Search results for: smart micro-grid
423 Methods of Interpolating Temperature and Rainfall Distribution in Northern Vietnam
Authors: Thanh Van Hoang, Tien Yin Chou, Yao Min Fang, Yi Min Huang, Xuan Linh Nguyen
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Reliable information on the spatial distribution of annual rainfall and temperature is essential in research projects relating to urban and regional planning. This research presents results of a classification of temperature and rainfall in the Red River Delta of northern Vietnam based on measurements from seven meteorological stations (Ha Nam, Hung Yen, Lang, Nam Dinh, Ninh Binh, Phu Lien, Thai Binh) in the river basin over a thirty-years period from 1982-2011. The average accumulated rainfall trends in the delta are analysed and form the basis of research essential to weather and climate forecasting. This study employs interpolation based on the Kriging Method for daily rainfall (min and max) and daily temperature (min and max) in order to improve the understanding of sources of variation and uncertainly in these important meteorological parameters. To the Kriging method, the results will show the different models and the different parameters based on the various precipitation series. The results provide a useful reference to assist decision makers in developing smart agriculture strategies for the Red River Delta in Vietnam.Keywords: spatial interpolation method, ArcGIS, temperature variability, rainfall variability, Red River Delta, Vietnam
Procedia PDF Downloads 327422 Intelligent Control of Doubly Fed Induction Generator Wind Turbine for Smart Grid
Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef
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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm
Procedia PDF Downloads 265421 Comparing Image Processing and AI Techniques for Disease Detection in Plants
Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller
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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation
Procedia PDF Downloads 378420 A Study to Examine the Use of Traditional Agricultural Practices to Fight the Effects of Climate Change
Authors: Rushva Parihar, Anushka Barua
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The negative repercussions of a warming planet are already visible, with biodiversity loss, water scarcity, and extreme weather events becoming ever so frequent. The agriculture sector is perhaps the most impacted, and modern agriculture has failed to defend farmers from the effects of climate change. This, coupled with the added pressure of higher demands for food production caused due to population growth, has only compounded the impact. Traditional agricultural practices that are routed in indigenous knowledge have long safeguarded the delicate balance of the ecosystem through sustainable production techniques. This paper uses secondary data to explore these traditional processes (like Beejamrita, Jeevamrita, sheep penning, earthen bunding, and others) from around the world that have been developed over centuries and focuses on how they can be used to tackle contemporary issues arising from climate change (such as nutrient and water loss, soil degradation, increased incidences of pests). Finally, the resulting framework has been applied to the context of Indian agriculture as a means to combat climate change and improve food security, all while encouraging documentation and transfer of local knowledge as a shared resource among farmers.Keywords: sustainable food systems, traditional agricultural practices, climate smart agriculture, climate change, indigenous knowledge
Procedia PDF Downloads 125419 Advanced Hybrid Particle Swarm Optimization for Congestion and Power Loss Reduction in Distribution Networks with High Distributed Generation Penetration through Network Reconfiguration
Authors: C. Iraklis, G. Evmiridis, A. Iraklis
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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid
Procedia PDF Downloads 443418 Computational Neurosciences: An Inspiration from Biological Neurosciences
Authors: Harsh Sadawarti, Kamal Malik
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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe
Procedia PDF Downloads 108417 Encryption and Decryption of Nucleic Acid Using Deoxyribonucleic Acid Algorithm
Authors: Iftikhar A. Tayubi, Aabdulrahman Alsubhi, Abdullah Althrwi
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The deoxyribonucleic acid text provides a single source of high-quality Cryptography about Deoxyribonucleic acid sequence for structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to encrypt and decrypt Deoxy Ribonucleic Acid sequence text. It includes complex, securing by using Algorithm to encrypt and decrypt Deoxy Ribonucleic Acid sequence. The utility of this Deoxy Ribonucleic Acid Sequence Text is that, it can provide a user-friendly interface for users to Encrypt and Decrypt store the information about Deoxy Ribonucleic Acid sequence. These interfaces created in this project will satisfy the demands of the scientific community by providing fully encrypt of Deoxy Ribonucleic Acid sequence during this website. We have adopted a methodology by using C# and Active Server Page.NET for programming which is smart and secure. Deoxy Ribonucleic Acid sequence text is a wonderful piece of equipment for encrypting large quantities of data, efficiently. The users can thus navigate from one encoding and store orange text, depending on the field for user’s interest. Algorithm classification allows a user to Protect the deoxy ribonucleic acid sequence from change, whether an alteration or error occurred during the Deoxy Ribonucleic Acid sequence data transfer. It will check the integrity of the Deoxy Ribonucleic Acid sequence data during the access.Keywords: algorithm, ASP.NET, DNA, encrypt, decrypt
