Search results for: smart signature

Authors: Tanuj Joshi

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Smart transportation is fast emerging as a solution to modern cities’ approach mobility issues, delayed emergency response rate and high congestion on streets. Present day scenario with Google Maps, Waze, Yelp etc. demonstrates how information and communications technologies controls the intelligent transportation system. This intangible and invisible infrastructure is largely guided by the big data analytics. On the other side, the exponential increase in Indian urban population has intensified the demand for better services and infrastructure to satisfy the transportation needs of its citizens. No doubt, India’s huge internet usage is looked as an important resource to guide to achieve this. However, with a projected number of over 40 billion objects connected to the Internet by 2025, the need for systems to handle massive volume of data (big data) also arises. This research paper attempts to identify the ways of exploiting the big data variables which will aid commuters on Indian tracks. This study explores real life inputs by conducting survey and interviews to identify which gaps need to be targeted to better satisfy the customers. Several experts at Mumbai Metropolitan Region Development Authority (MMRDA), Mumbai Metro and Brihanmumbai Electric Supply and Transport (BEST) were interviewed regarding the Information Technology (IT) systems currently in use. The interviews give relevant insights and requirements into the workings of public transportation systems whereas the survey investigates the macro situation.

Keywords: smart transportation, mobility issue, Mumbai transportation, big data, data analysis

Procedia PDF Downloads 178

Authors: Edlira Kalemi, Sule Yildirim-Yayilgan

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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.

Keywords: criminal digital evidence, social media, ontologies, reasoning

Procedia PDF Downloads 388

Authors: Emanuele A. Solagna, Ricardo S, Tozetto, Roberto dos S. Rabello

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Nowadays, physical processes are becoming digitized by the evolution of communication, sensing and storage technologies which promote the development of smart cities. The evolution of this technology has generated multiple challenges related to the generation of big data and the active participation of electronic devices in society. Thus, devices can send information that is captured and processed over large areas, but there is no guarantee that all the obtained data amount will be effectively stored and correctly persisted. Because, depending on the technology which is used, there are parameters that has huge influence on the full delivery of information. This article aims to characterize the project, currently under development, of a platform that based on data science will perform a performance and effectiveness evaluation of an industrial network that implements LoRaWAN technology considering its main parameters configuration relating these parameters to the information loss.

Keywords: Internet of Things, LoRa, LoRaWAN, smart cities

Procedia PDF Downloads 148

Authors: Katarzyna Pawęska, Aleksandra Bawiec, Ewa Burszta-Adamiak, Wiesław Fiałkiewicz

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The water shortage becomes a serious problem not only in African and Middle Eastern countries, but also recently in the European Union. Scarcity of water means that not all agricultural, industrial and municipal needs will be met. When the annual availability of renewable freshwater per capita is less than 1,700 cubic meters, countries begin to experience periodic or regular water shortages. The phenomenon of water stress is the result of an imbalance between the constantly growing demand for water and its availability. The constant development of industry, population growth, and climate changes make the situation even worse. The search for alternative water sources and independent supplies is becoming a priority for many countries. Data enabling the assessment of country’s condition regarding water resources, water consumption, water price, wastewater volume, forecasted climate changes e.g. temperature, precipitation, are scattered and their interpretation by common entrepreneurs may be difficult. For this purpose, a digital tool has been developed to support decisions related to the implementation of water and wastewater re-use systems, as a result of an international research project “Framework for organizational decision-making process in water reuse for smart cities” (SMART-WaterDomain) funded under the EIG-CONCERT Japan call on Smart Water Management for Sustainable Society. The developed geo-visualization tool graphically presents, among others, data about the capacity of wastewater treatment plants and the volume of water demand in the private and public sectors for Poland, Germany, and the Czech Republic. It is expected that such a platform, extended with economical water management data and climate forecasts (temperature, precipitation), will allow in the future independent investigation and assessment of water use rate and wastewater production on the local and regional scale. The tool is a great opportunity for small business owners, entrepreneurs, farmers, local authorities, and common users to analyze the impact of climate change on the availability of water in the regions of their business activities. Acknowledgments: The authors acknowledge the support of the Project Organisational Decision Making in Water Reuse for Smart Cities (SMART- WaterDomain), funded by The National Centre for Research and Development and supported by the EIG-Concert Japan.

