Wyniki wyszukiwania - BazTech

1

Enhancing traffic safety: a comprehensive approach through real-time data and intelligent transportation systems

Le Khanh Giang

Zeszyty Naukowe. Transport / Politechnika Śląska

|

2024

|

z. 122

129--149

EN

Today, traffic accidents are still a difficult and urgent problem for many countries around the world. Traffic accidents on highways are often more serious than accidents on urban roads. Therefore, disseminating emergency information and creating immediate connections with road users is key to rescuing passengers and reducing congestion. Thus, this study applies data fusion and data mining techniques to analyze travel time and valuable information about traffic accidents based on the real-time data collected from On-Board Unit installed in vehicles. The results show that this important information is the vital database to analyze traffic conditions and safety factors, thereby developing a smart traffic information platform. This result enables traffic managers to provide real-time traffic information or forecasts of congestion and traffic accidents to road users. This helps limit congestion and serious accidents on the Highway.

2

A study of big data in cloud computing

Khan Imran

Computer Assisted Methods in Engineering and Science

|

2024

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Vol. 31, no. 3

313--349

EN

Over the last two decades, the size and amount of data has increased enormously, whichhas changed traditional methods of data management and introduced two new technolog-ical terms: big data and cloud computing. Addressing big data, characterized by massivevolume, high velocity and variety, is quite challenging as it requires large computationalinfrastructure to store, process and analyze it. A reliable technique to carry out sophisti-cated and enormous data processing has emerged in the form of cloud computing becauseit eliminates the need to manage advanced hardware and software, and offers various ser-vices to users. Presently, big data and cloud computing are gaining significant interestamong academia as well as in industrial research. In this review, we introduce variouscharacteristics, applications and challenges of big data and cloud computing. We providea brief overview of different platforms that are available to handle big data, including theircritical analysis based on different parameters. We also discuss the correlation betweenbig data and cloud computing. We focus on the life cycle of big data and its vital analysisapplications in various fields and domains At the end, we present the open research issuesthat still need to be addressed and give some pointers to future scholars in the fields ofbig data and cloud computing.

3

Secure Big Data Model Based on Blockchain Technology

Alshammari Ahmad

Advances in Science and Technology. Research Journal

|

2024

|

Vol. 18, no 4

163--176

EN

Blockchain has been growing rapidly in the cryptocurrency age and is one of the best information technologies that provide security and privacy to the data of people in crypto economy. In most cases, tampering with data and problems regarding data authentication tend to occur when data is shared and stored on centralized servers. With the assistance of blockchain technology, big data can be managed and saved in the cloud, and the technologies that enhance security by keeping out pernicious users could be used. Therefore, this paper has two aims: to discover the advantages and disadvantages of existing security big data models and to develop a conceptual secure big data model based on blockchain technology. The design science method is used for the purposes of this study. The developed conceptual secure big data model consists of three main processes: dataset storage and encryption, verification and consensus, and access control mechanism. The finding of this study discovered that the developed conceptual secure big data model offers a mix of both traditional and modern security measures which helps domain practitioners understand the security concepts of the blockchain along with big data as well.

4

Metrologia przyszłości. Czy powinniśmy się bać?

Wieczorowski Michał

Stal, Metale & Nowe Technologie

|

2023

|

nr 3-4

8--16

PL

Jakie zmiany czekają metrologię w najbliższym czasie? Czy dynamiczny postęp technologiczny sprawi, że pojawią się zupełnie nowe możliwości w tej dziedzinie?

5

The possibilities of visualisation multidimensional databases in interactive visual communication

Rybak Łukasz, Bednarski Radosław

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

|

2023

|

nr 5

22--27

EN

In the article, we describe the possibilities of presenting multidimensional data warehouses in interactive two dimensional visualizations. We show how to avoid the information overload problem. This is a complex and difficult issue because each set describes different data. Therefore, there are no universal methods that can be transferred between visualizations of different databases. In this article, we analyze the graphical resources of available two-dimensional data visualizations. We describe the possibilities of their binding to specific types of data. In addition, we present their use for a specific data set described by thirteen features. In order to check the correctness of our analysis, we conduct scenario tests of usability.