Procedia PDF Downloads 230416 Health and Climate Changes: "Ippocrate" a New Alert System to Monitor and Identify High Risk
Authors: A. Calabrese, V. F. Uricchio, D. di Noia, S. Favale, C. Caiati, G. P. Maggi, G. Donvito, D. Diacono, S. Tangaro, A. Italiano, E. Riezzo, M. Zippitelli, M. Toriello, E. Celiberti, D. Festa, A. Colaianni
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Climate change has a severe impact on human health. There is a vast literature demonstrating temperature increase is causally related to cardiovascular problem and represents a high risk for human health, but there are not study that improve a solution. In this work, it is studied how the clime influenced the human parameter through the analysis of climatic conditions in an area of the Apulia Region: Capurso Municipality. At the same time, medical personnel involved identified a set of variables useful to define an index describing health condition. These scientific studies are the base of an innovative alert system, IPPOCRATE, whose aim is to asses climate risk and share information to population at risk to support prevention and mitigation actions. IPPOCRATE is an e-health system, it is designed to provide technological support to analysis of health risk related to climate and provide tools for prevention and management of critical events. It is the first integrated system of prevention of human risk caused by climate change. IPPOCRATE calculates risk weighting meteorological data with the vulnerability of monitored subjects and uses mobile and cloud technologies to acquire and share information on different data channels. It is composed of four components: Multichannel Hub. Multichannel Hub is the ICT infrastructure used to feed IPPOCRATE cloud with a different type of data coming from remote monitoring devices, or imported from meteorological databases. Such data are ingested, transformed and elaborated in order to be dispatched towards mobile app and VoIP phone systems. IPPOCRATE Multichannel Hub uses open communication protocols to create a set of APIs useful to interface IPPOCRATE with 3rd party applications. Internally, it uses non-relational paradigm to create flexible and highly scalable database. WeHeart and Smart Application The wearable device WeHeart is equipped with sensors designed to measure following biometric variables: heart rate, systolic blood pressure and diastolic blood pressure, blood oxygen saturation, body temperature and blood glucose for diabetic subjects. WeHeart is designed to be easy of use and non-invasive. For data acquisition, users need only to wear it and connect it to Smart Application by Bluetooth protocol. Easy Box was designed to take advantage from new technologies related to e-health care. EasyBox allows user to fully exploit all IPPOCRATE features. Its name, Easy Box, reveals its purpose of container for various devices that may be included depending on user needs. Territorial Registry is the IPPOCRATE web module reserved to medical personnel for monitoring, research and analysis activities. Territorial Registry allows to access to all information gathered by IPPOCRATE using GIS system in order to execute spatial analysis combining geographical data (climatological information and monitored data) with information regarding the clinical history of users and their personal details. Territorial Registry was designed for different type of users: control rooms managed by wide area health facilities, single health care center or single doctor. Territorial registry manages such hierarchy diversifying the access to system functionalities. IPPOCRATE is the first e-Health system focused on climate risk prevention.Keywords: climate change, health risk, new technological system
Procedia PDF Downloads 867415 Exploring the Activity Fabric of an Intelligent Environment with Hierarchical Hidden Markov Theory
Authors: Chiung-Hui Chen
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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object
Procedia PDF Downloads 233414 Behavioral Response of Bee Farmers to Climate Change in South East, Nigeria
Authors: Jude A. Mbanasor, Chigozirim N. Onwusiribe
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The enigma climate change is no longer an illusion but a reality. In the recent years, the Nigeria climate has changed and the changes are shown by the changing patterns of rainfall, the sunshine, increasing level carbon and nitrous emission as well as deforestation. This study analyzed the behavioural response of bee keepers to variations in the climate and the adaptation techniques developed in response to the climate variation. Beekeeping is a viable economic activity for the alleviation of poverty as the products include honey, wax, pollen, propolis, royal jelly, venom, queens, bees and their larvae and are all marketable. The study adopted the multistage sampling technique to select 120 beekeepers from the five states of Southeast Nigeria. Well-structured questionnaires and focus group discussions were adopted to collect the required data. Statistical tools like the Principal component analysis, data envelopment models, graphs, and charts were used for the data analysis. Changing patterns of rainfall and sunshine with the increasing rate of deforestation had a negative effect on the habitat of the bees. The bee keepers have adopted the Kenya Top bar and Langstroth hives and they establish the bee hives on fallow farmland close to the cultivated communal farms with more flowering crops.Keywords: climate, farmer, response, smart