Keywords: circular economy, digital tool, geo-visualization, wastewater re-use

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Authors: Weidong Fu, Qingsong Wang, Wei Hua, Ming Cheng, Giuseppe Buja

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A single-phase transformerless electric energy router (TL-EER) is proposed for renewable energy management and power quality improvement in smart homes. The proposed TL-EER only contains four semiconductor switching devices, which reduces costs greatly compared to traditional electric energy routers. TL-EER functions as intelligent systems that optimize the flow and distribution of energy within a grid, enabling seamless interaction between generation, storage, and consumption. In addition, TL-EER operates in multiple modes and could be converted to diverse topologies by changing the states of relays. As for power quality, voltage and current compensating methods are adapted. Thus, high-quality electrical energy could be transferred to the load, and the grid-side power factor could be improved. Finally, laboratory prototypes are established to validate the effectiveness of the system.

Keywords: transformerless, electric energy router, power flow, power quality, power factor

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Authors: Mehrzad Soltani, Pegah Rezaei

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In response to the escalating challenges posed by resource scarcity, urban congestion, and the dearth of green spaces, contemporary urban areas have undergone a remarkable transformation into smart cities. This evolution necessitates a strategic and forward-thinking approach to urban development, with the primary objective of diminishing and eventually eradicating dependence on non-renewable energy sources. This steadfast commitment to sustainable development is geared toward the continual enhancement of our global urban milieu, ensuring a healthier and more prosperous environment for forthcoming generations. This transformative vision has been meticulously shaped by an extensive research framework, incorporating in-depth field studies and investigations conducted at both neighborhood and city levels. Our holistic strategy extends its purview to encompass major cities and states, advocating for the realization of exceptional development firmly rooted in the principles of sustainable intelligence. At its core, this approach places a paramount emphasis on stringent pollution control measures, concurrently safeguarding ecological equilibrium and regional cohesion. Central to the realization of this vision is the widespread adoption of environmentally friendly materials and components, championing the cultivation of plant life and harmonious green spaces, and the seamless integration of intelligent lighting and irrigation systems. These systems, including solar panels and solar energy utilization, are deployed wherever feasible, effectively meeting the essential lighting and irrigation needs of these dynamic urban ecosystems. Overall, the transformation of urban areas into smart cities necessitates a holistic and innovative approach to urban development. By actively embracing sustainable intelligence and adhering to strict environmental standards, these cities pave the way for a brighter and more sustainable future, one that is marked by resilient, thriving, and eco-conscious urban communities.

Keywords: smart city, green urban, sustainability, urban management

Procedia PDF Downloads 72

Authors: Nikola Radovanovic, Petros Gkotsis, Mathieu Doussineau

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Aeronautics is regarded as a strategically important sector for European competitiveness. It was at the heart of European entrepreneurial development since the industry was born. Currently, the EU is the world leader in the production of civil aircraft, including helicopters, aircraft engines, parts, and components. It is recording a surplus in trade relating to aerospace products, which are exported all over the globe. Also, this industry shows above-average investments in research and development, as demonstrated in the patent activity in this area. The post-pandemic recovery of the industry will partly depend on the possibilities to streamline collaboration in further research and innovation activities. Aeronautics features as one of the often selected priority domains in smart specialisation, which represents the main regional and national approach in developing and implementing innovation policies in Europe. The basis for the selection of priority domains for smart specialisation lies in the mapping of innovative potential, with research and patent activities being among the key elements of this analysis. This research is aimed at identifying characteristics of the trends in research and patent activities in the regions and countries that base their competitiveness on the aeronautics sector. It is also aimed at determining the scope and patterns of collaborations in aeronautics between innovators from the European regions, focusing on revealing new technology areas that emerge from these collaborations. For this purpose, we developed a methodology based on desk research and the analysis of the PATSTAT patent database as well as the databases of R&I framework programmes.

