict requirements on the biosensors characteristics, especially technological feasibility, and selectivity. There is a growing interest in the analysis of human health biological markers, which indirectly testifying the pathological processes in the body. Such markers are acids and alkalis produced by the human, in particular - ammonia and hydrochloric acid, which are found in human sweat, blood, and urine, as well as in gastric juice. Biosensors based on modern nanomaterials, especially low dimensional, can be used for this markers detection. Most classical adsorption sensors based on metal and silicon oxides are considered non-selective, because they identically change their electrical resistance (or impedance) under the action of adsorption of different target analytes. This work demonstrates a feasible frequency-resistive method of electrical impedance spectroscopy data analysis. The approach allows to obtain of selectivity in adsorption sensors of a resistive type. The method potential is demonstrated with analyzis of impedance spectra of silicon nanowires in the presence of NH3 and HCl vapors with concentrations of about 125 mmol/L (2 ppm) and water vapor. We demonstrate the possibility of unambiguous distinction of the sensory signal from NH3 and HCl adsorption. Moreover, the method is found applicable for analysis of the composition of ammonia and hydrochloric acid vapors mixture without water cross-sensitivity. Presented silicon sensor can be used to find diseases of the gastrointestinal tract by the qualitative and quantitative detection of ammonia and hydrochloric acid content in biological samples. The method of data analysis can be directly translated to other nanomaterials to analyze their applicability in the field of biosensory.

Keywords: electrical impedance spectroscopy, spectroscopy data analysis, selective adsorption sensor, nanotechnology

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1138 Automatic Content Curation of Visual Heritage

Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

Abstract:

Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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1137 Exploring Open Innovation Practice in Start-Ups within an Innovation Ecosystem

Authors: Yassine Mehros, Jean-Michel Degeorge, Abdelaziz Elabjani

Abstract:

Innovation has long been considered the key to the survival, development, and growth of companies. It is a process in which start-ups play a key role, but they suffer from a structural lack of resources, which hinders the development of new innovations and their commercialization. The use of alternative channels to access resources is therefore becoming a necessity to overcome this constraint and identify opportunities. This is why they can be part of large communities of interdependent actors, namely innovation ecosystems that are part of a logic of sharing and open innovation. This research aims to explore and better understand OI in start-ups within an innovation ecosystem. We offer an exploratory qualitative study with start-ups and other actors in the Saint-Étienne innovation ecosystem. Our paper explored the characteristics and main actors of the Saint-Etienne innovation ecosystem, focusing on start-ups. We have identified the motivations of start-up’s adopting OI, its difficulties, its risks, and its impact on their growth. Also, our results show the existence of strong links between the different actors in the ecosystem. In addition, a strong trust has been established between these actors thanks to the geographical proximity; the start-ups manage to get in touch with the different actors of their innovation ecosystem by practicing OI. The actors collaborate on projects involving companies and, in particular, start-ups.

Keywords: open innovation, start-ups, Innovation ecosystem, actors

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1136 Relative Clause Attachment Ambiguity Resolution in L2: the Role of Semantics

Authors: Hamideh Marefat, Eskandar Samadi

Abstract:

This study examined the effect of semantics on processing ambiguous sentences containing Relative Clauses (RCs) preceded by a complex Determiner Phrase (DP) by Persian-speaking learners of L2 English with different proficiency and Working Memory Capacities (WMCs). The semantic relationship studied was one between the subject of the main clause and one of the DPs in the complex DP to see if, as predicted by Spreading Activation Model, priming one of the DPs through this semantic manipulation affects the L2ers’ preference. The results of a task using Rapid Serial Visual Processing (time-controlled paradigm) showed that manipulation of the relationship between the subject of the main clause and one of the DPs in the complex DP preceding RC has no effect on the choice of the antecedent; rather, the L2ers' processing is guided by the phrase structure information. Moreover, while proficiency did not have any effect on the participants’ preferences, WMC brought about a difference in their preferences, with a DP1 preference by those with a low WMC. This finding supports the chunking hypothesis and the predicate proximity principle, which is the strategy also used by monolingual Persian speakers.

