scholarly journals Big Data an Interesting Tool for Policing and Law Enforcement to Ensure the Safety, Health, Possessions of Citizens, and To Prevent Crime and Civil Disorder

2020 ◽  
Vol 9 (11) ◽  
pp. 225-228
Keyword(s):  
Big Data ◽  
Law Enforcement ◽  
Small Contribution ◽  
Global Pandemic ◽  
Data Application ◽  
The World ◽  
Civil Disorder ◽  
Big Data Application ◽  
Physical Asset ◽  
Predictive Software

This research paper portrays a small contribution towards the exploration of big data application; particularly in the policing and legal departments around the world. It showcases the concept of real time study of ever growing, constant and large amount of data being put into use and showcasing how this data in the coming world is not less than any physical asset. This paper provides a good understanding about the implementation of big data and how out of multiple sectors it is being utilized in the policing and law enforcement sectors of numerous countries with the help of technical advancements like Artificial Intelligence and Predictive Software. An understanding in the working of Predictive Analysis Softwares & AI with the policing bodies that already are into existence and running. This includes system-oriented reproductions for producing road segment-based lawbreaking forecasts. The big data proved to be very useful for the policing and law enforcement sectors during the global pandemic caused by the COVID-19 virus when social distancing is critical.

scholarly journals The Application of “Big Data Analysis + Hierarchical Medical” Model in the Context of the COVID-19

2021 ◽  
Vol 292 ◽  
pp. 02014
Author(s):  
Xingyu Yang ◽  
Tianyu Yan ◽  
Zelong Huang ◽  
Xiaofang Zhang ◽  
Yuchen Zhao ◽  
...  
Keyword(s):  
Public Health ◽  
Big Data ◽  
Data Analysis ◽  
Medical Model ◽  
Big Data Analysis ◽  
Public Health Emergencies ◽  
Data Application ◽  
The World ◽  
Big Data Application ◽  
Hierarchical Medical System

The COVID-19 epidemic has swept the world, causing serious impact and influence on economic development and residents' life in countries all over the world. This paper takes China as an example, further analyses the characteristics of China's hierarchical medical model based on the international hierarchical medical research planning, and proposes the application of “big data analysis + hierarchical medical” model for the new coronavirus epidemic and other public health emergencies based on the advantages of big data application to solve public health crises, in order to provide a reference for the planning of hierarchical medical system during the epidemic. It is expected to provide reference for the planning of hierarchical medical and health system during the epidemic, which is an innovative attempt of the medical industry.

scholarly journals Perspectives on a Big Data Application: What Database Engineers and IT Students Need to Know

2015 ◽  
Vol 5 (5) ◽  
pp. 850-853 ◽  
Author(s):  
E. Erturk ◽  
K. Jyoti
Keyword(s):  
Big Data ◽  
Computer Engineering ◽  
It Professionals ◽  
Academic Literature ◽  
Current Trends ◽  
Data Application ◽  
The World ◽  
Big Data Application ◽  
Institute Of Technology ◽  
Eastern Institute

Cloud Computing and Big Data are important and related current trends in the world of information technology. They will have significant impact on the curricula of computer engineering and information systems at universities and higher education institutions. Learning about big data is useful for both working database professionals and students, in accordance with the increase in jobs requiring these skills. It is also important to address a broad gamut of database engineering skills, i.e. database design, installation, and operation. Therefore the authors have investigated MongoDB, a popular application, both from the perspective of industry retraining for database specialists and for teaching. This paper demonstrates some practical activities that can be done by students at the Eastern Institute of Technology New Zealand. In addition to testing and preparing new content for future students, this paper contributes to the very recent and emerging academic literature in this area. This paper concludes with general recommendations for IT educators, database engineers, and other IT professionals.

scholarly journals Big Data Analytic Framework for Organizational Leverage

2021 ◽  
Vol 11 (5) ◽  
pp. 2340
Author(s):  
Sanjay Mathrani ◽  
Xusheng Lai
Keyword(s):  
Big Data ◽  
Web Sites ◽  
Big Data Analytics ◽  
Building Blocks ◽  
Application Service ◽  
Data Application ◽  
Other Information ◽  
Big Data Application ◽  
Diverse Data ◽  
Framework System

Web data have grown exponentially to reach zettabyte scales. Mountains of data come from several online applications, such as e-commerce, social media, web and sensor-based devices, business web sites, and other information types posted by users. Big data analytics (BDA) can help to derive new insights from this huge and fast-growing data source. The core advantage of BDA technology is in its ability to mine these data and provide information on underlying trends. BDA, however, faces innate difficulty in optimizing the process and capabilities that require merging of diverse data assets to generate viable information. This paper explores the BDA process and capabilities in leveraging data via three case studies who are prime users of BDA tools. Findings emphasize four key components of the BDA process framework: system coordination, data sourcing, big data application service, and end users. Further building blocks are data security, privacy, and management that represent services for providing functionality to the four components of the BDA process across information and technology value chains.

Preliminary Benefits of Big Data in the Construction Industry: A Case Study

2022 ◽  
pp. 1-11
Author(s):  
Bernard Tuffour Atuahene ◽  
Sittimont Kanjanabootra ◽  
Thayaparan Gajendran
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Construction Projects ◽  
Big Data Applications ◽  
Data Application ◽  
Construction Firm ◽  
Big Data Application ◽  
Tangible Benefit ◽  
Design Construction

Big data applications consist of i) data collection using big data sources, ii) storing and processing the data, and iii) analysing data to gain insights for creating organisational benefit. The influx of digital technologies and digitization in the construction process includes big data as one newly emerging digital technology adopted in the construction industry. Big data application is in a nascent stage in construction, and there is a need to understand the tangible benefit(s) that big data can offer the construction industry. This study explores the benefits of big data in the construction industry. Using a qualitative case study design, construction professionals in an Australian Construction firm were interviewed. The research highlights that the benefits of big data include reduction of litigation amongst projects stakeholders, enablement of near to real-time communication, and facilitation of effective subcontractor selection. By implication, on a broader scale, these benefits can improve contract management, procurement, and management of construction projects. This study contributes to an ongoing discourse on big data application, and more generally, digitization in the construction industry.

scholarly journals Federated Learning in Big Data Application and Sharing

2020 ◽  
Author(s):  
Jing Yang ◽  
Quan Zhang ◽  
Kunpeng Liu ◽  
Peng Jin ◽  
Guoyi Zhao
Keyword(s):  
Big Data ◽  
Data Privacy ◽  
The State ◽  
Ideal Model ◽  
Local Data ◽  
Data Safety ◽  
Big Data Applications ◽  
Data Application ◽  
Big Data Application ◽  
Uniform Model

In recent years, electricity big data has extensive applications in the grid companies across the provinces. However, certain problems are encountered including, the inability to generate an ideal model using the isolated data possessed by each company, and the priority concerns for data privacy and safety during big data application and sharing. In this pursuit, the present research envisaged the application of federated learning to protect the local data, and to build a uniform model for different companies affiliated to the State Grid. Federated learning can serve as an essential means for realizing the grid-wide promotion of the achievements of big data applications, while ensuring the data safety.

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