scholarly journals Use of Big Data to Improve Environmental Sustainability in Developing Countries

2017 ◽  
Vol 12 (11) ◽  
pp. 249 ◽  
Author(s):  
Maged Adel Abdo Mukred ◽  
Zheng Jianguo
Keyword(s):  
Big Data ◽  
Multinational Corporations ◽  
Environmental Sustainability ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Government Sector ◽  
Wide Range ◽  
Private And Public ◽  
The Government ◽  
Set Up

Big data inhibits the ability to significantly impact a wide range of fields in an economy, from the government sector to commercial sectors like retail and healthcare. Not only has it altered the way companies assess their product’s demand and supply patterns but has also phenomenally helped in making the environment healthier in recent years. It carries the ability to identify valuable data from a huge dataset with exceptional parallel processing. This study presents the general introduction of big data bringing forth its various features and advantages along with the challenges which organizations face while using with respect to environmental sustainability. Observations have also been made on the findings of various researches, and studies and surveys performed by some international organizations in the recent years on the urgent need of taking necessary measures and initiatives to prevent further depletion of natural resources thus making the environment sustainable. Making the issue the study aim, future studies must intend to explore how multinational corporations can enhance environmental sustainability through big data analytics. Lastly, recommendations have been made to organisations– private and public in hiring adequate expertise and set-up, thereby making big data analytics more efficient and reliable.

RELATIONSHIP IN IOT AND BIG DATA ANALYTICS: THE OPPORTUNITIES AND OPEN CHALLENGES

2021 ◽  
Vol 83 (4) ◽  
pp. 100-111
Author(s):  
Ahmad Anwar Zainuddin ◽  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Physical World ◽  
Future Directions ◽  
Wide Range ◽  
Time Utilization ◽  
Relationship Of ◽  
The Internet Of Things

Internet of Things (IoT) is an up-and-coming technology that has a wide variety of applications. It empowers physical objects to be organized in a specialized framework to grow its convenience in terms of ease and time utilization. It is to convert the thought of bridging the crevice between the physical world and the machine world. It is also being use in the wide range of the technology in this current situation. One of its applications is to monitor and store data over time from numerous devices allows for easy analysis of the dataset. This analysis can then be the basis of decisions made on the same. In this study, the concept, architecture, and relationship of IoT and Big Data are described. Next, several use cases in IoT and big data in the research methodology are studied. The opportunities and open challenges which including the future directions are described. Furthermore, by proposing a new architecture for big data analytics in the Internet of Things, this paper adds value. Overall, the various types of big IoT data analytics, their methods, and associated big data mining technologies are discussed.

Biodiesel Renewable Energy and Transportation Consumption

2021 ◽  
Vol 12 (1) ◽  
pp. 77-77
Author(s):  
Suppanunta Romprasert ◽  
Korakot Kataboonyaruk ◽  
Natthacha Tangnititham ◽  
Tanyaluk Suwanthaijaroen ◽  
Maytavee Soonthornwattanachai ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Environmental Sustainability ◽  
Swot Analysis ◽  
Development Theory ◽  
Pm 2.5 ◽  
Quality Practices ◽  
Current Consumption ◽  
Wide Range ◽  
The Government ◽  
Set Up

Paper focuses on the renewable energy in Thailand. Objective is to compare risk on renewable energy and transportation consumption on biodiesel. It is using SWOT analysis and sustainable development theory as the tools. Besides, collecting data via questionnaire to investigate behaviors of people in having the ideas relating to biodiesel. The 52 responses from survey launching have returned. According to the results, the current consumption of biodiesel is still low because insufficient is on awareness of the consumers' trusts about biodiesel. Moreover, government's policy is not in good quality control. Biodiesel price has not been confirmed or set up in a clear standard that shows confidence in biodiesel to consumers. Remains adherence to diesel as it has been used for a longer period of time. Therefore, the risk of renewable energy in biodiesel is a relatively high risk. At the same time, in terms of environmental sustainability development, research results show that the use of biodiesel can help reducing air pollution at either PM 2.5 or global warming. Also, it would distribute an income to palm farmers. The results can be implemented for making improvements and suggesting recommendations to the government. A strengthening policy on renewable energy security and implement strategies is for solving various energy problems. With the concept of supporting research and development, it can create a wide range of knowledges, and the production of biodiesel as renewable energy. There should control the price structure, and the well quality practices to be fairly suitable in the nearly future. Keywords: Biodiesel, Consumption, Renewable Energy, Risk, Transportation

