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| fleet management data analytics: Aligning Business Strategies and Analytics Murugan Anandarajan, Teresa D. Harrison, 2018-09-27 This book examines issues related to the alignment of business strategies and analytics. Vast amounts of data are being generated, collected, stored, processed, analyzed, distributed and used at an ever-increasing rate by organizations. Simultaneously, managers must rapidly and thoroughly understand the factors driving their business. Business Analytics is an interactive process of analyzing and exploring enterprise data to find valuable insights that can be exploited for competitive advantage. However, to gain this advantage, organizations need to create a sophisticated analytical climate within which strategic decisions are made. As a result, there is a growing awareness that alignment among business strategies, business structures, and analytics are critical to effectively develop and deploy techniques to enhance an organization’s decision-making capability. In the past, the relevance and usefulness of academic research in the area of alignment is often questioned by practitioners, but this book seeks to bridge this gap. Aligning Business Strategies and Analytics: Bridging Between Theory and Practice is comprised of twelve chapters, divided into three sections. The book begins by introducing business analytics and the current gap between academic training and the needs within the business community. Chapters 2 - 5 examines how the use of cognitive computing improves financial advice, how technology is accelerating the growth of the financial advising industry, explores the application of advanced analytics to various facets of the industry and provides the context for analytics in practice. Chapters 6 - 9 offers real-world examples of how project management professionals tackle big-data challenges, explores the application of agile methodologies, discusses the operational benefits that can be gained by implementing real-time, and a case study on human capital analytics. Chapters 10 - 11 reviews the opportunities and potential shortfall and highlights how new media marketing and analytics fostered new insights. Finally the book concludes with a look at how data and analytics are playing a revolutionary role in strategy development in the chemical industry. |
| fleet management data analytics: Data Intelligence and Cognitive Informatics I. Jeena Jacob, Selwyn Piramuthu, Przemyslaw Falkowski-Gilski, 2024-02-07 The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2023), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during June 27–28, 2023. This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems. |
| fleet management data analytics: Big Data Analytics for Connected Vehicles and Smart Cities Bob McQueen, 2017-08-31 This practical new book presents the application of “big data” analytics to connected vehicles, smart cities, and transportation systems. This book enables transportation professionals to understand how data analytics can and will expand the design and engineering of connected vehicles and smart cities. Readers find extensive case studies and examples that provide a strong framework focusing on practical application of data sciences and analytic tools for actual projects in the field. Both federal and private sector investments have a strong interest in the connected vehicle and this book discusses the impact this has on transportation. This book defines urban analytics and modeling, incentives and governance, mobility networks, energy networks, and other attributes and elements that craft a smart city. Readers learn how smart cities impact the application of advanced technologies in urban areas. This book explains how recently passed transportation legislation for the US has a specific emphasis on the use of data for performance management. |
| fleet management data analytics: Data Analytics for Smart Cities Amir Alavi, William G. Buttlar, 2018-10-26 The development of smart cities is one of the most important challenges over the next few decades. Governments and companies are leveraging billions of dollars in public and private funds for smart cities. Next generation smart cities are heavily dependent on distributed smart sensing systems and devices to monitor the urban infrastructure. The smart sensor networks serve as autonomous intelligent nodes to measure a variety of physical or environmental parameters. They should react in time, establish automated control, and collect information for intelligent decision-making. In this context, one of the major tasks is to develop advanced frameworks for the interpretation of the huge amount of information provided by the emerging testing and monitoring systems. Data Analytics for Smart Cities brings together some of the most exciting new developments in the area of integrating advanced data analytics systems into smart cities along with complementary technological paradigms such as cloud computing and Internet of Things (IoT). The book serves as a reference for researchers and engineers in domains of advanced computation, optimization, and data mining for smart civil infrastructure condition assessment, dynamic visualization, intelligent transportation systems (ITS), cyber-physical systems, and smart construction technologies. The chapters are presented in a hands-on manner to facilitate researchers in tackling applications. Arguably, data analytics technologies play a key role in tackling the challenge of creating smart cities. Data analytics applications involve collecting, integrating, and preparing time- and space-dependent data produced by sensors, complex engineered systems, and physical assets, followed by developing and testing analytical models to verify the accuracy of results. This book covers this multidisciplinary field and examines multiple paradigms such as machine learning, pattern recognition, statistics, intelligent databases, knowledge acquisition, data visualization, high performance computing, and expert systems. The book explores new territory by discussing the cutting-edge concept of Big Data analytics for interpreting massive amounts of data in smart city applications. |
| fleet management data analytics: Internet of Things and Big Data Analytics-Based Manufacturing Arun Kumar Rana, Sudeshna Chakraborty, Pallavi Goel, Sumit Kumar Rana, Ahmed A. Elngar, 2024-10-17 By enabling the conversion of traditional manufacturing systems into contemporary digitalized ones, Internet of Things (IoT) adoption in manufacturing creates huge economic prospects through reshaping industries. Modern businesses can more readily implement new data-driven strategies and deal with the pressure of international competition thanks to Industrial IoT. But as the use of IoT grows, the amount of created data rises, turning industrial data into Industrial Big Data. Internet of Things and Big Data Analytics-Based Manufacturing shows how Industrial Big Data can be produced as a result of IoT usage in manufacturing, considering sensing systems and mobile devices. Different IoT applications that have been developed are demonstrated and it is shown how genuine industrial data can be produced, leading to Industrial Big Data. This book is organized into four sections discussing IoT and technology, the future of Big Data, algorithms, and case studies demonstrating the use of IoT and Big Data in a variety of industries, including automation, industrial manufacturing, and healthcare. This reference title brings all related technologies into a single source so that researchers, undergraduate and postgraduate students, academicians, and those in the industry can easily understand the topic and further their knowledge. |
