UID:
almahu_9949567209402882
Format:
XII, 182 p. 118 illus., 108 illus. in color.
,
online resource.
Edition:
1st ed. 2023.
ISBN:
9789819946778
Series Statement:
Studies in Big Data, 130
Content:
The volume presents research works on developing Artificial Intelligence based algorithms and methodologies for making social good that too to a notable one. The book discusses latest findings on efficient technological solutions of e-governance and other areas of life from the leading researchers in the field. The prime focus is on solving socio-economic technical problems using state-of-the-art research findings like fuzzy computing, evolutionary and hybrid frameworks, neuro computing, etc., along with other AI based computation platforms. The topics covered include solution frameworks using Artificial Intelligence based models in application areas like agriculture and rural development, road accident, travel and tourism, solid waste management, rural medical care, crowd sourced election monitoring system, ragging, rape and other abuses, cyber criminals and cyber bullying, disaster management, social good, etc. The book offers a valuable resource for all undergraduate, postgraduate students and researchers interested in exploring solution frameworks for social good problems using artificial intelligence.
Note:
Artificial Intelligence for Rural Healthcare Management: Prognosis, Diagnosis and Treatment -- A Study using Support Vector Machine as a Tool for Patient's Satisfaction for SARS-CoV-2 Cases Using Telemedicine -- Applications of AI and IoT technology in Protected Cultivation for Enhancing Agricultural Productivity: A Concise Review -- IoT Based Smart Farming Using AI -- Random Forest Algorithm for Plant Disease Prediction.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9789819946761
Additional Edition:
Printed edition: ISBN 9789819946785
Additional Edition:
Printed edition: ISBN 9789819946792
Language:
English
DOI:
10.1007/978-981-99-4677-8
URL:
https://doi.org/10.1007/978-981-99-4677-8
URL:
Volltext
(URL des Erstveröffentlichers)
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