Keywords: aeronautics, smart specialisation, innovation, research, regional policy

Procedia PDF Downloads 106

Authors: Sung Hyun Yoo, In Hwan Choi, Jun Ho Jung, Choon Ki Ahn, Myo Taeg Lim

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Home energy management system (HEMS) has been issued to reduce the power consumption. The HEMS performs electric power control for the indoor electric device. However, HEMS commonly treats the smart devices. In this paper, we suggest the output estimation of home legacy device using the artificial neural fuzzy inference system (ANFIS). This paper discusses the overview and the architecture of the system. In addition, accurate performance of the output estimation using the ANFIS inference system is shown via a numerical example.

Keywords: artificial neural fuzzy inference system (ANFIS), home energy management system (HEMS), smart device, legacy device

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Authors: Ankita Dixit

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A conference call using a mobile refers to a telephonic call in which several people talks to each other simultaneously. This is one of the most eminent features nowadays. This concept is already existing using LTE technology for mobile phones supporting SIM cards. Hence, currently, a conference call is possible only with the support of a SIM card, i.e., a Mobile operator. Bluetooth is a short-range wireless technology that is used for exchanging data between devices placed over short distances (up to 240 meters). This is a booming technology that is easily and freely available and has no dependency on network operators. Our study work proposes a smart system to enable conference calls with more than two mobile users without SIM support to communicate with each other simultaneously. The AI-based proposed solution will be self–governed, self-learned and will be intelligent enough to smartly switch between all callers connected via Bluetooth in a conference call. This proposed solution system will greatly increase the potential of using Bluetooth technology from a wider applicability perspective of conference calls, which is currently only possible over LTE mobiles.

Keywords: conference call, bluetooth, AI, frequency hopping, piconet, scatter net

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Authors: Banan Aljumaiah

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In recent years, the construction industry has leveraged the information revolution, which makes it possible to view the entire construction process of new buildings before they are built with the advent of Building Information Modelling (BIM). Although BIM is an integration of the building model with the data and documents about the building, however, its implementation is limited to individual buildings missing the large picture of the city infrastructure. This limitation of BIM led to the birth of City Information Modelling. Three years ago, Eastern Province Municipality (EPM) in Saudi Arabia mandated that all major projects be delivered with collaborative 3D BIM. After three years of implementation, EPM started to implement City Information Modelling (CIM) as a part of the Smart City Plan to link infrastructure and public services and modelling how people move around and interact with the city. This paper demonstrates a local case study of BIM implementation in EPM and its future as a part of project management automation; the paper also highlights the ambitious plan of EPM to transform CIM towards building smart cities.

Keywords: BIM, BIM to CIM

Procedia PDF Downloads 142

Authors: Silvia Moreno, Banu Iyisan, Hannes Gumz, Brigitte Voit, Dietmar Appelhans

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Polymersomes are materials which are considered as artificial counterparts of natural vesicles. The nanotechnology of such smart nanovesicles is very useful to enhance the efficiency of many therapeutic and diagnostic drugs. Those compounds show a higher stability, flexibility, and mechanical strength to the membrane compared to natural liposomes. In addition, they can be designed in detail, the permeability of the membrane can be controlled by different stimuli, and the surface can be functionalized with different biological molecules to facilitate monitoring and target. For this purpose, this study demonstrates the formation of multifunctional and pH sensitive polymersomes and their functionalization with different reactive groups or biomolecules inside and outside of polymersomes´ membrane providing by crossing the membrane and docking/undocking processes for biomedical applications. Overall, they are highly versatile and thus present new opportunities for the design of targeted and selective recognition systems, for example, in mimicking cell functions and in synthetic biology.