| fleet management data analytics: Data Science and Data Analytics Dinesh Kumar Arivalagan, 2024-07-31 Data Science and Data Analytics explores the foundational concepts, methodologies, and tools that drive data-driven decision-making in various industries. This book provides a comprehensive overview of data collection, processing, analysis, and visualization techniques, emphasizing practical applications and real-world case studies. Readers will gain insights into statistical methods, machine learning algorithms, and the importance of data ethics, equipping them with the knowledge to harness the power of data for informed decision-making and strategic planning in an increasingly data-centric world. |
| fleet management data analytics: Data Analytics Applied to the Mining Industry Ali Soofastaei, 2020-11-12 Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors |
| fleet management data analytics: Predictive Analytics Vijay Kumar, Mangey Ram, 2021-01-13 Predictive analytics refers to making predictions about the future based on different parameters which are historical data, machine learning, and artificial intelligence. This book provides the most recent advances in the field along with case studies and real-world examples. It discusses predictive modeling and analytics in reliability engineering and introduces current achievements and applications of artificial intelligence, data mining, and other techniques in supply chain management. It covers applications to reliability engineering practice, presents numerous examples to illustrate the theoretical results, and considers and analyses case studies and real-word examples. The book is written for researchers and practitioners in the field of system reliability, quality, supply chain management, and logistics management. Students taking courses in these areas will also find this book of interest. |
| fleet management data analytics: The Next Wave of Sociotechnical Design Leona Chandra Kruse, Stefan Seidel, Geir Inge Hausvik, 2021-07-27 This book constitutes the thoroughly refereed proceedings of the 16th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2021, held in Kristiansand, Norway, in August 2021.* The 24 revised full research papers, included in the volume together with 6 short contributions and 7 prototype papers, were carefully reviewed and selected from 78 submissions. They are organized in the following topical sections: impactful sociotechnical design; problem and contribution articulation; design knowledge for reuse; emerging methods and frameworks for DSR; DSR and governance; the new boundaries of DSR. *Apart from the planned on-site event, the hybrid conference model was explored due to the Covid-19 pandemic. |
| fleet management data analytics: Recent Trends and Future Direction for Data Analytics Kumari, Aparna, 2024-05-14 In an increasingly data-centric world, scholars and practitioners grapple with the complexities of harnessing data analytics effectively across various industries. The challenge lies in navigating the rapid evolution of methodologies, identifying emerging trends, and understanding the nuanced applications of data analytics in real-world scenarios. This gap between theory and practice inhibits academic progress. It hampers industry innovation, leaving stakeholders needing help to leverage data to its full potential. Recent Trends and Future Direction for Data Analytics presents a compelling solution. By delving into real-world case studies spanning supply chain management, marketing, healthcare, and finance, this book bridges the gap between theory and practice, offering invaluable insights into the practical applications of data analytics. A systematic exploration of fundamental concepts, advanced techniques, and specialized topics equips scholars, researchers, and industry professionals with the knowledge and tools needed to navigate the complexities of data analytics with confidence. |
| fleet management data analytics: Applying Predictive Analytics Richard V. McCarthy, Mary M. McCarthy, Wendy Ceccucci, Leila Halawi, 2019-03-12 This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes. |
| fleet management data analytics: Deep Learning and Big Data for Intelligent Transportation Khaled R. Ahmed, Aboul Ella Hassanien, 2021-04-10 This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today’s technology. Road sensors, UAVs, GPS, CCTV and incident reports are sources of massive amount of data which are crucial to make serious traffic decisions. Herewith this substantial volume and velocity of data, it is challenging to build reliable prediction models based on machine learning methods and traditional relational database. Therefore, this book includes recent research works on big data, deep convolution networks and IoT-based smart solutions to limit the vehicle’s speed in a particular region, to support autonomous safe driving and to detect animals on roads for mitigating animal-vehicle accidents. This book serves broad readers including researchers, academicians, students and working professional in vehicles manufacturing, health and transportation departments and networking companies. |
| fleet management data analytics: Internet of Things and Data Analytics Handbook Hwaiyu Geng, 2017-01-10 This book examines the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view. Internet of Things and Data Analytics Handbook describes essential technical knowledge, building blocks, processes, design principles, implementation, and marketing for IoT projects. It provides readers with knowledge in planning, designing, and implementing IoT projects. The book is written by experts on the subject matter, including international experts from nine countries in the consumer and enterprise fields of IoT. The text starts with an overview and anatomy of IoT, ecosystem of IoT, communication protocols, networking, and available hardware, both present and future applications and transformations, and business models. The text also addresses big data analytics, machine learning, cloud computing, and consideration of sustainability that are essential to be both socially responsible and successful. Design and implementation processes are illustrated with best practices and case studies in action. In addition, the book: Examines cloud computing, data analytics, and sustainability and how they relate to IoT overs the scope of consumer, government, and enterprise applications Includes best practices, business model, and real-world case studies Hwaiyu Geng, P.E., is a consultant with Amica Research (www.AmicaResearch.org, Palo Alto, California), promoting green planning, design, and construction projects. He has had over 40 years of manufacturing and management experience, working with Westinghouse, Applied Materials, Hewlett Packard, and Intel on multi-million high-tech projects. He has written and presented numerous technical papers at international conferences. Mr. Geng, a patent holder, is also the editor/author of Data Center Handbook (Wiley, 2015). |
