LEADER 10041nam 2200517 450 001 9910624303403321 005 20230318071842.0 010 $a3-031-08815-8 035 $a(MiAaPQ)EBC7130705 035 $a(Au-PeEL)EBL7130705 035 $a(CKB)25270808200041 035 $a(PPN)266349056 035 $a(EXLCZ)9925270808200041 100 $a20230318d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSustainable smart cities $etheoretical foundations and practical considerations /$feditors, Pradeep Kumar Singh [and three others] 210 1$aCham, Switzerland :$cSpringer,$d[2023] 210 4$d©2023 215 $a1 online resource (342 pages) 225 1 $aStudies in computational intelligence ;$vVolume 942 311 08$aPrint version: Singh, Pradeep Kumar Sustainable Smart Cities Cham : Springer International Publishing AG,c2022 9783031088148 327 $aIntro -- Preface -- Contents -- Social Aspects of Making City Smart -- A Smart City Analytical Framework in Economics -- 1 Introduction -- 2 Literature Review -- 3 Smart City Analytical Framework -- 4 Data in Vietnam -- 5 Conclusion -- 6 Limitations of the Research and the Next Researches -- References -- Smart City-Development Trend in the World and Vietnam -- 1 Introduction -- 2 Concepts About the Smart City -- 3 Smart City Model in the World -- 4 Smart City Development in Vietnam -- 5 Conclusion and Implications -- References -- Smart City from a Standards Perspective -- References -- Point-of-Interests Recommendation Service in Location-Based Social Networks: A Survey, Research Challenges, and Future Perspectives -- 1 Introduction -- 2 Literature Review -- 2.1 Content-Based Recommendation Systems -- 2.2 Collaborative Recommendation Systems -- 2.3 Hybrid Recommendation Systems -- 3 Pros and Cons of Recommendation Algorithms -- 4 Research Challeges -- 5 Conclusion -- References -- San Marcos Smart City: A Proposal of Framework for Developing ISO 37120:2018-Based Smart City's Services for Lima -- 1 Introduction -- 1.1 Why Smart City for Lima -- 1.2 Chapter Organization -- 2 Architecture Proposal -- 2.1 San Marcos Smart City Architecture -- 2.2 Physical Layer -- 2.3 Communication Layer -- 3 Proposal Implementation -- 3.1 WIFI Component -- 3.2 LoRaWAN Component -- 3.3 Facial Recognition Component -- 4 Results -- 4.1 WiFi Component -- 4.2 LoRAWAN Component -- 4.3 Facial Recognition Component -- 5 Summary and Future Directions -- 6 Conclusions -- References -- Social and Technical Challenges in Eco-Sustainable Smart City in India-An Analysis -- 1 Introduction -- 2 A Smart City Model and Its Components -- 3 Role of ICT in the Development of Smart City -- 3.1 Smart Neighbourhood -- 3.2 Smartivists -- 3.3 Smart Community. 327 $a4 Infrastructure and Transport -- 5 Smart Agriculture -- 6 Smart Healthcare -- 7 Smart Energy Management -- 8 Smart Resource Management, Governance, Waste Management -- 9 Education, Training and Security -- 10 Smart City Challenges in India -- 10.1 Mission Smart Cities -- 10.2 Implementation -- 10.3 Challenges and Issues -- 11 Conclusion -- References -- 5G and Other Networking Technologies for Smart Cities -- A Framework for Designing Long Term Digital Preservation System -- 1 Introduction -- 2 General Assumption About Document Retention and Preservation by Organization -- 3 Literature Survey -- 4 Methodology for Digital Data Preservation System (DPS) -- 4.1 Existing System Study Analysis and Design -- 4.2 Examples of Various Categories of Operating Organizations in India -- 4.3 Questionnaire Prepared for Survey in Assistance of Carrying out Face to Face Interview Sessions with Various Organizational Stakeholders -- 4.4 Select the Organization Needs -- 5 The Open Archival Information System Reference Model (OAIS) -- 6 Digital Repository Development -- 7 Conclusion and Future Scope -- References -- Towards Sustainable Smart Cities: The Use of the ViaPPS as Road Monitoring System -- 1 Introduction -- 2 Sensing Technologies in On-Road Object Inventory -- 3 Case Study: The ViaPPS -- 3.1 System Design -- 3.2 Road Inspection-Data Acquisition -- 3.3 Data Handling -- 3.4 Features Extraction and Image Anonymization -- 3.5 Reports and Data Management Systems -- 4 Discussion -- 5 Conclusion -- References -- Optimal Resource Allocation for Public Safety Device to Device Communication Using PSO -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 3.1 Particle Swarm Optimization (PSO) -- 3.2 Resource Allocation Using PSO -- 3.3 Weighted Average Throughput and Penalty for Resource Constrained Settings -- 3.4 Implementation Details -- 4 Results and Analysis. 