Keywords: multifunctionalized, pH stimulus, controllable release, cellular uptake

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Authors: Ritwik Dutta, Marylin Wolf

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This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver

Procedia PDF Downloads 390

Authors: Jasim Uddin, Rod Smith, Malcolm Gillies

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Surface irrigation is the most popular irrigation method all over the world. However, two issues: low efficiency and huge labour involvement concern irrigators due to scarcity in recent years. To address these issues, a smart automated furrow is conceptualised that can be operated using digital devices like smartphone, iPad or computer and a preliminary evaluation was conducted in this study. The smart automated system is the integration of commercially available software and hardware. It includes real-time surface irrigation optimisation software (SISCO) and Rubicon Water’s surface irrigation automation hardware and software. The automated system consists of automatic water delivery system with 300 mm flexible pipes attached to both sides of a remotely controlled valve to operate the irrigation. A water level sensor to obtain the real-time inflow rate from the measured head in the channel, advance sensors to measure the advance time to particular points of an irrigated field, a solar-powered telemetry system including a base station to communicate all the field sensors with the main server. On the basis of field data, the software (SISCO) is optimised the ongoing irrigation and determine the optimum cut-off for particular irrigation and send this information to the control valve to stop the irrigation in a particular (cut-off) time. The preliminary evaluation shows that the automated surface irrigation worked reasonably well without manual intervention. The evaluation of farmers managed irrigation events show the potentials to save a significant amount of water and labour. A substantial amount of economic and social benefits are expected in rural industries by adopting this system. The future outcome of this work would be a fully tested commercial adaptive real-time furrow irrigation system able to compete with the pressurised alternative of centre pivot or lateral move machines on capital cost, water and labour savings but without the massive energy costs.

Keywords: furrow irrigation, smart automation, infiltration, SISCO, real-time irrigation, adoptive control

Procedia PDF Downloads 451

Authors: Fatemehsadat Mousaviabarbekouh

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Population growth and changing consumption patterns have led to waste management becoming a significant global challenge. With projections indicating that nearly 67% of the Earth's population will live in megacities by 2050, there is a pressing need for smart solutions to address citizens' demands. Waste collection, facilitated by the Internet of Things (IoT), offers an efficient and cost-effective approach. This study aims to review the utilization of IoT for waste collection and explore technologies that promote eco-friendly waste management. The research focuses on information and communication technologies (ICTs), including spatial, identification, acquisition, and data communication technologies. Additionally, the study examines various energy harvesting technologies to further reduce costs. The findings indicate that the application of these technologies can lead to significant cost savings, energy efficiency, and ultimately reshape the future of waste management.

Keywords: waste collection, IoT, smart cities, eco-friendly, information and communication technologies, energy harvesting

Procedia PDF Downloads 111

Authors: Muhammad Umair, Yuri Nikolaev, Denis Artemov, Ighor Uzhinsky

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A flexible manufacturing system is an integral part of a smart factory of industry 4.0 in which every machine is interconnected and works autonomously. Robots are in the process of replacing humans in every industrial sector. As the cyber-physical-system (CPS) and artificial intelligence (AI) are advancing, the manufacturing industry is getting more dependent on computers than human brains. This modernization has boosted the production with high quality and accuracy and shifted from classic production to smart manufacturing systems. However, material handling for such automated productions is a challenge and needs to be addressed with the best possible solution. Conventional clamping systems are designed for manual work and not suitable for highly automated production systems. Researchers and engineers are trying to find the most economical solution for loading/unloading and transportation workpieces from a warehouse to a machine shop for machining operations and back to the warehouse without human involvement. This work aims to propose an advanced multi-shape tooling solution for highly automated manufacturing systems. The currently obtained result shows that it could function well with automated guided vehicles (AGVs) and modern conveyor belts. The proposed solution is following requirements to be automation-friendly, universal for different part geometry and production operations. We used a bottom-up approach in this work, starting with studying different case scenarios and their limitations and finishing with the general solution.