| fleet management data analytics: People Analytics in the Era of Big Data Jean Paul Isson, Jesse S. Harriott, 2016-04-21 Apply predictive analytics throughout all stages of workforce management People Analytics in the Era of Big Data provides a blueprint for leveraging your talent pool through the use of data analytics. Written by the Global Vice President of Business Intelligence and Predictive Analytics at Monster Worldwide, this book is packed full of actionable insights to help you source, recruit, acquire, engage, retain, promote, and manage the exceptional talent your organization needs. With a unique approach that applies analytics to every stage of the hiring process and the entire workforce planning and management cycle, this informative guide provides the key perspective that brings analytics into HR in a truly useful way. You're already inundated with disparate employee data, so why not mine that data for insights that add value to your organization and strengthen your workforce? This book presents a practical framework for real-world talent analytics, backed by groundbreaking examples of workforce analytics in action across the U.S., Canada, Europe, Asia, and Australia. Leverage predictive analytics throughout the hiring process Utilize analytics techniques for more effective workforce management Learn how people analytics benefits organizations of all sizes in various industries Integrate analytics into HR practices seamlessly and thoroughly Corporate executives need fact-based insights into what will happen with their talent. Who should you hire? Who should you promote? Who are the top or bottom performers, and why? Who is at risk to quit, and why? Analytics can provide these answers, and give you insights based on quantifiable data instead of gut feeling and subjective assessment. People Analytics in the Era of Big Data is the essential guide to optimizing your workforce with the tools already at your disposal. |
| fleet management data analytics: Strategic Leadership and Management in the Automotive Industry Jenny Tran.T. Hoan My, 2024-08-12 The automotive industry is one of the most dynamic and competitive sectors globally, constantly evolving through technological advancements and market shifts. Strategic Leadership and Management in the Automotive Industry explores the critical aspects of strategic management and leadership that drive success in this field. This book offers a comprehensive analysis of leadership theories, strategic planning, operational excellence, and marketing strategies, with a special focus on Proton Holdings Berhad, a prominent automotive manufacturer. |
| fleet management data analytics: Encyclopedia of Business ideas Mansoor Muallim, (Content updated) Agri-Tools Manufacturing 1. Market Overview: The Agri-Tools Manufacturing industry is a vital part of the agriculture sector, providing essential equipment and machinery to support farming operations. Growth is driven by the increasing demand for advanced and efficient farming tools to meet the rising global food production requirements. 2. Market Segmentation: The Agri-Tools Manufacturing market can be segmented into several key categories: a. Hand Tools: • Basic manual tools used for tasks like planting, weeding, and harvesting. b. Farm Machinery: • Larger equipment such as tractors, Plows, and combines used for field cultivation and crop management. c. Irrigation Equipment: • Tools and systems for efficient water management and irrigation. d. Harvesting Tools: • Machinery and hand tools for crop harvesting and post-harvest processing. e. Precision Agriculture Tools: • High-tech equipment including GPS-guided machinery and drones for precision farming. f. Animal Husbandry Equipment: • Tools for livestock management and animal husbandry practices. 3. Regional Analysis: The adoption of Agri-Tools varies across regions: a. North America: • A mature market with a high demand for advanced machinery, particularly in the United States and Canada. b. Europe: • Growing interest in precision agriculture tools and sustainable farming practices. c. Asia-Pacific: • Rapidly expanding market, driven by the mechanization of farming in countries like China and India. d. Latin America: • Increasing adoption of farm machinery due to the region's large agricultural sector. e. Middle East & Africa: • Emerging market with potential for growth in agri-tools manufacturing. 4. Market Drivers: a. Increased Farming Efficiency: • The need for tools and machinery that can increase farm productivity and reduce labour costs. b. Population Growth: • The growing global population requires more efficient farming practices to meet food demands. c. Precision Agriculture: • The adoption of technology for data-driven decision-making in farming. d. Sustainable Agriculture: • Emphasis on tools that support sustainable and eco-friendly farming practices. 5. Market Challenges: a. High Initial Costs: • The expense of purchasing machinery and equipment can be a barrier for small-scale farmers. b. Technological Adoption: • Some farmers may be resistant to adopting new technology and machinery. c. Maintenance and Repairs: • Ensuring proper maintenance and timely repairs can be challenging. 6. Opportunities: a. Innovation: • Developing advanced and efficient tools using IoT, AI, and automation. b. Customization: • Offering tools tailored to specific crops and regional needs. c. Export Markets: • Exploring export opportunities to regions with growing agricultural sectors. 7. Future Outlook: The future of Agri-Tools Manufacturing looks promising, with continued growth expected as technology continues to advance and the need for efficient and sustainable agriculture practices increases. Innovations in machinery and equipment, along with the adoption of precision agriculture tools, will play a significant role in transforming the industry and addressing the challenges faced by the agriculture sector. Conclusion: Agri-Tools Manufacturing is a cornerstone of modern agriculture, providing farmers with the equipment and machinery they need to feed a growing global population. As the industry continues to evolve, there will be opportunities for innovation and collaboration to develop tools that are not only efficient but also environmentally friendly. Agri-tools manufacturers play a critical role in supporting sustainable and productive farming practices, making them essential contributors to the global food supply chain. |