Procedia PDF Downloads 131413 A Case Study of Mobile Game Based Learning Design for Gender Responsive STEM Education
Authors: Raluca Ionela Maxim
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Designing a gender responsive Science, Technology, Engineering and Mathematics (STEM) mobile game based learning solution (mGBL) is a challenge in terms of content, gamification level and equal engagement of girls and boys. The goal of this case study was to research and create a high-fidelity prototype design of a mobile game that contains role-models as avatars that guide and expose girls and boys to STEM learning content. For this research purpose it was applied the methodology of design sprint with five-phase process that combines design thinking principles. The technique of this methodology comprises smart interviews with STEM experts, mind-map creation, sketching, prototyping and usability testing of the interactive prototype of the gender responsive STEM mGBL. The results have shown that the effect of the avatar/role model had a positive impact. Therefore, by exposing students (boys and girls) to STEM role models in an mGBL tool is helpful for the decreasing of the gender inequalities in STEM fields.Keywords: design thinking, design sprint, gender-responsive STEM education, mobile game based learning, role-models
Procedia PDF Downloads 134412 Colour Quick Response Code with High Damage Resistance Capability
Authors: Minh Nguyen
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Today, QR or Quick Response Codes are prevalent, and mobile/smart devices can efficiently read and understand them. Therefore, we can see their appearance in many areas, such as storing web pages/websites, business phone numbers, redirecting to an app download, business location, social media. The popularity of the QR Code is mainly because of its many advantages, such as it can hold a good amount of information, is small, easy to scan and read by a general RGB camera, and it can still work with some damages on its surface. However, there are still some issues. For instance, some areas needed to be kept untouched for its successful decode (e.g., the “Finder Patterns,” the “Quiet Zone,” etc.), the capability of built-in auto-correction is not robust enough, and it is not flexible enough for many application such as Augment Reality (AR). We proposed a new Colour Quick Response Code that has several advantages over the original ones: (1) there is no untouchable area, (2) it allows up to 40% of the entire code area to be damaged, (3) it is more beneficial for Augmented Reality applications, and (4) it is back-compatible and readable by available QR Code scanners such as Pyzbar. From our experience, our Colour Quick Response Code is significantly more flexible on damage compared to the original QR Code. Our code is believed to be suitable in situations where standard 2D Barcodes fail to work, such as curved and shiny surfaces, for instance, medical blood test sample tubes and syringes.Keywords: QR code, computer vision, image processing, 2D barcode
Procedia PDF Downloads 118411 An Application for Risk of Crime Prediction Using Machine Learning
Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento
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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.Keywords: crime prediction, machine learning, public safety, smart city
Procedia PDF Downloads 110410 Potential of Visualization and Information Modeling on Productivity Improvement and Cost Saving: A Case Study of a Multi-Residential Construction Project
Authors: Sara Rankohi, Lloyd Waugh
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Construction sites are information saturated. Digitalization is hitting construction sites to meet the incredible demand of knowledge sharing and information documentations. From flying drones, 3D Lasers scanners, pocket mobile applications, to augmented reality glasses and smart helmet, visualization technologies help real-time information imposed straight onto construction professional’s field of vision. Although these technologies are very applicable and can have the direct impact on project cost and productivity, experience shows that only a minority of construction professionals quickly adapt themselves to benefit from them in practice. The majority of construction managers still tend to apply traditional construction management methods. This paper investigates a) current applications of visualization technologies in construction projects management, b) the direct effect of these technologies on productivity improvement and cost saving of a multi-residential building project via a case study on Mac Taggart Senior Care project located in Edmonton, Alberta. The research shows the imaged based technologies have a direct impact on improving project productivity and cost savings.Keywords: image-based technologies, project management, cost, productivity improvement
Procedia PDF Downloads 359409 Crow Search Algorithm-Based Task Offloading Strategies for Fog Computing Architectures
Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara
