Electronic Resource

Open Data for Sustainable Community

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Penilaian

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This book is an attempt to bring value to the enterprise pursuits in the areas of research and innovation around the specific issues in terms of topic selection, open data resources and researcher orientation. Over the last 300 years, industrial revolutions have had game-changing impact on societies. Presently, by and large, we are at the crossroads of the fourth industrial revolution, where phygital systems are going to play a massive role, where digital systems can simulate and go beyond the limitations of the physical world, thereby enabling a new world order. This transformation is cutting across every sphere known to mankind. The world will become a globally localized marketplace. In today’s business world, sustainability is a corporate agenda. Enterprises are also aiming to be purpose-driven, adaptive and resilient to disruptions. The contributions to community and environment are part of their corporate branding. The book explores and presents a part of the open data sets from government institutions to achieve the sustainable goals at local level, in turn contributing towards global mission. As the topic suggests, the authors are looking at some of the specific issues in the areas of environment, agriculture and health care through the lens of data science. The authors believe that the above three areas chosen have deep relevance in today’s world. The intent is to explore these issues from a data and analytics perspective and identify cracks through which deeper inroads can be made. Conscious efforts have been taken to make use of all the major data science techniques like prediction, classification, clustering, and correlation. Given the above background, deeper waters will be explored through the contents of this book.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
1908000582	EB0001135	338.927 Sha o	Central Library (OPAC)	Available

Detail Information

Series Title

Advances in Sustainability Science and Technology

Call Number

338.927 Sha o

Publisher

Singapore : Springer Singapore., 2020

Collation

xxiv, 299p.:Ill

Language

English

ISBN/ISSN

978-981-33-4312-2

Classification

338.927

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

-

Subject(s)

Predictive analytics

Specific Detail Info

-

Statement of Responsibility

BRF

Other version/related

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