PL

W artykule opisujemy możliwości prezentacji wielowymiarowych hurtowni danych w interaktywnych wizualizacjach dwuwymiarowych. Pokazujemy, jak uniknąć problemu redundancji informacji. Jest to zagadnienie złożone i trudne, gdyż każdy zbiór opisuje inne dane. Dlatego nie ma uniwersalnych metod, które można przenosić pomiędzy wizualizacjami różnych baz danych. W artykule analizujemy zasoby graficzne dostępnych dwuwymiarowych wizualizacji danych. Opisujemy możliwości ich powiązania z określonymi typami danych. Dodatkowo prezentujemy ich zastosowanie dla konkretnego zbioru danych opisanego przez trzynaście cech. W celu sprawdzenia poprawności naszej analizy przeprowadzamy scenariuszowe testy użyteczności.

6

Methodology for creating dynamic emergency vehicle availability maps

Lupa Michał, Naziemiec Weronika, Adamek Katarzyna, Zawadzki Mateusz

Polish Cartographical Review

|

2023

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Vol. 55, No. 1

24--37

EN

One of the main priorities of emergency services is to minimize the response time to calls. In the process of proper allocation of emergency vehicles, maps of emergency vehicle accessibility are found to be helpful. These maps represent areas within which emergency services can reach the specified location within a certain time. Calculating travel times requires taking into account the rapidly changing current road conditions. This paper presents a method for dynamically generating maps of emergency vehicle accessibility, considering network models and irregular computational grids.

7

Poznański producent rowerów optymalizuje dostawy ostatniej mili

Ciesielski Marcin

Logistyka

|

2023

|

nr 5

38--43

PL

Hazay Bikes buduje kompletny produkt do optymalizacji logistyki miejskiej: elektryczny rower towarowy wraz z rozwiązaniami software'owymi.

8

Artificial intelligence in the smart city — a literature review

Szpilko Danuta, Naharro Felix Jimenez, Lăzăroiu George, Nica Elvira, Gallegos Antonio de la Torre

Engineering Management in Production and Services

|

2023

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Vol. 15, no. 4

53--75

EN

The influence of artificial intelligence (AI) in smart cities has resulted in enhanced efficiency, accessibility, and improved quality of life. However, this integration has brought forth new challenges, particularly concerning data security and privacy due to the widespread use of Internet of Things (IoT) technologies. The article aims to provide a classification of scientific research relating to artificial intelligence in smart city issues and to identify emerging directions of future research. A systematic literature review based on bibliometric analysis of Scopus and Web of Science databases was conducted for the study. Research query included TITLE-ABS-KEY (“smart city” AND “artificial intelligence”) in the case of Scopus and TS = (“smart city” AND “artificial intelligence”) in the case of the Web of Sciences database. For the purpose of the analysis, 3101 publication records were qualified. Based on bibliometric analysis, seven research areas were identified: safety, living, energy, mobility, health, pollution, and industry. Urban mobility has seen significant innovations through AI applications, such as autonomous vehicles (AVs), electric vehicles (EVs), and unmanned aerial vehicles (UAVs), yet security concerns persist, necessitating further research in this area. AI’s impact extends to energy management and sustainability practices, demanding standardised regulations to guide future research in renewable energy adoption and developing integrated local energy systems. Additionally, AI’s applications in health, environmental management, and the industrial sector require further investigation to address data handling, privacy, security, and societal implications, ensuring responsible and sustainable digitisation in smart cities.

9

Metodyka pozyskiwania danych big data z telefonii komórkowej i możliwości ich wykorzystania w modelowaniu podróży

Birr Krystian

Transport Miejski i Regionalny

|

2022

|

nr 5

10--17

PL

Celem niniejszego artykułu jest przedstawienie przykładowych możliwych źródeł danych o wielkim wolumenie (Big Data) ze szczególnym uwzględnieniem metody pozyskania danych z telefonii komórkowej – kart SIM oraz potencjału ich wykorzystania w modelowaniu podróży na poziomie makroskopowym. Na podstawie doświadczeń zdobytych podczas zakupu danych typu big data od kilku dostawców dla jednostek samorządowych w województwie pomorskim opisano najważniejsze zagadnienia metodyczne związane problematyką pozyskania i weryfikacji danych Big Data o rozmieszczeniu i przemieszczeniach ludności.