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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.Keywords: IoT, fog computing, task offloading, efficient crow search algorithm
Procedia PDF Downloads 56408 Development of an Energy Independant DC Building Demonstrator for Insulated Island Site
Authors: Olivia Bory Devisme, Denis Genon-Catalot, Frederic Alicalapa, Pierre-Olivier Lucas De Peslouan, Jean-Pierre Chabriat
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In the context of climate change, it is essential that island territories gain energy autonomy. Currently mostly dependent on fossil fuels, the island of Reunion lo- cated in the Indian Ocean nevertheless has a high potential for solar energy. As the market for photovoltaic panels has been growing in recent years, the issues of energy losses linked to the multiple conversions from direct current to alternating current are emerging. In order to quantify these advantages and disadvantages by a comparative study, this document present the measurements carried out on a direct current test bench, particularly for lighting, ventilation, air condi- tioning and office equipment for the tertiary sector. All equipment is supplied with DC power from energy produced by photovoltaic panels. A weather sta- tion, environmental indoor sensors, and drivers are also used to control energy. Self-consumption is encouraged in order to manage different priorities between user consumption and energy storage in a lithium iron phosphate battery. The measurements are compared to a conventional electrical architecture (DC-AC- DC) for energy consumption, equipment overheating, cost, and life cycle analysis.Keywords: DC microgrids, solar energy, smart buildings, storage
Procedia PDF Downloads 160407 Fuzzy Neuro Approach for Integrated Water Management System
Authors: Stuti Modi, Aditi Kambli
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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution
Procedia PDF Downloads 185406 Developing Measurement Instruments for Enterprise Resources Planning (ERP) Post-Implementation Failure Model
Authors: Malihe Motiei, Nor Hidayati Zakaria, Davide Aloini
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This study aims to present a method to develop the failure measurement model for ERP post-implementation. To achieve this outcome, the study firstly evaluates the suitability of Technology-Organization-Environment framework for the proposed conceptual model. This study explains how to discover the constructs and subsequently to design and evaluate the constructs as formative or reflective. Constructs are used including reflective and purely formative. Then, the risk dimensions are investigated to determine the instruments to examine the impact of risk on ERP failure after implementation. Two construct as formative constructs consist inadequate implementation and poor organizational decision making. Subsequently six construct as reflective construct include technical risks, operational risks, managerial risks, top management risks, lack of external risks, and user’s inefficiency risks. A survey was conducted among Iranian industries to collect data. 69 data were collected from manufacturing sectors and the data were analyzed by Smart PLS software. The results indicated that all measurements included 39 critical risk factors were acceptable for the ERP post-implementation failure model.Keywords: critical risk factors (CRFs), ERP projects, ERP post-implementation, measurement instruments, ERP system failure measurement model
Procedia PDF Downloads 361405 BIM Data and Digital Twin Framework: Preserving the Past and Predicting the Future
Authors: Mazharuddin Syed Ahmed
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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.Keywords: building information modelling, circular economy integration, digital twin, predictive analytics
Procedia PDF Downloads 41404 Smart Polymeric Nanoparticles Loaded with Vincristine Sulfate for Applications in Breast Cancer Drug Delivery in MDA-MB 231 and MCF7 Cell Lines
Authors: Reynaldo Esquivel, Pedro Hernandez, Aaron Martinez-Higareda, Sergio Tena-Cano, Enrique Alvarez-Ramos, Armando Lucero-Acuna
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Stimuli-responsive nanomaterials play an essential role in loading, transporting and well-distribution of anti-cancer compounds in the cellular surroundings. The outstanding properties as the Lower Critical Solution Temperature (LCST), hydrolytic cleavage and protonation/deprotonation cycle, govern the release and delivery mechanisms of payloads. In this contribution, we experimentally determine the load efficiency and release of antineoplastic Vincristine Sulfate into PNIPAM-Interpenetrated-Chitosan (PIntC) nanoparticles. Structural analysis was performed by Fourier Transform Infrared Spectroscopy (FT-IR) and Proton Nuclear Magnetic Resonance (1HNMR). ζ-Potential (ζ) and Hydrodynamic diameter (DH) measurements were monitored by Electrophoretic Mobility (EM) and Dynamic Light scattering (DLS) respectively. Mathematical analysis of the release pharmacokinetics reveals a three-phase model above LCST, while a monophasic of Vincristine release model was observed at 32 °C. Cytotoxic essays reveal a noticeable enhancement of Vincristine effectiveness at low drug concentration on HeLa cervix cancer and MDA-MB-231 breast cancer.Keywords: nanoparticles, vincristine, drug delivery, PNIPAM
Procedia PDF Downloads 154403 The Internet of Healthcare Things: A European Perspective and a Review of Ethical Concerns