The Strategic Value of Big Data Analytics in Health Care Policy-Making

2018 ◽  
Vol 14 (3) ◽  
pp. 20-33 ◽  
Author(s):  
Hamed M. Zolbanin ◽  
Dursun Delen ◽  
Sushil K Sharma
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Health Care Policy ◽  
Big Data Analytics ◽  
Advantages And Disadvantages ◽  
Strategic Value ◽  
Before And After ◽  
The Government ◽  
New Policies

This article describes how the metrics that are used to gauge acceptable versus inadequate care have spurred debates among health care administrators and scholars. Specifically, they argue that the use of readmissions as a quality-of-care metric may reduce patients' safety. Consequently, the new well-intended policies may prove ineffective, or even worse, yield disappointing results. While the discussions over the advantages and disadvantages of the new policies are based more on conjectures rather than on evidence, analytics provides a vehicle to measure the effectiveness of such overarching strategies. In this effort, the authors analyze large volumes of hospital encounters data before and after the implementation of the Patient Protection and Affordable Care Act (PPACA) to show how overlooking some aspects of a problem may lead to unexpected outcomes. The authors conclude that the feedback provided by big data analytics can be used by the government and organization policymakers to obtain a better understanding of loopholes and to propose more effective policies in prospective endeavors.

scholarly journals The dynamics of traffic congestion: a specific look into malaysian scenario and the plausible solutions to eradicate it using machine learning

2019 ◽  
Vol 15 (2) ◽  
pp. 1086
Author(s):  
M. Ali ◽  
T. K. Sheng ◽  
K. M. Yusof ◽  
M. R. Suhaili ◽  
N. E. Ghazali ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Big Data ◽  
Traffic Congestion ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Active Role ◽  
Machine Learning Algorithms ◽  
Asia Pacific ◽  
The Government

Transportation has been considered as the backbone of the economy for the past many years. Unfortunately, since few years due to the uncontrolled urbanization and inadequate planning, countries are facing problem of congestion. The congestion is hindering the economic growth and also causing environmental issues. This has caused serious concerns among the major economies of the world, especially in Asia-Pacific region. Many countries are playing an active role in eradicating this problem and some have been quite successful so far. Malaysia, being a major ASEAN economy is also tackling with this huge problem. The authorities are committed to solve the issue. In this regard, solving the issue leveraging the use of big data analytics has become crucial. The authorities can form a complete robust framework based on big data analytics and decision making process to solve the issue effectively. The work focuses and observes the traffic data samples and analyzes the accuracy of machine learning algorithms, which helps in decision making. Yet, here is a lot to be done if the government needs to solve the problem effectively. Supposedly, a comprehensive big data transport framework leveraging machine learning, is one way to solve the issue.

scholarly journals Big Data and surveillance: Hype, commercial logics and new intimate spheres

2020 ◽  
Vol 7 (1) ◽  
pp. 205395172092585 ◽  
Author(s):  
Kirstie Ball ◽  
William Webster
Keyword(s):  
Big Data ◽  
Value Chain ◽  
Service User ◽  
Data Analytics ◽  
Service Providers ◽  
Big Data Analytics ◽  
User Engagement ◽  
Embodied Experience ◽  
Data Practices ◽  
Private And Public

Big Data Analytics promises to help companies and public sector service providers anticipate consumer and service user behaviours so that they can be targeted in greater depth. The attempts made by these organisations to connect analytically with users raise questions about whether surveillance, and its associated ethical and rights-based concerns, are intensified. The articles in this special themed issue explore this question from both organisational and user perspectives. They highlight the hype which firms use to drive consumer, employee and service user engagement with analytics within both private and public spaces. Further, they explore extent to which, through Big Data, there is an attempt to expand surveillance into the emotional registers of domestic, embodied experience. Collectively, the papers reveal a fascinating nexus between the much-vaunted potential of analytics, the data practices themselves and the newly configured intimate spheres which have been drawn into the commercial value chain. Together, they highlight the need for conceptual and regulatory innovation so that analytics in practice may be better understood and critiqued. Whilst there is now a rich variety of scholarship on Big Data Analytics, critical perspectives on the organising practices of Big Data Analytics and its surveillance implications are thin on the ground. Combined, the articles published in this special theme begin to address this shortcoming.

scholarly journals Big data analytics and sustainable textile manufacturing

2020 ◽  
Vol 58 (8) ◽  
pp. 1699-1714 ◽  
Author(s):  
Dieu Hack-Polay ◽  
Mahfuzur Rahman ◽  
Md Morsaline Billah ◽  
Hesham Z. Al-Sabbahy
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Environmental Sustainability ◽  
Textile Industry ◽  
Data Analytics ◽  
New Technologies ◽  
Developing World ◽  
Big Data Analytics ◽  
Content Type ◽  
Member Exchange