Keywords: artificial intelligence, cyber physics system, Industry 4.0, material handling, smart factory, flexible manufacturing system

Procedia PDF Downloads 132

Authors: Sumaiya Amir Khan, Shayma Al-Sharif, Samiha Mazher, Neha Intikhab Khan

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This research paper aims to evaluate the effectiveness of sleep-tracking AI applications in smart-watches. It focuses on comparing the sleep analyses of two different smartwatch brands, Samsung and Fitbit, and measuring sleep at three different stages – REM (Rapid-Eye-Movement), NREM (Non-Rapid-Eye-Movement), and deep sleep. The methodology involves the participation of different users and analyzing their sleep data. The results reveal that although light sleep is the longest stage, deep sleep is higher than average in the participants. The study also suggests that light sleep is not uniform, and getting higher levels of deep sleep can prevent debilitating health conditions. Based on the findings, it is recommended that individuals should aim to achieve higher levels of deep sleep to maintain good health. Overall, this research contributes to the growing literature on the effectiveness of sleep-tracking AI applications and their potential to improve sleep quality.

Keywords: sleep tracking, lifestyle, accuracy, health, AI, AI features, ML

Procedia PDF Downloads 79

Authors: Justina Jor, Mahmud Pinga

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Climate change has become a significant worldwide environmental challenge with extensive implications, compelling both governments and non-governmental organizations to remain vigilant, as it seemingly impacts various sectors of the global economy, including education. The study investigates the implementation of smart climate change measures for effective primary school management in Benue State, Nigeria. Theorized by the diffusion of innovations, the study was guided by two research questions, and two null hypotheses were formulated and tested. The study used a descriptive survey design. The population comprised 12,364 teachers from 2,721 primary schools, with a sample of 618 teachers from 136 schools selected through a multistage sampling procedure. Smart climate change measures questionnaire (SCCMQ) and key informant interview (KII) were used for data collection. The data collected were analyzed using mean and standard deviation to answer the research questions, while the Chi-square (χ2) test of goodness-of-fit was used to test the hypotheses at a 0.05 level of significance, with qualitative data analyzed using simple percentages, tables, and bar charts. The findings highlight the significant positive impact of green building practices on the efficient administration of primary schools in Benue State, Nigeria. The crucial integration of environmentally sustainable construction methods is emphasized for enhancing overall management in these educational institutions. In addition, the research demonstrates a favorable impact on the adoption of renewable energy solutions and effective school management. The utilization of renewable energy not only aligns with eco-friendly practices but also contributes to the overall operational efficiency and sustainability of primary schools in the region. The study recommends that educational authorities and policymakers prioritize integrating green building practices and renewable energy solutions, pointing towards the prospect of improved governance and functionality for primary education facilities not only in Benue but throughout Nigeria.

Keywords: smart, climate change, effective management, green building, renewable energy

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Authors: Alexander Peikos, Carole Binsfeld

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The aim of this paper is to determine a thermally comfortable air temperature in an automated living room. This calculated temperature should serve as input for a user-specific and dynamic heating control in such a living space. In addition to the usual physical factors (air temperature, humidity, air velocity, and radiation temperature), individual clothing and activity should be taken into account. The calculation of such a temperature is based on different methods and indices which are usually used for the evaluation of the thermal comfort. The thermal insulation of the worn clothing is determined with a Radio Frequency Identification system. The activity performed is only taken into account indirectly through the generated heart rate. All these methods are ultimately very well suited for use in temperature regulation in an automated home, but still require further research and extensive evaluation.