Authors: M. Emmanouilidou
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The Internet of Things (IoT) is a disruptive technological paradigm that is at the center of the digital evolution by integrating physical and virtual worlds leading to the creation of extended interconnected ecosystems that are characterized as smart environments. The concept of the IoT has a broad range of applications in different industries including the healthcare sector. The Internet of Healthcare Things (IoHT), a branch of the IoT, is expected to bring promising benefits to all involved stakeholders and accelerate the revolution of the healthcare sector through a transition towards preventive and personalized medicine. The socio-economic challenges that the healthcare sector is facing further emphasize the need for a radical transformation of healthcare systems in both developed and developing countries with the role of pervasive technological innovations, such as IoHT, recognized as key to counteract the relevant challenges. Besides the number of potential opportunities that IoHT presents, there are fundamental ethical concerns that need to be considered and addressed in relation to the application of IoHT. This paper contributes to the discussion of the emerging topic of IoHT by providing an overview of the role and potential of IoHT, highlighting the characteristics of the current and future healthcare landscape, reporting on the up-to-date status of IoHT in Europe and reflecting upon existing research in the ethics of IoHT by incorporating additional ethical dimensions that have been ignored which can provide pathways for future research in the field.Keywords: ethics, Europe, healthcare, Internet of Things
Procedia PDF Downloads 133402 Information Theoretic Approach for Beamforming in Wireless Communications
Authors: Syed Khurram Mahmud, Athar Naveed, Shoaib Arif
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Beamforming is a signal processing technique extensively utilized in wireless communications and radars for desired signal intensification and interference signal minimization through spatial selectivity. In this paper, we present a method for calculation of optimal weight vectors for smart antenna array, to achieve a directive pattern during transmission and selective reception in interference prone environment. In proposed scheme, Mutual Information (MI) extrema are evaluated through an energy constrained objective function, which is based on a-priori information of interference source and desired array factor. Signal to Interference plus Noise Ratio (SINR) performance is evaluated for both transmission and reception. In our scheme, MI is presented as an index to identify trade-off between information gain, SINR, illumination time and spatial selectivity in an energy constrained optimization problem. The employed method yields lesser computational complexity, which is presented through comparative analysis with conventional methods in vogue. MI based beamforming offers enhancement of signal integrity in degraded environment while reducing computational intricacy and correlating key performance indicators.Keywords: beamforming, interference, mutual information, wireless communications
Procedia PDF Downloads 278401 Smart Demand Response: A South African Pragmatic, Non-Destructive and Alternative Advanced Metering Infrastructure-Based Maximum Demand Reduction Methodology
Authors: Christo Nicholls
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The National Electricity Grid (NEG) in South Africa has been under strain for the last five years. This overburden of the NEG led Eskom (the State-Owned Entity responsible for the NEG) to implement a blunt methodology to assist them in reducing the maximum demand (MD) on the NEG, when required, called Loadshedding. The challenge of this methodology is that not only does it lead to immense technical issues with the distribution network equipment, e.g., transformers, due to the frequent abrupt off and on switching, it also has a broader negative fiscal impact on the distributors, as their key consumers (commercial & industrial) are now grid defecting due to the lack of Electricity Security Provision (ESP). This paper provides a pragmatic alternative methodology utilizing specific functionalities embedded within direct-connect single and three-phase Advanced Meter Infrastructure (AMI) Solutions deployed within the distribution network, in conjunction with a Multi-Agent Systems Based AI implementation focused on Automated Negotiation Peer-2-Peer trading. The results of this research clearly illustrate, not only does methodology provide a factual percentage contribution towards the NEG MD at the point of consideration, it also allows the distributor to leverage the real-time MD data from key consumers to activate complex, yet impact-measurable Demand Response (DR) programs.Keywords: AI, AMI, demand response, multi-agent
Procedia PDF Downloads 110400 Effect of an Interface Defect in a Patch/Layer Joint under Dynamic Time Harmonic Load
Authors: Elisaveta Kirilova, Wilfried Becker, Jordanka Ivanova, Tatyana Petrova