EN

The objective of this article is to present examples of possible data sources of great volume (Big Data) with particular emphasis on methods of obtaining data from mobile networks (SIM cards) and potential for its application in travel modelling on a macroscopic level. Based on experience gained during purchasing Big Data from several providers for regional government units in the Pomeranian voivodeship, the most essential methodical issues of data collecting and verification about population location and trips were described.

10

Cognitive technologies in smart city services as the future in strategic management of cities

Giela Małgorzata

Management Systems in Production Engineering

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2022

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nr 3 (30)

276--281

EN

The purpose of this paper is to indicate the possibility of applying cognitive technologies in smart city services and analyze their impact on strategic management in the city. The subject of this study is the use of cognitive technologies in big data as one of the tools of smart city. The study also identifies the risks that may occur when using modern technologies at the local level. At the same time, it refers to features that can provide a form of safeguards for an individual's rights and freedoms. This article also covers legal issues that affect the use of cognitive technologies in local government units. This paper indicates that the challenge that local governments should now meet is to build a Smart Sustainable City. Implementation of modern solutions should strive to improve the lives of all residents and thus prevent the exclusion of social groups or individuals.

11

A distributed big data analytics model for traffic accidents classification and recognition based on SparkMlLib cores

Mallahi Imad El, Riffi Jamal, Tairi Hamid, Ez-Zahout Abderrahmane, Mahraz Mohamed Adnane

Journal of Automation Mobile Robotics and Intelligent Systems

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2022

|

Vol. 16, No. 4

62--71

EN

This paper focuses on the issue of big data analytics for traffic accident prediction based on SparkMllib cores; however, Spark’s Machine Learning Pipelines provide a helpful and suitable API that helps to create and tune classification and prediction models to decision-making concerning traffic accidents. Data scientists have recently focused on classification and prediction techniques for traffic accidents; data analytics techniques for feature extraction have also continued to evolve. Analysis of a huge volume of received data requires considerable processing time. Practically, the implementation of such processes in real-time systems requires a high computation speed. Processing speed plays an important role in traffic accident recognition in real-time systems. It requires the use of modern technologies and fast algorithms that increase the acceleration in extracting the feature parameters from traffic accidents. Problems with overclocking during the digital processing of traffic accidents have yet to be completely resolved. Our proposed model is based on advanced processing by the Spark MlLib core. We call on the real-time data streaming API on spark to continuously gather real-time data from multiple external data sources in the form of data streams. Secondly, the data streams are treated as unbound tables. After this, we call the random forest algorithm continuously to extract the feature parameters from a traffic accident. The use of this proposed method makes it possible to increase the speed factor on processors. Experiment results showed that the proposed method successfully extracts the accident features and achieves a seamless classification performance compared to other conventional traffic accident recognition algorithms. Finally, we share all detected accidents with details onto online applications with other users.

12

Integration of Remote Sensing Data in a Cloud Computing Environment

Sabri Yassine, Bahja Fadoua, Pet Henk

International Journal of Electronics and Telecommunications

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2022

|

Vol. 68, No. 1

167--172

EN

With the rapid development of remote sensing technology, our ability to obtain remote sensing data has been improved to an unprecedented level. We have entered an era of big data. Remote sensing data clear showing the characteristics of Big Data such as hyper spectral, high spatial resolution, and high time resolution, thus, resulting in a significant increase in the volume, variety, velocity and veracity of data. This paper proposes a feature supporting, salable, and efficient data cube for time-series analysis application, and used the spatial feature data and remote sensing data for comparative study of the water cover and vegetation change. In this system, the feature data cube building and distributed executor engine are critical in supporting large spatiotemporal RS data analysis with spatial features. The feature translation ensures that the geographic object can be combined with satellite data to build a feature data cube for analysis. Constructing a distributed executed engine based on dask ensures the efficient analysis of large-scale RS data. This work could provide a convenient and efficient multidimensional data services for many remote sensing applications.

