Digital Cities Roadmap. Группа авторов

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      1 Chapter 1Figure 1.1 Natural hazard year wise in US.Figure 1.2 Societal principle of resilience and sustainability.Figure 1.3 Decision making resilience and sustainable development framework.Figure 1.4 Bavarian decision analytics.Figure 1.5 Framework system modeling.Figure 1.6 Quantification of resilience.Figure 1.7 Mapping of quantification of sustainability and resilience.Figure 1.8 Techniques of quantification of sustainability and resilience [58].Figure 1.9 Paradigm of damage of building.Figure 1.10 Estimation of household dislocation.Figure 1.11 Estimation of permanent residence.Figure 1.12 Resilience seismic concept [58].Figure 1.13 (a) Healthy population (b) Patients-days treatment.Figure 1.14 (a) Building after earthquake, (b) Building two years after earthqua...Figure 1.15 (a) Improve resilience structure, (b) Reduce probability structural ...Figure 1.16.Building damage by earthquake [55].Figure 1.17 Framework of upper de-aggregation (ULD).Figure 1.18 Framework of critical system modeling.Figure 1.19 Smart building appliances [52].Figure 1.20 Smart Residential Building Connected Sensors and Actuators.Figure 1.21 IoT smart resilience building architecture.Figure 1.22 Smart building components.Figure 1.23 Machine learning techniques.Figure 1.24 ML tasks in SB Environment.Figure 1.25 Framework ML concept in the SB context.Figure 1.26 Taxonomy of SB Services.

      2 Chapter 2Figure 2.1 Block diagram of a sensor [10].Figure 2.2 Blue color represents training data and red color test data.Figure 2.3 Naïve Bayes prediction.Figure 2.4 Forecasting with simple average.Figure 2.5 Prediction based on moving average.Figure 2.6 Simple Exponential Smoothing.Figure 2.7 Holt’s Linear Trend.Figure 2.8 Holt–Winters Method.Figure 2.9 Auto Regressive Integrated Moving Average model.Figure 2.10 Artificial neural network [67].Figure 2.11 Artificial neural network [67].Figure 2.12 Membership values.Figure 2.13 The result when parameters values are high.Figure 2.14 The results at average values of the parameters.Figure 2.15 The results at low values of the parameters.Figure 2.16 Information collected by UAV from smart building for processing.

      3 Chapter 3Figure 3.1 Internet of things landscape concerning data fusion.Figure 3.2 Centralized architecture.Figure 3.3 Decentralized architecture.Figure 3.4 Distributed architecture.Figure 3.5 Smart city infrastructure development framework.Figure 3.6 Smart city monitoring center.Figure 3.7 System use case diagram.Figure 3.8 System flow chart explaining the working.Figure 3.9 First page.Figure 3.10 Firstcandidate and frequent list.Figure 3.11 Second and third candidate and frequent list.Figure 3.12 Input data from text file.Figure 3.13 Display of data and euclidean distance matrix.Figure 3.14 Final result.

      4 Chapter 4Figure 4.1 Domains of smart city [31].Figure 4.2 Simplistic view of blockchain.Figure 4.3 Electronic voting process [50].Figure 4.4 The flow of dividend payment and tax refund application [61].Figure 4.5 Blockchain and environment.Figure 4.6 Smart living.

      5 Chapter 5Figure 5.1 Basic E-Governance model.Figure 5.2 Platform types for Electronic Governance.Figure 5.3 IoT and Cloud (IC) Platform.Figure 5.4 Big Data & Cloud (BC) Platform.Figure 5.5 CPS and Cloud (CC) Platform.Figure 5.6 Ecosystem based data analytics framework [8].Figure 5.7 Ecosystem-based data analytics framework [19].Figure 5.8 Four stage model of E-Governance [3].Figure 5.9 Smart city features/dimensions in India [61].Figure 5.10 Proposed framework for smart governance applications.

      6 Chapter 6Figure 6.1 Framework for design of smart homes for the elderly.Figure 6.2 Schematic design for Nesting Homes.Figure 6.3 IoT-based provisions proposed in Nesting Homes.Figure 6.4 Comprehensive health monitoring system integrated in nesting homes.

