Deep Learning Technologies for the Sustainable Development Goals: Issues and Solutions in the Post-COVID Era

Description

This 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. Preface Acknowledgements Contents Contributors 1 How Deep Learning Can Help in Regulating the Subscription Economy to Ensure Sustainable Consumption and Production Patterns (12th Goal of SDGs) Introduction Why Do We Need Faster and Efficient Manufacturing? How Long Will We Be Able to Rely on Our Natural Resources for Our Rapid Consumption Demand? Subscription Services Mode of Delivery (Online/Offline/Mix) Payment System (Pay as Use/Periodic) Limited and Unlimited Subscription Role of Artificial Intelligence in Subscription Business Evolution of Deep Learning to Support AI Paradox: Deep Learning and Sustainable Consumption Deep Learning as a Solution to Regulate Subscription Economy and Ensuring Sustainable Consumption Reducing Customer Churn in Subscription of OTT Platforms Collaborating Internet of Vehicle (IoV) and Deep Learning in Vehicle Subscription Minimizing Food Wastage and Global Hunger Convolutional Neural Network (CNN) to Help Shoppers in Identifying Green Products Regulating the Energy and Water Consumption Conclusion Discussions on Findings Scope for Future Research Implications for Practitioners References 2 Deep Technologies Using Big Data in: Energy and Waste Management Introduction Deep Learning in Big Data Analytics Exploiting Deep Learning for Energy Management in Big Data Introduction Analytics Model for Energy Management Using Deep Learning Discussion Exploiting Deep Learning for Waste Management in Big Data Introduction Analysis Model of Waste Management Using Deep Learning Discussion Challenges and Prospects: Energy and Waste Management Summary References 3 QoS Aware Service Provisioning and Resource Distribution in 4G/5G Heterogeneous Networks Introduction Related Work QoS Provisioning for M2M Enhanced LTE Network Architecture for 5G Networks Resource Allocation to Ensure QoS Adaptive Channel Bandwidth Selection in LTE 4G/5G Networks System Architecture Delay Bounded QoS Provisioning Hybrid Scheduler with QoS Class Identifier Conclusion References 4 Leveraging Fog Computing for Healthcare Introduction Architecture of Fog Computing Characteristics of Fog Computing Applications of Fog Computing Fog Computing in Healthcare Healthcare Application Needs Aim of Fog Computing in HealthCare Case Studies The Influence of Healthcare 4.0 with FC in Rural Places Healthcare 4.0 ECG Monitoring [27] Patient Training and Monitoring Support [29] Research Challenges Conclusion and Future Work References 5 Intelligent Self-tuning Control Design for Wastewater Treatment Plant Based on PID and Model Predictive Methods Introduction Literature Review Objective of the Work Proposed Control Methodology Modelling of Wastewater Treatment Plant Wastewater Treatment Plant Activated Sludge Process Control Techniques Decentralized PI Controller PID Controller Model Predictive Control Simulation Result and Discussion Conclusion Future Scope References 6 Impact of Deep Learning Models for Technology Sustainability in Tourism Using Big Data Analytics Introduction Deep Learning Progress in Tourism Deep Learning-Based Tourism Models Deep Learning-Based Recommendation System in Tourism Deep Learning-Based Tourist Demand Forecasting Model Deep Learning-Based Sentiment Analysis Models in Tourism Sector Tourism Sustainability and Covid-19 Application to Facilitate Challenges in Tourism Impact of Covid-19 on Tourism Tourism Sustainability: Post Covid-19 Conclusion References 7 Study of UAV Management Using Cloud-Based Systems Introduction Need and Benefits of UAVs Architecture of Cloud Systems UAV Monitoring and Management System Self-allocation Distributed Architecture for Collaborative UAVs Cloud Computing and Smart Objects UAV-Cloud Framework Layers UAV-Cloud Users UAV-Cloud Elements UAV-Cloud Platform Architecture “REST Architecture” UAV Resources Implementation Evaluation of Response Time of UAVs UAV-Cloud Versus Other Related Solution Conclusion Future Work References 8 Contemporary Role of Blockchain in Industry 4.0 Introduction Literature Review IIoT Manufacturing Industry Blockchain Technology and Industry 4.0 Benefits of Blockchain Technology in Manufacturing Systems Challenges Conclusion References 9 SDGs Laid Down by UN 2030 Document Introduction Sustainable Development Goals (SDGs) Conclusion Future Scope References 10 Healthcare 4P: Systematic Review of Applications of Decentralized Trust Using Blockchain Technology Introduction Analysis of Blockchain Applications in Removing Barriers for Information Sharing Barriers in Healthcare Sector Research Methodology Analysis of Existing Barriers in Healthcare Vertical Insights of Blockchain Type for Healthcare Sector Summarized View of Barriers and Applications of Standard Blockchain Types for Healthcare Vertical Analysis of Blockchain Models for Healthcare Sector Summary of Conceptual Lens Based on Literature Review Initial Interview Protocol Challenges in Information Sharing Final Interview Protocol Based on Survey Findings Interview Responses Review of Challenges Across Blockchain Categories Contribution to Literature Conclusion and Future Scope References 11 Implementation of an IoT-Based Water and Disaster Management System Using Hybrid Classification Approach Introduction Related Works Problem Statement Proposed Methodology Result and Discussion Conclusion References 12 ANN: Concept and Application in Brain Tumor Segmentation Introduction Concept of ANN and Activation Function Activation Function (Φ) Steps Involved in ANN Conclusion References 13 Automation of Brain Tumor Segmentation Using Deep Learning Introduction Convolutional Neural Network Convolution Layer Pooling Layer Fully Connected Layer Application of CNN in Brain Tumor Segmentation Conclusion References 14 Transportation Management Using IoT Introduction Under-Utilization of Vehicle Capacity Route Optimality Order Tracking Untimely Delivery of the Consignment Low Visibility of Inventory and Logistics Transportation Cost IoT in Transportation Management IoT Components and Information Accomplishment IoT Dimensions in Transportation Management Basic ANN and Deep Learning [31–33] Deep Learning Using IoT in Transportation Traffic Flow Prediction Traffic Speed Prediction Travel Time Prediction Traffic Congestion Prediction Travel Risk Prediction Traffic Pollution Monitoring Parking Occupancy Prediction Chapter Conclusion and Future Scope References 15 Enhancing Shoppers’ Loyalty by Prioritizing Customer-Centricity Drivers in the Retail Industry Introduction Customer Centricity Drivers Problem Discussion Research Methodology Data Analysis The Model Research Implication Conclusion References