Keywords: semantics, relative clause processing, ambiguity resolution, proficiency, working memory capacity

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1135 Mitigation of Electromagnetic Interference Generated by GPIB Control-Network in AC-DC Transfer Measurement System

Authors: M. M. Hlakola, E. Golovins, D. V. Nicolae

Abstract:

The field of instrumentation electronics is undergoing an explosive growth, due to its wide range of applications. The proliferation of electrical devices in a close working proximity can negatively influence each other’s performance. The degradation in the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic interference originating in the General Purpose Interface Bus (GPIB) control-network of the ac-dc transfer measurement system. Remedial measures of reducing measurement errors and failure of range of industrial devices due to EMI have been explored. The ac-dc transfer measurement system was analyzed for the common-mode (CM) EMI effects. Further investigation of coupling path as well as more accurate identification of noise propagation mechanism has been outlined. To prevent the occurrence of common-mode (ground loops) which was identified between the GPIB system control circuit and the measurement circuit, a microcontroller-driven GPIB switching isolator device was designed, prototyped, programmed and validated. This mitigation technique has been explored to reduce EMI effectively.

Keywords: CM, EMI, GPIB, ground loops

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1134 Gendered Water Insecurity: a Structural Equation Approach for Female-Headed Households in South Africa

Authors: Saul Ngarava, Leocadia Zhou, Nomakhaya Monde

Abstract:

Water crises have the fourth most significant societal impact after weapons of mass destruction, climate change, and extreme weather conditions, ahead of natural disasters. Intricacies between women and water are central to achieving the 2030 Sustainable Development Goals (SDGs). The majority of the 1.2 billion poor people worldwide, with two-thirds being women, and mostly located in Sub Sahara Africa (SSA) and South Asia, do not have access to safe and reliable sources of water. There exist gendered differences in water security based on the division of labour associating women with water. Globally, women and girls are responsible for water collection in 80% of the households which have no water on their premises. Women spend 16 million hours a day collecting water, while men and children spend 6 million and 4 million per day, respectively, which is time foregone in the pursuit of other livelihood activities. Due to their proximity and activities concerning water, women are vulnerable to water insecurity through exposures to water-borne diseases, fatigue from physically carrying water, and exposure to sexual and physical harassment, amongst others. Proximity to treated water and their wellbeing also has an effect on their sensitivity and adaptive capacity to water insecurity. The great distances, difficult terrain and heavy lifting expose women to vulnerabilities of water insecurity. However, few studies have quantified the vulnerabilities and burdens on women, with a few taking a phenomenological qualitative approach. Vulnerability studies have also been scanty in the water security realm, with most studies taking linear forms of either quantifying exposures, sensitivities or adaptive capacities in climate change studies. The current study argues for the need for a water insecurity vulnerability assessment, especially for women into research agendas as well as policy interventions, monitoring, and evaluation. The study sought to identify and provide pathways through which female-headed households were water insecure in South Africa, the 30th driest country in the world. This was through linking the drinking water decision as well as the vulnerability frameworks. Secondary data collected during the 2016 General Household Survey (GHS) was utilised, with a sample of 5928 female-headed households. Principal Component Analysis and Structural Equation Modelling were used to analyse the data. The results show dynamic relationships between water characteristics and water treatment. There were also associations between water access and wealth status of the female-headed households. Association was also found between water access and water treatment as well as between wealth status and water treatment. The study concludes that there are dynamic relationships in water insecurity (exposure, sensitivity, and adaptive capacity) for female-headed households in South Africa. The study recommends that a multi-prong approach is required in tackling exposures, sensitivities, and adaptive capacities to water insecurity. This should include capacitating and empowering women for wealth generation, improve access to water treatment equipment as well as prioritising the improvement of infrastructure that brings piped and safe water to female-headed households.

Keywords: gender, principal component analysis, structural equation modelling, vulnerability, water insecurity

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1133 Improved Distance Estimation in Dynamic Environments through Multi-Sensor Fusion with Extended Kalman Filter

Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

Abstract:

The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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1132 Cross-Dialect Sentence Transformation: A Comparative Analysis of Language Models for Adapting Sentences to British English

Authors: Shashwat Mookherjee, Shruti Dutta

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This study explores linguistic distinctions among American, Indian, and Irish English dialects and assesses various Language Models (LLMs) in their ability to generate British English translations from these dialects. Using cosine similarity analysis, the study measures the linguistic proximity between original British English translations and those produced by LLMs for each dialect. The findings reveal that Indian and Irish English translations maintain notably high similarity scores, suggesting strong linguistic alignment with British English. In contrast, American English exhibits slightly lower similarity, reflecting its distinct linguistic traits. Additionally, the choice of LLM significantly impacts translation quality, with Llama-2-70b consistently demonstrating superior performance. The study underscores the importance of selecting the right model for dialect translation, emphasizing the role of linguistic expertise and contextual understanding in achieving accurate translations.

Keywords: cross-dialect translation, language models, linguistic similarity, multilingual NLP

Procedia PDF Downloads 75