| fleet management data analytics: Internet of Things Pramod R. Gunjal, Satish R. Jondhale, Jaime Lloret Mauri, Karishma Agrawal, 2024-03-14 This book addresses the fundamental technologies, architectures, application domains, and future research directions of the Internet of Things (IoT). It also discusses how to create your own IoT system according to applications requirements, and it presents a broader view of recent trends in the IoT domain and open research issues. This book encompasses various research areas such as wireless networking, advanced signal processing, IoT, and ubiquitous computing. Internet of Things: Theory to Practice discusses the basics and fundamentals of IoT and real-time applications, as well as the associated challenges and open research issues. The book includes several case studies about the use of IoT in day-to-day life. The authors review various advanced computing technologies—such as cloud computing, fog computing, edge computing, and Big Data analytics—that will play crucial roles in future IoT-based services. The book provides a detailed role of blockchain technology, Narrowband IoT (NB-IoT), wireless body area network (WBAN), LoRa (a longrange low power platform), and Industrial IoT (IIoT) in the 5G world. This book is intended for university/college students, as well as amateur electronic hobbyists and industry professionals who are looking to stay current in the IoT domain. |
| fleet management data analytics: Video Data Analytics for Smart City Applications: Methods and Trends Abhishek Singh Rathore, 2023-04-20 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. |
| fleet management data analytics: Supply Chain Analytics Kurt Y. Liu, 2022-04-07 This innovative new core textbook, written by an experienced professor and practitioner in supply chain management, offers a business-focused overview of the applications of data analytics and machine learning to supply chain management. Accessible yet rigorous, this text introduces students to the relevant concepts and techniques needed for data analysis and decision making in modern supply chains and enables them to develop proficiency in a popular and powerful programming software. Suitable for use on upper-level undergraduate, postgraduate and MBA courses in supply chain management, it covers all of the major supply chain processes, including managing supply and demand, warehousing and inventory control, transportation and route optimization. Each chapter comes with practical real-world examples drawn from a range of business contexts, including Amazon and Starbucks, case study discussion questions, computer-assisted exercises and programming projects. |
| fleet management data analytics: AI-Powered Productivity Dr. Asma Asfour, 2024-07-29 This book, AI-Powered Productivity, aims to provide a guide to understanding, utilizing AI and generative tools in various professional settings. The primary purpose of this book is to offer readers a deep dive into the concepts, tools, and practices that define the current AI landscape. From foundational principles to advanced applications, this book is structured to cater to both beginners and professionals looking to enhance their knowledge and skills in AI. This book is divided into nine chapters, each focusing on a specific aspect of AI and its practical applications: Chapter 1 introduces the basic concepts of AI, its impact on various sectors, and key factors driving its rapid advancement, along with an overview of generative AI tools. Chapter 2 delves into large language models like ChatGPT, Google Gemini, Claude, Microsoft's Turing NLG, and Facebook's BlenderBot, exploring their integration with multimodal technologies and their effects on professional productivity. Chapter 3 offers a practical guide to mastering LLM prompting and customization, including tutorials on crafting effective prompts and advanced techniques, as well as real-world examples of AI applications. Chapter 4 examines how AI can enhance individual productivity, focusing on professional and personal benefits, ethical use, and future trends. Chapter 5 addresses data-driven decision- making, covering data analysis techniques, AI in trend identification, consumer behavior analysis, strategic planning, and product development. Chapter 6 discusses strategic and ethical considerations of AI, including AI feasibility, tool selection, multimodal workflows, and best practices for ethical AI development and deployment. Chapter 7 highlights the role of AI in transforming training and professional development, covering structured training programs, continuous learning initiatives, and fostering a culture of innovation and experimentation. Chapter 8 provides a guide to successfully implementing AI in organizations, discussing team composition, collaborative approaches, iterative development processes, and strategic alignment for AI initiatives. Finally, Chapter 9 looks ahead to the future of work, preparing readers for the AI revolution by addressing training and education, career paths, common fears, and future trends in the workforce. The primary audience for the book is professionals seeking to enhance productivity and organizations or businesses. For professionals, the book targets individuals from various industries, reflecting its aim to reach a broad audience across different professional fields. It is designed for employees at all levels, offering valuable insights to both newcomers to AI and seasoned professionals. Covering a range of topics from foundational concepts to advanced applications, the book is particularly relevant for those interested in improving efficiency, with a strong emphasis on practical applications and productivity tools to optimize work processes. For organizations and businesses, the book serves as a valuable resource for decision-makers and managers, especially with chapters on data-driven decision-making, strategic considerations, and AI implementation. HR and training professionals will find the focus on AI in training and development beneficial for talent management, while IT and technology teams will appreciate the information on AI tools and concepts. |
| fleet management data analytics: Building Secure Automotive IoT Applications Dr. Dennis Kengo Oka, Sharanukumar Nadahalli, Jeff Yost, Ram Prasad Bojanki, 2024-08-28 Enhance your automotive IoT design and development knowledge by learning vehicle architectures, cybersecurity best practices, cloud applications, and software development processes Key Features Explore modern vehicle architectures designed to support automotive IoT use cases Discover cybersecurity practices and processes to develop secure automotive IoT applications Gain insights into how cloud technologies and services power automotive IoT applications Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionSoftware-defined vehicles, equipped with extensive computing power and connectivity, are unlocking new possibilities in automotive Internet of Things (IoT) applications, creating a critical need for skilled software engineers to lead innovation in the automotive sector. This book equips you to thrive in this industry by learning automotive IoT software development. The book starts by examining the current trends in automotive technology, highlighting IoT applications and key vehicle architectures, including