13

Small Farms as “Data Producers” for the Needs of Agricultural Management Information System

Zysk Elżbieta, Mroczkowski Tomasz, Dawidowicz Agnieszka

Geomatics and Environmental Engineering

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2022

|

Vol. 16, no. 3

79--109

EN

In the face of current global threats, including the COVID-19 Pandemic, new technological solutions are needed. Globalization, progressing urbanization, the decreasing availability of cultivable land for food production, water contamination, flood risk and climate change, can all be viewed as potential threats to food safety. According to forecasts and trends, the future of both agricultural policy and agricultural innovation will be based on big data, data analytics and machine learning. Therefore, it is and will continue to be important to develop information systems dedicated to agricultural innovation and the management of food security challenges. The main aim of the study is a classification of data for a uniform AMIS from data from IREIS, GC and AIIS based on survey and expert interview data obtained. We propose to expand the range of data produced by small farmers while keeping in mind the protection of farmers and their rights and the possible benefits of the data provided. The literature recognizes the value of such data but it has not yet been legally regulated, protected, managed and, above all, properly used for agricultural and food security policy purposes. Therefore, we develop the idea of extended farmers’ participation in the production of agricultural activity data. The research used a survey questionnaire and expert interviews. A viable AIIS needs current data that farmers already produce as well as additional data needs which we identify in our research. We propose an architecture of databases and describe their flow in the Agriculture Management Information System (AMIS).

14

Od ambitnego pomysłu do realizacji

Wietecha Martyna, Sławik Łukasz, Kopeć Dominik, Gadawska Alicja

Geodeta : magazyn geoinformacyjny

|

2022

|

nr 1

26--29

15

Monitorology – the Art of Observing the World

Malek Miroslaw

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

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2021

|

Vol. 25, No 2

131--139

EN

We focus on the art of observing the world by electronic devices such as sensors and meters that, in general, we call monitors. We also define main monitoring objectives and pose five challenges for effective and efficient monitoring that still need a lot of research. In the era where compute power like electricity is easily available and easy to use across the globe, and big data is generated in enormous amounts at ever-increasing rates, the question, what to monitor and how, will become ever more relevant to save the world from flood of meaningless, dumb data, leading frequently to false conclusions and wrong decisions whose impact may range from a minor inconvenience to loss of lives and major disasters.

16

Big Data i Data Mining w polskim budownictwie

Gajzler Marcin

Przegląd Budowlany

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2021

|

R. 92, nr 7-8

150--153

PL

W artykule podjęto dyskusję nad występowaniem w polskim sektorze budownictwa bardzo dużych zasobów danych, określanych jako Big Data. W innych sektorach, np. finansowym czy usług, obserwuje się dostępność dużych baz danych i ich wykorzystanie w celu poprawy jakości usług, lepszego dostosowania się do wymagań klienta czy poprawy konkurencyjności na rynku. Sektor budowlany, a przede wszystkim jego produkt na tle innych dziedzin gospodarki cechuje specyfika. Czy jej występowanie powoduje brak zasobów Big Data? Artykuł wskazuje na występowanie zasobów Big Data w polskim budownictwie, możliwości i sposoby ich wykorzystania.

EN

The article discusses the work in Polish for the construction of very large data resources, referred to as Big Data. In other sectors, e.g. financial or services, the availability of the database market and their use to improve the quality of services is observed, a test version for customer testing or improvement of market competitiveness. The construction sector, and above all its product, is specific compared to other sectors of the economy. Does its occurrence result in a lack of Big Data resources? An article on the occurrence of Big Data resources in Polish construction, possibilities and ways of using them.

17

An approach to managing innovation to protect financial sector against cybercrime

Kuzmenko Olha, Kubálek Jan, Bozhenko Victoria, Kushneryov Olexandr, Vida Imre

Polish Journal of Management Studies

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2021

|

Vol. 24, No. 2

276--291

EN

Ensuring the cyber security management is an ever-increasing challenge for the financial institutions and the national financial regulators. The main purpose of the research is to improve cyber security management through analyzing large data volumes of information which helps to identify potential cyber threats at an early stage. The factors of the rapid cybercrime growth via supervised learning models with associated learning (SVM) were identified and evaluated in the paper. The object of research is 21 EU countries. The paper presents the results of an empirical analysis, which showed that the cyber threats are caused by the growth of using online banking (0.49), improvement of internet user skills (0.42), expansion of activities online (0.41). The results of the research can be useful for financial institutions, national regulators and cybersecurity professionals.