327 $a5 Conclusion and Future Work -- References -- Research Progress in Internet of Things (IoT) Application in Smart Cities Development: A Bibliometric Analysis -- 1 Introduction -- 2 Methodology -- 3 Results and Discussion -- 3.1 Document Types and Language of Publication -- 3.2 Annual Growth of Publications on IoT Application in Smart Cities -- 3.3 Most Productive SCOPUS Subject Categories and Journals -- 3.4 Most Productive Countries -- 3.5 Highly Productive Institutions in IoT Application in Smart Cities -- 3.6 Highly Cited and Impactful Articles Related to the IoT Application in Smart Cities Development -- 3.7 Author Keyword Analysis and Research Hotspot -- 3.8 Application of Bibliometric Studies in Assessing the Future Research in IoT -- 4 Conclusion -- References -- Neural Network Based Task Scheduling in Cloud Using Harmony Search Algorithm -- 1 Introduction -- 2 Related Work -- 2.1 A. Framework that is Used to Optimize Task Scheduling in the Cloud Environment [1] -- 2.2 B. Harmony Search Algorithm: Strengths and Weaknesses [2] -- 2.3 C. Particle Swarm Optimization: Development, Applications, and Resources [3] -- 2.4 D. NN-Based Secure Task Scheduling in Computational Clouds [4] -- 2.5 E. Ant Colony Optimization [5] -- 2.6 An Idea Based on Honey Bee Swarm for Numerical Optimization [6] -- 2.7 Job Scheduling for Cloud Computing Using Neural Networks [7] -- 3 Proposed Model -- 3.1 Phases of Harmony Search Algorithm -- 3.2 Flow Diagram of the Harmony Search Algorithm -- 3.3 Input Definitions -- 4 Simulation Result -- 5 Conclusion -- References -- Neural Inspired Ant Lion Algorithm for Resource Optimization in Cloud -- 1 Introduction -- 2 Related Work -- 3 Proposed Model -- 4 Results -- 5 Conclusion -- References -- Data Science and Business Analytics, IoT, AI and ML for Smart Cities -- Smart School Selection with Supervised Machine Learning. 327 $a1 Introduction and Related Work -- 1.1 Dataset Description -- 2 Preprocessing -- 3 Experiments and Results -- 3.1 Experiment-I -- 3.2 Experiment-II -- 4 Model Evaluation -- 5 Conclusion -- References -- Artificially Intelligent and Sustainable Smart Cities -- 1 Introduction -- 2 Literature Review -- 3 Background Study -- 3.1 Internet of Things (IoT) -- 3.2 Artificial Intelligence (AI) -- 3.3 Augmented Reality (AR) -- 3.4 Drones -- 3.5 Cloud Computing -- 3.6 Big Data -- 4 Different Portfolios of Smart Cities -- 4.1 Smart Traffic Solution -- 4.2 Smart Fire Brigades -- 4.3 Smart Policy Making and Planning -- 4.4 Smart Farming -- 4.5 Smart Electricity Grids -- 4.6 Smart Parking Solutions -- 4.7 Smart Security Management (Law Enforcement) -- 4.8 Smart Waste Management -- 4.9 Smart Pollution Control -- 4.10 Smart Self-Sustainable Public Toilets -- 4.11 Smart Healthcare Facilities -- 5 Self-Building AI Model -- 6 An Ideal Smart City -- 6.1 ?-Command -- 6.2 ?-Command -- 6.3 ?-Command -- 7 Major Drawbacks -- 8 Conclusion and Future Scope -- References -- Machine Learning Self-Tuning Motivation Engine for Telemarketers -- 1 Introduction -- 2 State of the Art -- 3 Motivation and Serious Games -- 4 A New Perspective: MOTIVARNOS -- 5 Architecture and Basic Concepts -- 5.1 Loading of the Raw Data -- 5.2 Structure of the Data -- 5.3 Data Pre-processing -- 5.4 Exploratory Data Analysis -- 5.5 Telemarketer Profile -- 6 Conclusions and Future Work -- References -- QROWD-A Platform for Integrating Citizens in Smart City Data Analytics -- 1 Introduction -- 2 Related Work -- 2.1 IOT for Smart Cities -- 2.2 Mobile Crowdsensing and Crowdsourcing -- 3 The QROWD Platform and Architecture -- 4 Crowdsourcing Services -- 4.1 Design Guidelines for Human Tasks -- 4.2 Crowdsourcing Service Implementation Framework -- 5 Data Acquisition and Generation. 327 $a5.1 Pre-existing Data Sources -- 5.2 Data from Citizens Devices -- 5.3 Citizen Challenges -- 5.4 Annotations from Street-Level Imagery -- 6 Data Models and Storage -- 6.1 Data Models -- 6.2 Big Data Storage -- 7 Data Integration -- 8 Use Cases -- 8.1 Generating and Managing Mobility Infrastructure Data -- 8.2 Modal Split Surveys -- 9 Summary and Conclusion -- References -- Estimation of Short-Time Forecast for Covid-19 Outbreak in India: State-Wise Prediction and Analysis -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 4 Data Pre-processing -- 4.1 Population -- 4.2 Weather -- 5 Result Analysis -- 5.1 Time-Series Plots -- 6 Results -- 6.1 Short Term Predictions and Their Analysis -- 6.2 Kalman X-days Prediction Discussion for Indian Subcontinents -- 6.3 Comparative Analysis of Different Nations -- 7 Conclusion -- References. 410 0$aStudies in computational intelligence ;$vVolume 942. 606 $aInternet of things. 606 $aSmart cities. 606 $aSustainable development 615 0$aInternet of things. . 615 0$aSmart cities. . 615 0$aSustainable development. 676 $a004.678 702 $aSingh$b Pradeep Kumar 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910624303403321 996 $aSustainable Smart Cities$92100711 997 $aUNINA