the AUTOSAR platform. It delves into both classic and service-oriented vehicle diagnostics before covering robust security practices for automotive IoT development. You’ll learn how to adhere to industry standards such as ISO/SAE 21434, ASPICE for cybersecurity, and DevSecOps principles, with practical guidance on establishing a secure software development platform. Advancing to the system design of an automotive IoT application, you’ll be guided through the development of a remote vehicle diagnostics application and progress through chapters step by step, addressing the critical aspects of deploying and maintaining IoT applications in production environments. By the end of the book, you’ll be ready to integrate all the concepts you’ve learned to form a comprehensive framework of processes and best practices for embedded automotive development.What you will learn Explore the current automotive landscape and IoT tech trends Examine automotive IoT use cases such as phone-as-a-key, predictive maintenance, and V2X Grasp standard frameworks such as classic and adaptive AUTOSAR Get to grips with vehicle diagnostic protocols such as UDS, DoIP, and SOVD Establish a secure development process and mitigate software supply chain risks with CIAD, RASIC, and SBOM Leverage ASPICE and functional safety processes for industry standards compliance Understand how to design, develop, and deploy an automotive IoT application Who this book is for This book is for embedded developers and software engineers working in the automotive industry looking to learn IoT development, as well as IoT developers who want to learn automotive development. A fundamental grasp of software development will assist with understanding the concepts covered in the book. |
| fleet management data analytics: Smart Mobility Bob McQueen, Ammar Safi, Shafia Alkheyaili, 2024-07-25 Comprehensive learning resource providing a framework for successful application of advanced transportation technologies in urban areas Smart Mobility: Using Technology to Improve Transportation in Smart Cities addresses the nature and characteristics of smart cities, providing a focus on smart mobility within urban areas and the opportunities and challenges associated with the application of advanced transportation technologies. The three highly qualified authors include an emphasis on decarbonization possibilities and the potential for smart mobility to reduce emissions and fuel consumption while optimizing modal use, along with risk identification and management using a structured approach. A focus is also placed on the need for end-to-end travel support from origin to ultimate destination, reflecting consumer needs for comprehensive decision support and travel support services. Overall, Smart Mobility provides a framework, planning, and KPIs for smart mobility success and explains how effective performance management can be enabled. Additional topics covered in this modern and thought-provoking work include: Policies and strategies associated with smart mobility, including a description of the organizational arrangements required to support smart mobility technologies The definition of appropriate institutional, funding, and commercial arrangements to assist interested practitioners to solve what is often their biggest challenge Coverage of smart mobility operational management, explaining the likely impact of smart mobility on transportation operations How to attain balance between transportation objectives and the avoidance of undesirable side effects such as congestion For public and private sector professionals in the smart mobility community, Smart Mobility is an essential and easy-to-understand learning resource that will help readers comprehend the state-of-the-art progress in the field and be prepared for future advancements in this important and rapidly-developing industry. |
| fleet management data analytics: Big Data Analytics Techniques for Market Intelligence Darwish, Dina, 2024-01-04 The ever-expanding realm of Big Data poses a formidable challenge for academic scholars and professionals due to the sheer magnitude and diversity of data types, along with the continuous influx of information from various sources. Extracting valuable insights from this vast and complex dataset is crucial for organizations to uncover market intelligence and make informed decisions. However, without the proper guidance and understanding of Big Data analytics techniques and methodologies, scholars may struggle to navigate this landscape and maximize the potential benefits of their research. In response to this pressing need, Professor Dina Darwish presents Big Data Analytics Techniques for Market Intelligence, a groundbreaking book that addresses the specific challenges faced by scholars and professionals in the field. Through a comprehensive exploration of various techniques and methodologies, this book offers a solution to the hurdles encountered in extracting meaningful information from Big Data. Covering the entire lifecycle of Big Data analytics, including preprocessing, analysis, visualization, and utilization of results, the book equips readers with the knowledge and tools necessary to unlock the power of Big Data and generate valuable market intelligence. With real-world case studies and a focus on practical guidance, scholars and professionals can effectively leverage Big Data analytics to drive strategic decision-making and stay at the forefront of this rapidly evolving field. |
| fleet management data analytics: Decision Support, Analytics, and Business Intelligence, Second Edition Daniel J. Power, 2013-01-11 Competition is becoming more intense and decision makers are encountering increasing complexity, rapid change, and higher levels of risk. In many situations, the solution is more and better computerized decision support, especially analytics and business intelligence. Today managers need to learn about and understand computerized decision support. If a business is to succeed, managers must know much more about information technology solutions. This second edition of a powerful introductory book is targeted at busy managers and MBA students who need to grasp the basics of computerized decision support, including the following: What are analytics? What is a decision support system? How can managers identify opportunities to create innovative computerized support? Inside, the author addresses these questions and some 60 more fundamental questions that are key to understanding the rapidly changing realm of computerized decision support. In a short period of time, you’ll “get up to speed” on decision support, analytics, and business intelligence. |
| fleet management data analytics: Proceedings of Fifth International Conference on Computing, Communications, and Cyber-Security Sudeep Tanwar, |
