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Video data analytics is rapidly evolving and transforming the way we live in urban environments. Video Data Analytics for Smart City Applications: Methods and Trends, data science experts present a comprehensive review of the latest advances and trends in video analytics technologies and their extensive applications in smart city planning and engineering. The book covers a wide range of topics including object recognition, action recognition, violence detection, and tracking, exploring deep learning approaches and other techniques for video data analytics. It also discusses the key enabling technologies for smart cities and homes and the scope and application of smart agriculture in smart cities. Moreover, the book addresses the challenges and security issues in terahertz band for wireless communication and the empirical impact of AI and IoT on performance management. One contribution also provides a review of the progress in achieving the Jal Jeevan Mission Goals for institutional capacity building in the Indian State of Chhattisgarh. For researchers, computer scientists, data analytics professionals, smart city planners and engineers, this book provides detailed references for further reading and demonstrates how technologies are serving their use-cases in the smart city. The book highlights the advances and trends in video analytics technologies and extensively addresses key themes, making it an essential resource for anyone looking to gain a comprehensive understanding of video data analytics for smart city applications.
To continue providing people with safe, comfortable, and affordable places to live, cities must incorporate techniques and technologies to bring them into the future. The integration of big data and interconnected technology, along with the increasing population, will lead to the necessary creation of smart cities. Big Data Analytics for Smart and Connected Cities is a pivotal reference source that provides vital research on the application of the integration of interconnected technologies and big data analytics into the creation of smart cities. While highlighting topics such as energy conservation, public transit planning, and performance measurement, this publication explores technology integration in urban environments as well as the methods of planning cities to implement these new technologies. This book is ideally designed for engineers, professionals, researchers, and technology developers seeking current research on technology implementation in urban settings.
This book highlights state-of-the-art research on big data and the Internet of Things (IoT), along with related areas to ensure efficient and Internet-compatible IoT systems. It not only discusses big data security and privacy challenges, but also energy-efficient approaches to improving virtual machine placement in cloud computing environments. Big data and the Internet of Things (IoT) are ultimately two sides of the same coin, yet extracting, analyzing and managing IoT data poses a serious challenge. Accordingly, proper analytics infrastructures/platforms should be used to analyze IoT data. Information technology (IT) allows people to upload, retrieve, store and collect information, which ultimately forms big data. The use of big data analytics has grown tremendously in just the past few years. At the same time, the IoT has entered the public consciousness, sparking people’s imaginations as to what a fully connected world can offer. Further, the book discusses the analysis of real-time big data to derive actionable intelligence in enterprise applications in several domains, such as in industry and agriculture. It explores possible automated solutions in daily life, including structures for smart cities and automated home systems based on IoT technology, as well as health care systems that manage large amounts of data (big data) to improve clinical decisions. The book addresses the security and privacy of the IoT and big data technologies, while also revealing the impact of IoT technologies on several scenarios in smart cities design. Intended as a comprehensive introduction, it offers in-depth analysis and provides scientists, engineers and professionals the latest techniques, frameworks and strategies used in IoT and big data technologies.
Video has rich information including meta-data, visual, audio, spatial and temporal data which can be analysed to extract a variety of low and high-level features to build predictive computational models using machine-learning algorithms to discover interesting patterns, concepts, relations, and associations. This book includes a review of essential topics and discussion of emerging methods and potential applications of video data mining and analytics. It integrates areas like intelligent systems, data mining and knowledge discovery, big data analytics, machine learning, neural network, and deep learning with focus on multimodality video analytics and recent advances in research/applications. Features: Provides up-to-date coverage of the state-of-the-art techniques in intelligent video analytics. Explores important applications that require techniques from both artificial intelligence and computer vision. Describes multimodality video analytics for different applications. Examines issues related to multimodality data fusion and highlights research challenges. Integrates various techniques from video processing, data mining and machine learning which has many emerging indoors and outdoors applications of smart cameras in smart environments, smart homes, and smart cities. This book aims at researchers, professionals and graduate students in image processing, video analytics, computer science and engineering, signal processing, machine learning, and electrical engineering.