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The study is a continuation of the research on the hygrothermal piezoelectric response of a smart patch/layer joint with undesirable interface defect (gap) at dynamic time harmonic mechanical and electrical load and environmental conditions. In order to find the axial displacements, shear stress and interface debond length in a closed analytical form for different positions of the interface gap, the 1D modified shear lag analysis is used. The debond length is represented as a function of many parameters (frequency, magnitude, electric displacement, moisture and temperature, joint geometry, position of the gap along the interface, etc.). Then the Genetic algorithm (GA) is implemented to find this position of the gap along the interface at which a vanishing/minimal debond length is ensured, e.g to find the most harmless position for the safe work of the structure. The illustrative example clearly shows that analytical shear-lag solutions and GA method can be combined successfully to give an effective prognosis of interface shear stress and interface delamination in patch/layer structure at combined loading with existing defects. To show the effect of the position of the interface gap, all obtained results are given in figures and discussed.Keywords: genetic algorithm, minimal delamination, optimal gap position, shear lag solution
Procedia PDF Downloads 299399 Enhancement of Environmental Security by the Application of Wireless Sensor Network in Nigeria
Authors: Ahmadu Girgiri, Lawan Gana Ali, Mamman M. Baba
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Environmental security clearly articulates the perfections and developments of various communities around the world irrespective of the region, culture, religion or social inclination. Although, the present state of insecurity has become serious issue devastating the peace, unity, stability and progress of man and his physical environment particularly in developing countries. Recently, measure of security and it management in Nigeria has been a bottle-neck to the effectiveness and advancement of various sectors that include; business, education, social relations, politics and above all an economy. Several measures have been considered on mitigating environment insecurity such as surveillance, demarcation, security personnel empowerment and the likes, but still the issue remains disturbing. In this paper, we present the application of new technology that contributes to the improvement of security surveillance known as “Wireless Sensor Network (WSN)”. The system is new, smart and emerging technology that provides monitoring, detection and aggregation of information using sensor nodes and wireless network. WSN detects, monitors and stores information or activities in the deployed area such as schools, environment, business centers, public squares, industries, and outskirts and transmit to end users. This will reduce the cost of security funding and eases security surveillance depending on the nature and the requirement of the deployment.Keywords: application, environment, insecurity, sensor, wireless sensor network
Procedia PDF Downloads 262398 Uncontrolled Urbanization Leads to Main Challenge for Sustainable Development of Mongolia
Authors: Davaanyam Surenjav, Chinzolboo Dandarbaatar, Ganbold Batkhuyag
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Primate city induced rapid urbanization has been become one of the main challenges in sustainable development in Mongolia like other developing countries since transition to market economy in 1990. According due to statistical yearbook, population number of Ulaanbaatar city has increased from 0.5 million to 1.5 million for last 30 years and contains now almost half (47%) of total Mongolian population. Rural-Ulaanbaatar and local Cities-Ulaanbaatar city migration leads to social issues like uncontrolled urbanization, income inequality, poverty, overwork of public service, economic over cost for redevelopment and limitation of transport and environmental degradation including air, noise, water and soil pollution. Most thresholds of all of the sustainable urban development main and sub-indicators over exceeded from safety level to unsafety level in Ulaanbaatar. So, there is an urgent need to remove migration pull factors including some administrative and high education functions from Ulaanbaatar city to its satellite cities or secondary cities. Moreover, urban smart transport system and green and renewable energy technologies should be introduced to urban development master plan of Ulaanbaatar city.Keywords: challenge for sustainable urban development, migration factors, primate city , urban safety thresholds
Procedia PDF Downloads 130397 Vulnerability of Indian Agriculture to Climate Change: A Study of the Himalayan Region State
Authors: Rajendra Kumar Isaac, Monisha Isaac
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Climate variability and changes are the emerging challenges for Indian agriculture with the growing population to ensure national food security. A study was conducted to assess the Climatic Change effects in medium to low altitude areas of the Himalayan region causing changes in land use and cereal crop productivity with the various climatic parameters. The rainfall and temperature changes from 1951 to 2013 were studied at four locations of varying altitudes, namely Hardwar, Rudra Prayag, Uttar Kashi and Tehri Garwal. It was observed that there is noticeable increment in temperature on all the four locations. It was surprisingly observed that the mean rainfall intensity of 30 minutes duration has increased at the rate of 0.1 mm/hours since 2000. The study shows that the combined effect of increasing temperature, rainfall, runoff and urbanization at the mid-Himalayan region is causing an increase in various climatic disasters and changes in agriculture patterns. A noticeable change in cropping patterns, crop productivity and land use change was observed. Appropriate adaptation and mitigation strategies are necessary to ensure that sustainable and climate-resilient agriculture. Appropriate information is necessary for farmers, as well as planners and decision makers for developing, disseminating and adopting climate-smart technologies.Keywords: climate variability, agriculture, land use, mitigation strategies