Keywords: smart home, thermal comfort, predicted mean vote, radio frequency identification

Procedia PDF Downloads 159

Authors: Dong Seop Lee, Byung Sik Kim

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In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. These artificial intelligence technologies are applied in various services, including disaster management. Disaster information management does not just support disaster work, but it is also the foundation of smart disaster management. Furthermore, it gets historical disaster information using artificial intelligence technology. Disaster information is one of important elements of entire disaster cycle. Disaster information management refers to the act of managing and processing electronic data about disaster cycle from its’ occurrence to progress, response, and plan. However, information about status control, response, recovery from natural and social disaster events, etc. is mainly managed in the structured and unstructured form of reports. Those exist as handouts or hard-copies of reports. Such unstructured form of data is often lost or destroyed due to inefficient management. It is necessary to manage unstructured data for disaster information. In this paper, the Optical Character Recognition approach is used to convert handout, hard-copies, images or reports, which is printed or generated by scanners, etc. into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored in the disaster database system. Gathering and creating disaster information based on Optical Character Recognition for unstructured data is important element as realm of the smart disaster management. In this paper, Korean characters were improved to over 90% character recognition rate by using upgraded OCR. In the case of character recognition, the recognition rate depends on the fonts, size, and special symbols of character. We improved it through the machine learning algorithm. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle such as historical disaster progress, damages, response, and recovery. The expected effect of this research will be able to apply it to smart disaster management and decision making by combining artificial intelligence technologies and historical big data.

Keywords: disaster information management, unstructured data, optical character recognition, machine learning

Procedia PDF Downloads 129

Authors: S. C. Kattimani

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This article deals with the analysis of active constrained layer damping (ACLD) of smart multiferroic or magneto-electro-elastic doubly curved shells. The kinematics of deformations of the multiferroic doubly curved shell is described by a layer-wise shear deformation theory. A three-dimensional finite element model of multiferroic shells has been developed taking into account the electro-elastic and magneto-elastic couplings. A simple velocity feedback control law is employed to incorporate the active damping. Influence of layer stacking sequence and boundary conditions on the response of the multiferroic doubly curved shell has been studied. In addition, for the different orientation of the fibers of the constraining layer, the performance of the ACLD treatment has been studied.

Keywords: active constrained layer damping (ACLD), doubly curved shells, magneto-electro-elastic, multiferroic composite, smart structures

Procedia PDF Downloads 311

Authors: A. Aslihan Gokaltun, Martin L. Yarmush, Ayse Asatekin, O. Berk Usta

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Poly(dimethylsiloxane) (PDMS) is one of the most widely used materials in the fabrication of microfluidic devices. It is easily patterned and can replicate features down to nanometers. Its flexibility, gas permeability that allows oxygenation, and low cost also drive its wide adoption. However, a major drawback of PDMS is its hydrophobicity and fast hydrophobic recovery after surface hydrophilization. This results in significant non-specific adsorption of proteins as well as small hydrophobic molecules such as therapeutic drugs limiting the utility of PDMS in biomedical microfluidic circuitry. While silicon, glass, and thermoplastics have been used, they come with problems of their own such as rigidity, high cost, and special tooling needs, which limit their use to a smaller user base. Many strategies to alleviate these common problems with PDMS are lack of general practical applicability, or have limited shelf lives in terms of the modifications they achieve. This restricts large scale implementation and adoption by industrial and research communities. Accordingly, we aim to tailor biocompatible PDMS surfaces by developing a simple and one step bulk modification approach with novel smart materials to reduce non-specific molecular adsorption and to stabilize long-term cell analysis with PDMS substrates. Smart polymers that blended with PDMS during device manufacture, spontaneously segregate to surfaces when in contact with aqueous solutions and create a < 1 nm layer that reduces non-specific adsorption of organic and biomolecules. Our methods are fully compatible with existing PDMS device manufacture protocols without any additional processing steps. We have demonstrated that our modified PDMS microfluidic system is effective at blocking the adsorption of proteins while retaining the viability of primary rat hepatocytes and preserving the biocompatibility, oxygen permeability, and transparency of the material. We expect this work will enable the development of fouling-resistant biomedical materials from microfluidics to hospital surfaces and tubing.