The two-volume set LNCS 13373 and 13374 constitutes the papers of several workshops which were held in conjunction with the 21st International Conference on Image Analysis and Processing, ICIAP 2022, held in Lecce, Italy, in May 2022. The 96 revised full papers presented in the proceedings set were carefully reviewed and selected from 157 submissions. ICIAP 2022 presents the following Sixteen workshops: Volume I: GoodBrother workshop on visual intelligence for active and assisted livingParts can worth like the Whole - PART 2022Workshop on Fine Art Pattern Extraction and Recognition - FAPERWorkshop on Intelligent Systems in Human and Artificial Perception - ISHAPE 2022Artificial Intelligence and Radiomics in Computer-Aided Diagnosis - AIRCADDeep-Learning and High Performance Computing to Boost Biomedical Applications - DeepHealth Volume II: Human Behaviour Analysis for Smart City Environment Safety - HBAxSCESBinary is the new Black (and White): Recent Advances on Binary Image ProcessingArtificial Intelligence for preterm infants’ healthCare - AI-careTowards a Complete Analysis of People: From Face and Body to Clothes - T-CAPArtificial Intelligence for Digital Humanities - AI4DHMedical Transformers - MEDXFLearning in Precision Livestock Farming - LPLFWorkshop on Small-Drone Surveillance, Detection and Counteraction Techniques - WOSDETCMedical Imaging Analysis For Covid-19 - MIACOVID 2022Novel Benchmarks and Approaches for Real-World Continual Learning - CL4REAL
This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.
Traffic cameras have the properties of being cost-effective, information-rich, and widely deployed, which are filling up a big gap in today0́9s traffic sensor needs. With the recent progress in traffic operations, information technology, and computer vision, traffic video analytics is driving a broad range of smart city applications with great potential to benefit future transportation and infrastructure systems. Most such applications, e.g., smart traffic surveillance and autonomous driving, require not only high intelligence but also real-time processing capability. Real-time video analytics is well-believed to be one of the most challenging yet most powerful applications for smart cities. It is often bottlenecked by the large volume of video data, high computational cost, and limited data communication bandwidth. This dissertation explores general guidelines and new traffic video analytical methods and systems towards high intelligence and real-time operations for roadway transportation. The designs focus on both the algorithm level and the application system level. On the one hand, lightweight methods are devised based on machine learning techniques and transportation domain knowledge for high smartness, accuracy, and efficiency in specific traffic scenarios. On the other hand, system architectures are developed by leveraging the power of edge computing so that we can split the computational workload between the centralized servers and local Internet-of-Things (IoT) devices for the purpose of system performance optimization. The traffic analytics products and findings in this dissertation can be applied to three transportation-related scenarios with different properties regarding video data collection and processing: (1) traffic surveillance, (2) vehicle onboard sensing, and (3) unmanned aerial vehicle (UAV) sensing. Correspondingly, they apply to three key components of modern intelligent transportation systems (ITS), i.e., smart infrastructures, intelligent vehicle, and aerial surveillance for road traffic. These components possess unique characteristics that can be utilized for video analytics, yet with different challenges to address. To this end, the dissertation proposes algorithms, frameworks, and field implementation examples of how to design and evaluate traffic video analytics systems for smart transportation applications towards high intelligence and efficiency. Experiments were conducted with real-world datasets and tests in a variety of scenarios. This dissertation is among the first efforts in developing edge computing applications for transportation and in exploring UAV sensing for traffic flow.
Integration of IoT with Cloud Computing for Smart Applications provides an integrative overview of the Internet of Things (IoT) and cloud computing to be used for the various futuristic and intelligent applications. The aim of this book is to integrate IoT and cloud computing to translate ordinary resources into smart things. Discussions in this book include a broad and integrated perspective on the collaboration, security, growth of cloud infrastructure, and real-time data monitoring. Features: Presents an integrated approach to solve the problems related to security, reliability, and energy consumption. Explains a unique approach to discuss the research challenges and opportunities in the field of IoT and cloud computing. Discusses a novel approach for smart agriculture, smart healthcare systems, smart cities and many other modern systems based on machine learning, artificial intelligence, and big data, etc. Information presented in a simplified way for students, researchers, academicians and scientists, business innovators and entrepreneurs, management professionals and practitioners. This book can be great reference for graduate and postgraduate students, researchers, and academicians working in the field of computer science, cloud computing, artificial intelligence, etc.
Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today’s modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.
The global tourism industry stands at a crossroads, facing unprecedented challenges that demand immediate attention. Despite its undeniable economic significance, the sector has weathered various crises, prompting a critical reevaluation of its traditional modus operandi. Decision-makers grapple with the urgent need for a transformative approach, questioning how best to navigate the complex web of issues threatening the industry's stability. The convergence of evolving tourist behaviors, uncertainties related to new trends, and the escalating pressure for sustainability creates a pressing need for collaborative, tech-driven strategies to reshape the future of tourism management. Social Media Strategies for Tourism Interactivity emerges as a pivotal resource in this tumultuous landscape. Within the pages of this book, a strategic guide unfolds for decision-makers seeking to thrive in the face of challenges. By delving into the current trends of cooperative competition among traditional micro, small, and medium-sized enterprises (TSMEs), the book advocates for a transformative approach that leverages technological advancements and digitalization. It explores how these strategies can lead to more efficient resource utilization, rapid adaptation to changing tourism demands, and a sustainable balance that aligns with contemporary concerns. In the context of rapid change, this book becomes an essential tool, offering practical and visionary solutions for the substantial challenges of the tourism industry.