Procedia PDF Downloads 269396 The Effect of Carbon Nanofibers on the Electrical Resistance of Cementitious Composites
Authors: Reza Pourjafar, Morteza Sohrabi-Gilani, Mostafa Jamshidi Avanaki, Malek Mohammad Ranjbar
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Cementitious composites like concrete, are the most widely used materials in civil infrastructures. Numerous investigations on fiber’s effect on the properties of cement-based composites have been conducted in the last few decades. The use of fibers such as carbon nanofibers (CNFs) and carbon nanotubes (CNTs) in these materials is an ongoing field and needs further researches and studies. Excellent mechanical, thermal, and electrical properties of carbon nanotubes and nanofibers have motivated the development of advanced nanocomposites with outstanding and multifunctional properties. In this study, the electrical resistance of CNF reinforced cement mortar was examined. Three different dosages of CNF were used, and the resistances were compared to plain cement mortar. One of the biggest challenges in this study is dispersing CNF particles in the mortar mixture. Therefore, polycarboxylate superplasticizer and ultrasonication of the mixture have been selected for the purpose of dispersing CNFs in the cement matrix. The obtained results indicated that the electrical resistance of the CNF reinforced mortar samples decreases with increasing CNF content, which would be the first step towards examining strain and damage monitoring ability of cementitious composites containing CNF for structural health monitoring purposes.Keywords: carbon nanofiber, cement and concrete, CNF reinforced mortar, smart mater, strain monitoring, structural health monitoring
Procedia PDF Downloads 145395 The Moderation Effect of Smart Phone Addiction in Relationship between Self-Leadership and Innovative Behavior
Authors: Gi-Ryun Park, Gye-Wan Moon, Dong-Hoon Yang
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This study aims to explore the positive effects of self-leadership and innovative behavior that'd been proven in the existing researches proactively and understand the regulation effects of smartphone addiction which has recently become an issue in Korea. This study conducted a convenient sampling of college students attending the four colleges located at Daegu. A total of 210 questionnaires in 5-point Likert scale were distributed to college students. Among which, a total of 200 questionnaires were collected for our final analysis data. Both correlation analysis and regression analysis were carried out to verify those questionnaires through SPSS 20.0. As a result, college students' self-leadership had a significantly positive impact on innovative behavior (B= .210, P= .003). In addition, it is found that the relationship between self-leadership and innovative behavior can be adjusted depending on the degree of smartphone addiction in college students (B= .264, P= .000). This study could first understand the negative effects of smartphone addiction and find that if students' self-leadership is improved in terms of self-management and unnecessary use of smartphone is controlled properly, innovative behavior can be improved. In addition, this study is significant in that it attempts to identify a new impact of smartphone addiction with the recent environmental changes, unlike the existing researches that'd been carried out from the perspective of organizational behavior theory.Keywords: innovative behavior, revolutionary behavior, self-leadership, smartphone addiction
Procedia PDF Downloads 258394 Reactive Power Control with Plug-In Electric Vehicles
Authors: Mostafa Dastori, Sirus Mohammadi
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While plug-in electric vehicles (PEVs) potentially have the capability to fulfill the energy storage needs of the electric grid, the degradation on the battery during this operation makes it less preferable by the auto manufacturers and consumers. On the other hand, the on-board chargers can also supply energy storage system applications such as reactive power compensation, voltage regulation, and power factor correction without the need of engaging the battery with the grid and thereby preserving its lifetime. It presents the design motives of single-phase on-board chargers in detail and makes a classification of the chargers based on their future vehicle-to-grid usage. The pros and cons of each different ac–dc topology are discussed to shed light on their suit- ability for reactive power support. This paper also presents and analyzes the differences between charging-only operation and capacitive reactive power operation that results in increased demand from the dc-link capacitor (more charge/discharge cycles and in- creased second harmonic ripple current). Moreover, battery state of charge is spared from losses during reactive power operation, but converter output power must be limited below its rated power rating to have the same stress on the dc-link capacitor.Keywords: energy storage system, battery unit, cost, optimal sizing, plug-in electric vehicles (PEVs), smart grid
Procedia PDF Downloads 341