Keywords: cell culture, microfluidics, non-specific protein adsorption, PDMS, smart polymers

Procedia PDF Downloads 294

Authors: Prateek Saxena, Sanjeev Singh, Julius Roy

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The security of the power distribution grid remains a paramount to the utility professionals while enhancing and making it more efficient. The most serious threat to the system can be maintaining the transformers, as the load is ever increasing with the addition of elements like electric vehicles. In this paper, intelligent transformer monitoring and grid management has been proposed. The engineering is done to use the evolving data from the smart meter for grid analytics and diagnostics for preventive maintenance. The two-tier architecture for hardware and software integration is coupled to form a robust system for the smart grid. The proposal also presents interoperable meter standards for easy integration. Distribution transformer analytics based on real-time data benefits utilities preventing outages, protects the revenue loss, improves the return on asset and reduces overall maintenance cost by predictive monitoring.

Keywords: electric vehicle charging, transformer monitoring, data analytics, intelligent grid

Procedia PDF Downloads 791

Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: K. N. Dinesh Babu, M. V. Gopalan, G. R. Manjunatha, R. Ramaprabha, V. Rajini

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In this paper, monitoring and control of tap changer mechanism of a transformer implementation in an intelligent electronic device (IED) is discussed. Its been a custom for decades to provide a separate panel for on load tap changer control for monitoring the tap position. However this facility cannot either record or transfer the information to remote control centers. As there is a technology shift towards the smart grid protection and control standards, the need for implementing remote control and monitoring has necessitated the implementation of this feature in numerical relays. This paper deals with the programming, settings and logic implementation which is applicable to both IEC 61850 compatible and non-compatible IEDs thereby eliminating the need for separate tap changer control equipment. The monitoring mechanism has been implemented in a 28MVA, 110 /6.9kV transformer with 16 tap position with GE make T60 IED at Ultratech cement limited Gulbarga, Karnataka and is in successful service.

Keywords: transformer protection, tap changer control, tap position monitoring, on load tap changer, intelligent electronic device (IED)

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Authors: Jayesh M. Patel, Bharat P. Modi

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The availability of on mobile devices that can invoke the demonstrated that the total data demand from users is far higher than previously articulated by measurements based solely on a cellular-centric view of smart-phone usage. The ratio of Wi-Fi to cellular traffic varies significantly between countries, This paper is shown the compression between the cellular data usage and Wi-Fi data usage by the user. This strategy helps operators to understand the growing importance and application of yield management strategies designed to squeeze maximum returns from their investments into the networks and devices that enable the mobile data ecosystem. The transition from unlimited data plans towards tiered pricing and, in the future, towards more value-centric pricing offers significant revenue upside potential for mobile operators, but, without a complete insight into all aspects of smartphone customer behavior, operators will unlikely be able to capture the maximum return from this billion-dollar market opportunity.

Keywords: cellular, Wi-Fi, mobile, smart phone

Procedia PDF Downloads 365

Authors: Amara Prakasa Rao, N. V. S. N. Sarma

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This paper describes the synthesis of linear array geometry with minimum sidelobe level and null control using the Taguchi method. Based on the concept of the orthogonal array, Taguchi method effectively reduces the number of tests required in an optimization process. Taguchi method has been successfully applied in many fields such as mechanical, chemical engineering, power electronics, etc. Compared to other evolutionary methods such as genetic algorithms, simulated annealing and particle swarm optimization, the Taguchi method is much easier to understand and implement. It requires less computational/iteration processing to optimize the problem. Different cases are considered to illustrate the performance of this technique. Simulation results show that this method outperforms the other evolution algorithms (like GA, PSO) for smart antenna systems design.