| fleet management data analytics: Supply Chain Integration Challenges in Commercial Aerospace Klaus Richter, Johannes Walther, 2016-12-13 This book presents firsthand insights into strategies and approaches for the commercial aerospace supply chain in response to the numerous changes that airlines, aircraft OEMs and their suppliers have experienced over the past few decades. In doing so, it investigates the entire product value chain. Accordingly, the chapters address the challenges of configuration and demand, and highlight the specificities of customization in the aviation industry. They analyze component manufacturing, share valuable insights into assembly and integration activities, and describe aftermarket business models. In order to ensure more varied and balanced coverage, the book includes contributions by researchers, suppliers, and experts and practitioners from consulting companies and the aircraft industry. Taken together, they provide a holistic perspective on the transformation drivers and the innovations that have either been implemented or will be adopted in the near future. The book introduces and describes new concepts and innovations such as 3D printing, E2E demand management, digital production, predictive maintenance and open innovation in general, supplementing them with sample industrial applications from the aviation sector. |
| fleet management data analytics: Entrepreneurship and Knowledge Exchange Jay Mitra, John Edmondson, 2015-04-17 Over the last several decades there has been a growing interest in the relationship between entrepreneurship and university-industry collaboration, namely how such cooperation can benefit entrepreneurship development at individual, national, and regional levels. While there are several refereed journal articles on different aspects of university-industry cooperation, most studies dwell primarily on instruments such as spin-offs, incubators and graduate entrepreneurs. This collection offers the first book-length compendium of international comparative perspectives on university-industry cooperation. Entrepreneurship and Knowledge Exchange explores insights from a wide variety of countries of relevance to researchers as well as policy and decision makers, especially those working in developing economies. Seminal contributions from top academics in the field, such as Alan Gibb, Peter Scott, and Mary Walshok, are included. The issues of knowledge transfer, entrepreneurship, and regional/national economic regeneration have inspired countless programs and initiatives at national and regional levels, and the chapters in this book examine these initiatives, providing both a reference work and a record of practical experience. |
| fleet management data analytics: Sustainable Mobility Ashwani Kumar, Arbind Prasad, Gaurav Kumar, 2024-11-07 This book is essential for anyone interested in understanding and implementing sustainable transportation practices, as it provides comprehensive insights into the challenges, advancements, and policies related to sustainable mobility. Sustainable transportation refers to any means of transportation that is “green” and has a low impact on the environment. The goal of sustainable transportation is to balance our current and future needs. As per the United Nations Brundtland Commission (WCED, 1987), sustainable mobility can be defined as “mobility that satisfies the needs of present generations without compromising future generations”, but in the modern era, we are compromising the needs of the next generation in terms of pollution, depletion of fossil fuels, global warming, poor air quality, and hazardous gases. The three main pillars of sustainability, economics, environment, and social issues, are crushed by modern development, so there is a need to shift from traditional means of transportation to sustainable transportation. Under the vision of sustainable mobility, better infrastructure and services will be provided to support the movement of goods and people. This outcome will be achieved only if four goals are pursued simultaneously: developing the right policy, building awareness, developing intelligent transportation, and creating green vehicles. Sustainable Mobility: Policies, Challenges and Advancements will discuss transitions from conventional to sustainable mobility, infrastructure development challenges in this transition period, new vehicle policies, and the latest autonomous vehicles for intelligent transportation. The main highlights of the book are energy efficient technologies for transportation, accessibility and safety of the transport system, environmental footprint, health impacts, economic development, and social growth. Sustainable mobility is essential to economic and social development. The environmental impacts of transport can be reduced by reducing the weight of vehicles, creating sustainable styles of driving, reducing the friction of tires, encouraging electric and hybrid vehicles, improving the walking and cycling environment in cities, and enhancing the role of public transport, especially electric vehicles. Going green and sustainable is not only beneficial for the company, but it also maximizes the benefits of an environmental focus in the long term. |
| fleet management data analytics: Smart Cities: Power Electronics, Renewable Energy, and Internet of Things Ahteshamul Haque, Akhtar Kalam, Himanshu Sharma, 2024-02-19 This book discusses the integration of power electronics, renewable energy, and the Internet of Things (IoT) from the perspective of smart cities in a single volume. The text will be helpful for senior undergraduate, graduate students and academic researchers in diverse engineering fields including electrical, electronics and communication, and computers. The book: Covers the integration of power electronics, energy harvesting, and the IoT for smart city applications. Discusses concepts of power electronics and the IoT in electric vehicles for smart cities. Examines the integration of power electronics in renewable energy for smart cities. Discusses important concepts of energy harvesting including solar energy harvesting, maximum power point tracking (MPPT) controllers, and switch-mode power supplies (SMPS). Explores IoT connectivity technologies such as long-term evolution (LTE), narrow band NB-IoT, long-range (LoRa), Bluetooth, and ZigBee (IEEE Standard 802.15.4) for low data rate wireless personal communication applications. The text provides the knowledge about applications, technologies, and standards of power electronics, renewable energy, and IoT for smart cities. It will serve as an ideal reference text for senior undergraduate, graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, civil engineering, and environmental engineering. |