      7 Chapter 7Figure 7.1 Organizer use case diagram.Figure 7.2 Candidate use case diagram.Figure 7.3 Voter use case diagram.Figure 7.4 Class diagram for E-voting system.Figure 7.5 Home page.Figure 7.6 Organizer registration.Figure 7.7 Organizer registration.Figure 7.8 Candidate registration.Figure 7.9 Candidate dashboard.Figure 7.10 LIVE election section of HomePage.Figure 7.11 Election result.Figure 7.12 Truffle environment.Figure 7.13 Migration of our contacts to our test environment.Figure 7.14 Transaction Logs of user Election Contract.Figure 7.15 Transaction logs of admin contract.Figure 7.16 Smart contract deployed.Figure 7.17 Adding credentials.Figure 7.18 Check Aadhaar.

      8 Chapter 8Figure 8.1 Comparability in the middle of the approximated global population and...Figure 8.2 IoT-based interconnection.Figure 8.3 Applications of Smart City.Figure 8.4 Classification of IoT-Based Smart Cities.Figure 8.5 IoT-Enabled Smart Cities concerning technologies in IoT Five-layer Ar...Figure 8.6 IoT Five-layer architecture for Smart city applications.Figure 8.7 The IoT Computing paradigm for Smart City Application.Figure 8.8 Clever uses for deploying IoT architecture components on distinct con...Figure 8.9 5-Layered IoT Architecture for Smart City Over the 5-Staged of Smart ...

      9 Chapter 9Figure 9.1 Common symptoms of VOC exposure.Figure 9.2 Various strategies for maintaining healthy IAQ in Green Buildings.

      10 Chapter 10Figure 10.1 Components and themes of a Smart City.Figure 10.2 Smart building.Figure 10.3 Smart building framework.Figure 10.4 Smart health care systems.Figure 10.5 IoT framework.Figure 10.6 Communication technologies.Figure 10.7 Applications of IoT.Figure 10.8 Smart city design challenges.

      11 Chapter 11Figure 11.1 Basic architecture for IoT-based Smart City and Smart Tourism.Figure 11.2 Smart city and smart tourism components.Figure 11.3 Basic flow of mobile application-based trip planner.Figure 11.4 User interfaces for travel booking and task scheduling.

      12 Chapter 12Figure 12.1 Elderly living in a smart home independently and a happy care taker.Figure 12.2 Elderly living in a home independently and a sad care taker.Figure 12.3 Classification of sensors.Figure 12.4 Smart health monitoring cycle.

      13 Chapter 13Figure 13.1 IoT for smart city.Figure 13.2 Potential threats in Smart City.Figure 13.3 ML/DL in securing Smart City.Figure 13.4 KNN for IoT security.Figure 13.5 CNN for IoT security.Figure 13.6 Deep auto encoders working principle.Figure 13.7 Illustration of RNN for IoT security.Figure 13.8 Illustration of RBM working principle.Figure 13.9 GAN working principles.Figure 13.10 Implementation of ML/DL with other technologies.

      14 Chapter 14Figure 14.1 Components of Smart City.

      15 Chapter 15Figure 15.1 Schematic diagram of goals of green buildings.Figure 15.2 Green building optimization (Source: https://blogs.umass.edu/natsci3...Figure 15.3 Use of energy in commercial buildings and green buildings (Source: E...Figure 15.4 Emission of GHG in building structure.Figure 15.5 Comparison between construction materials used in green and conventi...

      1 Chapter 1Table 1.1 Report data of a survey.Table 1.2 Planning for community resilience [55].Table 1.3 Smart control devices [56].Table 1.4 Difference Between Various Smart Control Devices in SB [56].Table 1.5 Difference between of ML techniques.Table 1.6 Difference between deep learning and machine learning tools [56].Table 1.7 Difference between real time data analysis tools [56].Table 1.8 Application of smart buildings [56].

      2 Chapter 2Table 2.1 Results of different techniques.Table 2.2 Action taken for different range of values.Table 2.3 Forecast accuracy of different variables.Table 2.4 Features to be considered for fire detection.

      3 Chapter СКАЧАТЬ