Keywords: array factor, beamforming, null placement, optimization method, orthogonal array, Taguchi method, smart antenna system

Procedia PDF Downloads 394

Authors: Salah Aguib, Noureddine Chikh, Abdelmalek Khabli, Abdelkader Nour, Toufik Djedid, Lallia Kobzili

Abstract:

This study presents the behavior of a hybrid smart sandwich plate with a magnetorheological elastomer core. In order to improve the vibrational behavior of the plate, the pseudo‐fibers formed by the effect of the magnetic field on the elastomer charged by the ferromagnetic particles are oriented at 45° with respect to the direction of the magnetic field at 0°. Ritz's approach is taken to solve the physical problem. In order to verify and compare the results obtained by the Ritz approach, an analysis using the finite element method was carried out. The rheological property of the MRE material at 0° and at 45° are determined experimentally, The studied elastomer is prepared by a mixture of silicone oil, RTV141A polymer, and 30% of iron particles of total mixture, the mixture obtained is mixed for about 15 minutes to obtain an elastomer paste with good homogenization. In order to develop a magnetorheological elastomer (MRE), this paste is injected into an aluminum mold and subjected to a magnetic field. In our work, we have chosen an ideal percentage of filling of 30%, to obtain the best characteristics of the MRE. The mechanical characteristics obtained by dynamic mechanical viscoanalyzer (DMA) are used in the two numerical approaches. The natural frequencies and the modal damping of the sandwich plate are calculated and discussed for various magnetic field intensities. The results obtained by the two methods are compared. These off‐axis anisotropic MRE structures could open up new opportunities in various fields of aeronautics, aerospace, mechanical engineering and civil engineering.

Keywords: hybrid smart sandwich plate, vibratory behavior, FEM, Ritz approach, MRE

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Authors: Keunho Park, Sunghwan Jeong

Abstract:

The 4th Industrial Revolution, the next-generation industrial revolution, which is made up of convergence of information and communication technology (ICT), is no exception to the livestock industry, and various studies are being conducted to apply the livestock smart farm. In order to monitor livestock using sensors, it is necessary to drill holes in the organs such as the nose, ears, and even the stomach of the livestock to wear or insert the sensor into the livestock. This increases the stress of livestock, which in turn lowers the quality of livestock products or raises the issue of animal ethics, which has become a major issue in recent years. In this paper, we conducted a study to monitor livestock activity based on vision technology, effectively monitoring livestock activity without increasing animal stress and violating animal ethics. The movement rate was calculated based on the difference images between the frames, and the livestock activity was evaluated. As a result, the average F1-score was 96.67.

Keywords: barn monitoring, livestock, machine vision, smart farm

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Authors: Ahsan Ali, Mayank Ostwal, Nikhil Agarwal

Abstract:

Abstract—According to a World Bank report, millions of people across the globe still do not have access to improved water services. With uninterrupted growth of cities and urban inhabitants, there is a mounting need to safeguard the sustainable expansion of cities. Efficient functioning of the urban components and high living standards of the residents are needed to be ensured. The water and sanitation network of an urban development is one of its most essential parts of its critical infrastructure. The growth in urban population is leading towards increased water demand, and thus, the local water resources are severely strained. 'Smart water' is referred to water and waste water infrastructure that is able to manage the limited resources and the energy used to transport it. It enables the sustainable consumption of water resources through co-ordinate water management system, by integrating Information Communication Technology (ICT) solutions, intended at maximizing the socioeconomic benefits without compromising the environmental values. This paper presents a case study from a medium sized city in North-western Pakistan. Currently, water is getting contaminated due to the proximity between water and sewer pipelines in the study area, leading to public health issues. Due to unsafe grey water infiltration, the scarce ground water is also getting polluted. This research takes into account the design of smart urban water network by integrating ICT (Information and Communication Technology) with urban water network. The proximity between the existing water supply network and sewage network is analyzed and a design of new water supply system is proposed. Real time mapping of the existing urban utility networks will be projected with the help of GIS applications. The issue of grey water infiltration is addressed by providing sustainable solutions with the help of locally available materials, keeping in mind the economic condition of the area. To deal with the current growth of urban population, it is vital to develop new water resources. Hence, distinctive and cost effective procedures to harness rain water would be suggested as a part of the research study experiment.

Keywords: GIS, smart water, sustainability, urban water management

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Authors: Shuqi Zhang

Abstract:

Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%.

Keywords: federated learning, secure aggregation, backdoor attack, cluster analysis, neuron pruning

Procedia PDF Downloads 96