| fleet management data analytics: IoT Data Analytics using Python M S Hariharan, 2023-10-23 Harness the power of Python to analyze your IoT data KEY FEATURES ● Learn how to build an IoT Data Analytics infrastructure. ● Explore advanced techniques for IoT Data Analysis with Python. ● Gain hands-on experience applying IoT Data Analytics to real-world situations. DESCRIPTION Python is a popular programming language for data analytics, and it is also well-suited for IoT Data Analytics. By leveraging Python's versatility and its rich ecosystem of libraries and tools, Data Analytics for IoT can unlock valuable insights, enable predictive capabilities, and optimize decision-making in various IoT applications and domains. The book begins with a foundation in IoT fundamentals, its role in digital transformation, and why Python is the preferred language for IoT Data Analytics. It then covers essential data analytics concepts, how to establish an IoT Data Analytics environment, and how to design and manage real-time IoT data flows. Next, the book discusses how to implement Descriptive Analytics with Pandas, Time Series Forecasting with Python libraries, and Monitoring, Preventive Maintenance, Optimization, Text Mining, and Automation strategies. It also introduces Edge Computing and Analytics, discusses Continuous and Adaptive Learning concepts, and explores data flow and use cases for Edge Analytics. Finally, the book concludes with a chapter on IoT Data Analytics for self-driving cars, using the CRISP-DM framework for data collection, modeling, and deployment. By the end of the book, you will be equipped with the skills and knowledge needed to extract valuable insights from IoT data and build real-world applications. WHAT YOU WILL LEARN ● Explore the essentials of IoT Data Analytics and the Industry 4.0 revolution. ● Learn how to set up the IoT Data Analytics environment. ● Equip Python developers with data analysis foundations. ● Learn to build data lakes for real-time IoT data streaming. ● Learn to deploy machine learning models on edge devices. ● Understand Edge Computing with MicroPython for efficient IoT Data Analytics. WHO THIS BOOK IS FOR If you are an experienced Python developer who wants to master IoT Data Analytics, or a newcomer who wants to learn Python and its applications in IoT, this book will give you a thorough understanding of IoT Data Analytics and practical skills for real-world use cases. TABLE OF CONTENTS 1. Necessity of Analytics Across IoT 2. Up and Running with Data Analytics Fundamentals 3. Setting Up IoT Analytics Environment 4. Managing Data Pipeline and Cleaning 5. Designing Data Lake and Executing Data Transformation 6. Implementing Descriptive Analytics Using Pandas 7. Time Series Forecasting and Predictions 8. Monitoring and Preventive Maintenance 9. Model Deployment on Edge Devices 10. Understanding Edge Computing with MicroPython 11. IoT Analytics for Self-driving Vehicles |
| fleet management data analytics: Industry 4.0, Smart Manufacturing, and Industrial Engineering Amit Kumar Tyagi, Shrikant Tiwari, Sayed Sayeed Ahmad, 2024-09-16 Industry 4.0 is a revolutionary concept that aims to enhance productivity and profitability in various industries through the implementation of smart manufacturing techniques. This book discusses the profound impact of Industry 4.0, which involves the seamless integration of digital technologies into manufacturing processes within the realm of industrial engineering. Industry 4.0, Smart Manufacturing, and Industrial Engineering: Challenges and Opportunities thoroughly examines the intricate facets of Industry 4.0 and Smart Manufacturing, offering a comprehensive overview of the challenges and opportunities that this paradigm shift presents to industrial engineers. It provides practical insights and strategies to help professionals navigate the complexities of this evolving landscape. Fundamental components of Industry 4.0 and Smart Manufacturing, ranging from the incorporation of sensors and data analytics to the deployment of cyber-physical systems and the promotion of sustainable practices are covered in detail. The book addresses the obstacles and prospects brought about by Industry 4.0 in the digital age and offers solutions to issues such as data security, interoperability, and workforce preparedness. The book sheds light on how Industry 4.0 combines various disciplines, including engineering technology, data science, and management. It serves as a valuable resource for researchers, undergraduate and postgraduate students, as well as professionals operating in the field of industrial engineering and related domains. |
| fleet management data analytics: Big Data Analytics: From Data to Discovery Dr. Sudhakar.K, Mrs.Noor Sumaiya, Mrs.Niveditha.S, Mr.Debarshi Mazumder, 2024-06-12 Dr. Sudhakar.K, Associate Professor, Department of Artificial Intelligence & Data Science, NITTE Meenakshi Institute of Technology, Bangalore, Karnataka, India. Mrs.Noor Sumaiya, Assistant Professor, Department of Computer Science Engineering, The Oxford College of Engineering, Bangalore, Karnataka, India. Mrs.Niveditha.S, Assistant Professor, Department of Information Science & Engineering, Don Bosco Institute of Technology, Bangalore, Karnataka, India. Mr.Debarshi Mazumder, Assistant Professor, Department of Artificial Intelligence & Data Science, NITTE Meenakshi Institute of Technology, Bangalore, Karnataka, India. |
| fleet management data analytics: Distributed, Ambient and Pervasive Interactions: Understanding Humans Norbert Streitz, Shin’ichi Konomi, 2018-07-10 This two volume set constitutes the refereed proceedings of the 6th International Conference on Distributed, Ambient and Pervasive Interactions, DAPI 2018, held as part of the 20th International Conference on Human-Computer Interaction, HCII 2018, held in Las Vegas, NV, USA in July 2018. The total of 1171 papers and 160 posters presented at the 14 colocated HCII 2018 conferences. The papers were carefully reviewed and selected from 4346 submissions. These papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers thoroughly cover the entire field of Human-Computer Interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas.. The LNCS 10921 and LNCS 10922 contains papers addressing the following major topics: Technologies and Contexts ( Part I) and Understanding Humans (Part IΙ) |
| fleet management data analytics: Machine Learning, Optimization, and Data Science Giuseppe Nicosia, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos Pardalos, Giuseppe Di Fatta, Giovanni Giuffrida, Renato Umeton, 2023-03-08 This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications. |
| fleet management data analytics: DSS 2.0 - Supporting Decision Making With New Technologies G.E. Phillips-Wren, S. Carlsson, A. Respício, 2014-05-22 Advances in technology have resulted in new and advanced methods to support decision-making. For example, artificial intelligence has enabled people to make better decisions hrough the use of Intelligent Decision Support Systems (DSS). Emerging research in DSS demonstrates that decision makers can operate in a more timely manner using real-time data, more accurately due to data mining and 'big data' methods, more strategically by considering a greater number of factors, more precisely and inclusively due to the availability of social networking data, and with a wider media reach with video and audio technology._x000D_ _x000D_This book presents the proceedings of the IFIP TC8/Working Group 8.3 conference held at the Université Pierre et Marie Curie in Paris, France, in June 2014. Throughout its history the conference has aimed to present the latest innovations and achievements in Decision Support Systems. This year the conference looks to the next generation with the theme of new technologies to enable DSS2.0. The topics covered include theoretical, empirical and design science research; case-based approaches in decision support systems; decision models in the real-world; healthcare information technology; decision making theory; knowledge management; knowledge and resource discovery; business intelligence; group decision support systems; collaborative decision making; analytics and ‘big data’; rich language for decision support; multimedia tools for DSS; Web 2.0 systems in decision support; context-based technologies for decision making; intelligent systems and technologies in decision support; organizational decision support; research methods in DSS 2.0; mobile DSS; competing on analytics; and social media analytics._x000D_ _x000D_ The book will be of interest to all those who develop or use Decision Support Systems. The variety of methods and applications illustrated by this international group of carefully reviewed papers should provide ideas and directions for future researchers and practitioners alike. |
