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024 7 _a10.1007/978-981-19-5723-9
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245 1 0 _aDeep Learning Technologies for the Sustainable Development Goals
_h[electronic resource] :
_bIssues and Solutions in the Post-COVID Era /
_cedited by Virender Kadyan, T. P. Singh, Chidiebere Ugwu.
250 _a1st ed. 2023.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2023.
300 _aXII, 246 p. 83 illus., 63 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvanced Technologies and Societal Change,
_x2191-6861
505 0 _aHow Deep Learning can help in Regulating the Subscription Economy to Ensure Sustainable Consumption and Production Patterns (12th goal of SDGs) -- Deep Technologies using Big Data in: Energy and Waste Management -- QoS aware service provisioning and resource distribution in 4G/5G heterogeneous networks -- Leveraging Fog Computing for Healthcare -- Intelligent self-tuning control design for wastewater treatment plant based on PID and Model Predictive methods -- Impact of Deep learning models for technology sustainability in tourism using Big data analytics -- Study of UAV Management Using Cloud Based Systems -- Contemporary Role of Blockchain in Industry 4.0 -- SDGs Laid Down by UN 2030 Document -- Healthcare 4P: Systematic Review of Applications of Decentralized Trust using Blockchain Technology -- Implementation of An IOT Based Water And Disaster Management System By Using Hybrid Classification Approach -- Knowledge Representation to Expound Deep -- Learning Black Box -- Ann : Concept And Application In Brain Tumor Segmentation -- Automation Of Brain Tumor Segmentation Using Deep Learning -- Transportation Management using IoT Deep Learning to Predict various Traffic States.
520 _aThis book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.
650 0 _aComputational intelligence.
650 0 _aBlockchains (Databases).
650 0 _aSustainability.
650 0 _aQuantitative research.
650 0 _aArtificial intelligence.
650 0 _aInternet of things.
650 1 4 _aComputational Intelligence.
650 2 4 _aBlockchain.
650 2 4 _aSustainability.
650 2 4 _aData Analysis and Big Data.
650 2 4 _aArtificial Intelligence.
650 2 4 _aInternet of Things.
700 1 _aKadyan, Virender.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aSingh, T. P.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aUgwu, Chidiebere.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
_z9789811957246
776 0 8 _iPrinted edition:
_z9789811957253
830 0 _aAdvanced Technologies and Societal Change,
_x2191-6861
856 4 0 _uhttps://doi.org/10.1007/978-981-19-5723-9
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c185100
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