PurposeThe purpose of this article is to discuss issues associated with the application big data analytics for decision-making about the introduction of new technologies in the textile industry in the developing world.Design/methodology/approachThe leader–member exchange theoretical framework to consider the nature of the relationships between owners and followers to identify the potential issues that affect decision-making was used. However, decisions to adopt such environmentally friendly biotechnologies are hampered by the lack of awareness amongst owners, intergenerational conflict and cultural impediments.FindingsThe article found that the limited use of this valuable technological resource is linked to several factors, mainly cultural, generational and educational factors. The article exposes two key new technologies that could help the industry reduce its carbon footprint.Originality/valueThe study suggests more awareness raising amongst plant owners and greater empowerment of new generations in decision-making in the industry. This study, therefore, bears significant implications for environmental sustainability in the developing world where the textile industry is one of the major polluting industries affecting water quality and human health.

scholarly journals Studi On Big Data Analytics Framework in Smart City Context

2021 ◽  
Vol 328 ◽  
pp. 04022
Author(s):  
Rahmawati Dinda ◽  
Arief Assaf ◽  
Do Abdullah Saiful Saiful
Keyword(s):  
Big Data ◽  
Smart City ◽  
Data Analytics ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Future Research ◽  
Technology Governance ◽  
Advantages And Disadvantages ◽  
The Government ◽  
Data Analytic

The issue of global urbanization, which is a separate problem faced by the government, is the very rapid growth of population density in cities. To face this challenge, the government launched a smart city project by targeting sustainable economic growth and improving the quality of life. Information and Communication Technology governance is the key to realizing a smart city. However, each of these I.C.T. tools produce large amounts of data known as Big Data. Data processing with the Big Data approach is becoming a trend in information systems to provide better public services and provide references in the policy-making process. However, to obtain important information in the scope of big data, a Big Data Analytics process is needed, also known as Big Data Value Chain. Extracting knowledge from the related literature can identify the characteristics of the big data analytic framework for smart cities. This paper reviews several big data analytic frameworks applied to smart cities. This paper is to find the advantages and disadvantages of each framework so that it can be a direction for future research

scholarly journals Big Data Analytics With Reference To Wide Variety of Domains

2019 ◽  
Vol 8 (10) ◽  
pp. 1100-1104
Keyword(s):  
Health Care ◽  
Social Networks ◽  
Big Data ◽  
Data Analytics ◽  
High Speed ◽  
Big Data Analytics ◽  
Huge Amount ◽  
Government Sector ◽  
Big Data Technologies ◽  
Survey Results

In the current day scenario, a huge amount of data is been generated from various heterogeneous sources like social networks, business apps, government sector, marketing, health care system, sensors, machine log data which is created at such a high speed and other sources. Big Data is chosen as one among the upcoming area of research by several industries. In this paper, the author presents wide collection of literature that has been reviewed and analyzed. This paper emphasizes on Big Data Technologies, Application & Challenges, a comparative study on architectures, methodologies, tools, and survey results proposed by various researchers are presented

scholarly journals Integrating E-Governance with Big Data Analytics using Apache Spark

2020 ◽  
Vol 8 (6) ◽  
pp. 1609-1615
Keyword(s):  
Big Data ◽  
Management System ◽  
Database Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Database Management System ◽  
Apache Spark ◽  
World Government ◽  
Government Services ◽  
The Government

The constant innovations and rapid developments in the IT industry have revolutionized the thinking and mindset of the people throughout the world. Government departments have also been computerized to provide transparent, efficient and responsible government through e-governance. The government have been providing access to various websites or portal for filing complaints, uploading or downloading forms, pictures, data or PDFs to avail the government services. Enlightened citizens are frequently using the portal to access government services. Thus, the size and volume of data that need to be managed by government departments have been increasing drastically under e-governance. The traditional database management system is not designed to deal with such mix type of data. Moreover, the speed at which the e-governance generated data need to be processed is another big challenge being faced by traditional database system. All the abovesaid concerns can be solved by using the emerging technology - Big Data Analytics techniques. Big data analytic techniques can make the government more efficient and transparent by processing structured, unstructured or mixed types data at a great speed. In this paper, we shall understand the scenario for the need or the emergence of big data analytics in egovernance and knowhow of Apache Spark. This paper proposes a practical approach to integrate big data analytics with egovernance using Apache Spark. This paper also reflects how major issues of traditional database management system (mixed type datasets, speed and accuracy) can be resolved through the integration of big data analytics and e-governance.

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