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Open data for sustainable community ...

Sharma, Neha.

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Open data for sustainable community = glocalized sustainable development goals /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Open data for sustainable community/ by Neha Sharma, Santanu Ghosh, Monodeep Saha.
其他題名:	glocalized sustainable development goals /
作者:	Sharma, Neha.
其他作者:	Ghosh, Santanu.
出版者:	Singapore :Springer Singapore : : 2021.,
面頁冊數:	xxiv, 299 p. :ill., digital ;24 cm.
內容註:	Chapter 1. Environment-A Fact Based Study using Tree Census and Air Pollution Data -- Chapter 2. Exploring Air Pollution and Green Cover Dataset- A Quantitative Approach -- Chapter 3. Application of Statistical Analysis in Uncovering the Spatio-Temporal Relationships between the Environmental Datasets -- Chapter 4. Environment - A Fact Based Study using Tree Census and Air Pollution Data -- Chapter 5. Analysis & Visualization of Farmer Call Center Data -- Chapter 6. Chapter 6. An Approach for Exploring New Frontiers for Optimizing Query Volume for Farmer Call Centre - KCC Query Pattern -- Chapter 7. Demand and Supply Study of Healthcare Human Resource and Infrastructure- Through the Lens of COVID 19 -- Chapter 8. COVID-19 and Indian Healthcare System-A Race Against Time -- Chapter 9. Estimating Cases for COVID-19 in India -- Chapter 10.Multi-facet Impact of Pandemic on Society.
Contained By:	Springer Nature eBook
標題:	Sustainable development - Data processing. -
電子資源:	https://doi.org/10.1007/978-981-33-4312-2
ISBN:	9789813343122

Open data for sustainable community = glocalized sustainable development goals /
Sharma, Neha.

Open data for sustainable communityglocalized sustainable development goals /[electronic resource] :by Neha Sharma, Santanu Ghosh, Monodeep Saha. - Singapore :Springer Singapore :2021. - xxiv, 299 p. :ill., digital ;24 cm. - Advances in sustainability science and technology,2662-6829. - Advances in sustainability science and technology..

Chapter 1. Environment-A Fact Based Study using Tree Census and Air Pollution Data -- Chapter 2. Exploring Air Pollution and Green Cover Dataset- A Quantitative Approach -- Chapter 3. Application of Statistical Analysis in Uncovering the Spatio-Temporal Relationships between the Environmental Datasets -- Chapter 4. Environment - A Fact Based Study using Tree Census and Air Pollution Data -- Chapter 5. Analysis & Visualization of Farmer Call Center Data -- Chapter 6. Chapter 6. An Approach for Exploring New Frontiers for Optimizing Query Volume for Farmer Call Centre - KCC Query Pattern -- Chapter 7. Demand and Supply Study of Healthcare Human Resource and Infrastructure- Through the Lens of COVID 19 -- Chapter 8. COVID-19 and Indian Healthcare System-A Race Against Time -- Chapter 9. Estimating Cases for COVID-19 in India -- Chapter 10.Multi-facet Impact of Pandemic on Society.

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.

ISBN: 9789813343122

Standard No.: 10.1007/978-981-33-4312-2doiSubjects--Topical Terms:

2121400
Sustainable development
--Data processing.

LC Class. No.: HC79.E5

Dewey Class. No.: 338.927

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