PL

Zapewnienie zarządzania cyberbezpieczeństwem jest coraz większym wyzwaniem dla instytucji finansowych i krajowych organów nadzoru finansowego. Głównym celem badania jest usprawnienie zarządzania cyberbezpieczeństwem poprzez analizę dużych wolumenów danych informacji, co pomaga zidentyfikować potencjalne zagrożenia cybernetyczne na wczesnym etapie. W artykule zidentyfikowano i oceniono czynniki szybkiego wzrostu cyberprzestępczości poprzez nadzorowane modele uczenia się z powiązanym uczeniem (SVM). Przedmiotem badań jest 21 krajów UE. W artykule przedstawiono wyniki analizy empirycznej, która wykazała, że cyberzagrożenia spowodowane są wzrostem korzystania z bankowości internetowej (0,49), poprawą umiejętności internautów (0,42), ekspansją aktywności w sieci (0,41). Wyniki badania mogą być przydatne dla instytucji finansowych, krajowych regulatorów i specjalistów ds. cyberbezpieczeństwa.

18

Understanding the Impact of COVID–19 on Global Financial Network Using Graph Based Algorithm: Minimum Spanning Tree Approach

Hatipoğlu Veysel Fuat

Foundations of Computing and Decision Sciences

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2021

|

Vol. 46, No. 1

111--123

EN

In this paper effects of COVID–19 pandemic on stock market network are analyzed by an application of operational research with a mathematical approach. For this purpose two minimum spanning trees for each time period namely before and during COVID–19 pandemic are constructed. Dynamic time warping algorithm is used to measure the similarity between each time series of the investigated stock markets. Then, clusters of investigated stock markets are constructed. Numerical values of the topology evaluation for each cluster and time period is computed.

19

Prediction of Garment Production Cycle Time Based on a Neural Network

Cao Huaqing, Ji Xiaofen

Fibres & Textiles in Eastern Europe

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2021

|

Vol. 29, no. 1 (145)

8--12

EN

The process of garment production has always been a black box. The production time of different clothing is different and has great changes, thus managers cannot make a production plan accurately. With the world entering the era of industry 4.0 and the accumulation of big data, machine learning can provide services for the garment manufacturing industry. The production cycle time is the key to control the production process. In order to predict the production cycle time more accurately and master the production process in the garment manufacturing process, a neural network model of production cycle time prediction is established in this paper. Using a trained neural network to predict the production cycle time, the overall error of 6 groups is within 5%, and that of 3 groups is between 5% and 10%. Therefore, this neural network can be used to predict the future production cycle time and predict the overall production time of clothing.

PL

Czas produkcji różnych ubrań jest inny i podlega dużym zmianom, dlatego menedżerowie nie mogą dokładnie zaplanować produkcji. Wraz z wkroczeniem świata w erę przemysłu 4.0 i gromadzeniem dużych zbiorów danych dobrym rozwiązaniem dla przemysłu odzieżowego jest zastosowanie maszyn uczących się. Czas cyklu produkcyjnego jest kluczem do kontroli procesu produkcyjnego. W celu dokładniejszego przewidywania czasu cyklu produkcyjnego i opanowania procesu produkcyjnego w procesie produkcji odzieży, w artykule opracowano model sieci neuronowej do przewidywania czasu cyklu produkcyjnego. Do przewidywania czasu cyklu produkcyjnego użyto sieci neuronowej, ogólny błąd 6 grup mieścił się w granicach 5%, a 3 grup – między 5% a 10%. W związku z tym zaprezentowana sieć neuronowa może znaleźć zastosowanie w przewidywaniu czasu cyklu produkcyjnego i całkowitego czasu produkcji odzieży.

20

Formal verification of extension of istar to support big data projects

Djeddi Chabane, Zarour Nacer Eddine, Charrel Pierre-Jean

Computer Science

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2021

|

T. 22 (3)

321–344

EN

Identifying all of the correct requirements of any system is fundamental for its success. These requirements need to be engineered with precision in the early phases. Principally, late correction costs are estimated to be more than 200 times greater than the cost of corrections during requirements engineering (RE), especially in the big data area due to its importance and characteristics. A deep analysis of the big data literature suggests that current RE methods do not support the elicitation of big data project requirements. In this research, we present BiStar (an extension of iStar) to undertake big data characteris tics such as volume, variety, etc. As a first step, some missing concepts are identified that are not supported by the current methods of RE. Next, BiStar is presented to take big data-specific characteristics into account while dealing with the requirements. To ensure the integrity property of BiStar, formal proofs are made by performing a Bigraph-based description on iStar and BiStar. Fi nally, iStar and BiStar are applied on the same exemplary scenario. BiStar shows promising results, so it is more efficient for eliciting big data project requirements.