| fleet management data analytics: Seafaring Stories: The History of Maritime Exploration Rowley N. Howland, 2024-08-01 Embark on an epic journey across the world's oceans with Seafaring Stories: The History of Maritime Exploration. This captivating book delves into the rich and multifaceted history of humanity's relationship with the sea, from ancient mariners navigating uncharted waters to modern-day explorers pushing the boundaries of oceanic research. Discover how maritime exploration, a topic as relevant today as ever, has shaped global trade, influenced cultures, and transformed societies. Through engaging storytelling and meticulous research, Seafaring Stories uncovers the remarkable tales of daring explorers, innovative shipbuilders, and the indomitable human spirit that drove countless voyages into the unknown. Each chapter is a treasure trove of fascinating insights, shedding light on the profound impact of maritime exploration on our world. What you will find in this book: Ancient Mariners: The dawn of seafaring and early navigation techniques. Age of Discovery: The bold voyages that expanded the known world. Asian Naval Empires: The rise and influence of Eastern maritime powers. Golden Age of Sail: The era of conquest and colonization. Industrial Revolution: The transformation of maritime trade with steam and steel. World Wars: The strategic importance of naval power. Cold War: Modern maritime dynamics and superpower rivalries. Blue Economy: Innovations and sustainability in today's maritime industries. Cultural Currents: The cultural impact of maritime exploration. Future Exploration: The next frontier in oceanic discovery. Dive into the compelling narratives of Seafaring Stories and explore how the relentless pursuit of knowledge and adventure on the high seas has shaped our past and continues to influence our future. This book, with its insights into the past and its implications for the present and future, is a must-read for history enthusiasts, maritime buffs, and anyone fascinated by the enduring allure of the ocean. Discover the legacy of maritime exploration and its timeless connection to the human spirit. |
| fleet management data analytics: Are We There Yet? Martin Stewart-Weeks, Simon Cooper, 2019-07-01 Digital transformation across the public sector has stalled. After over 25 years of considerable time, money, and effort at national, state, and local levels, we’re still not 'there' yet. The reason is that successive waves of investment in digital transformation have focused largely on improving the transactional functions and activities of government. They have failed to embrace a bigger challenge - the need for governing and government to rethink a new 'theory of the business' - which that same revolution has caused and to which it is an inescapable part of the answer. This is a unique, timely, and distinctly Australian look at a global phenomenon by two 'reflective practitioners'. Their personal and practical experience of digital transformation in government and the public sector in Australia suggests it is a story missing half its plot. Packed full of insights from government and digital leaders from around Australia and across the world, this is a much-needed practical guide for public servants and leaders in any jurisdiction. It contains insights and ideas about the way digital technologies, and their associated tools, platforms, and cultures, are changing the business of governing and the design and delivery of public policy and services. Are We There Yet? lucidly diagnoses how digital technologies, including AI and big data, are transforming the role of the public servant and the project of governance itself. Stewart-Weeks and Cooper describe the important shift from power to problem-solving and explain how to harness digital transformation to make government work better for all of us.” - Beth Noveck, author of Wiki Government, former Deputy Chief Technology Officer in the Obama White House, Professor in Technology, Culture & Society, New York University and Chief Innovation Officer for New Jersey I've read a lot about the potential impact of digital technology on public services … this is the first book to persuade me that the power of digital, properly conceived, really can transform the nature of democratic governance. - Professor Peter Shergold AC, Chancellor, Western Sydney University, Former Secretary, Department of Prime Minister and Cabinet |
| fleet management data analytics: The Big Data-Driven Digital Economy: Artificial and Computational Intelligence Abdalmuttaleb M. A. Musleh Al-Sartawi, 2021-05-28 This book shows digital economy has become one of the most sought out solutions to sustainable development and economic growth of nations. This book discusses the implications of both artificial intelligence and computational intelligence in the digital economy providing a holistic view on AI education, economics, finance, sustainability, ethics, governance, cybersecurity, blockchain, and knowledge management. Unlike other books, this book brings together two important areas, intelligence systems and big data in the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations. The chapters hereby focus on how societies can take advantage and manage data, as well as the limitations they face due to the complexity of resources in the form of digital data and the intelligence which will support economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, students, economic development strategies, and the efforts made by the UN towards achieving their sustainability goals. |
| fleet management data analytics: Big Data Analysis: New Algorithms for a New Society Nathalie Japkowicz, Jerzy Stefanowski, 2015-12-16 This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges. |
| fleet management data analytics: THE DEFINITIVE GUIDE TO B2B DIGITAL TRANSFORMATION Fred Geyer, Joerg Niessing, 2020-05-26 This book guides B2B leaders along a step by step path to uncommon growth through three transformative shifts: The Digital Selling Shift to digital demand generation, The Digital Customer Experience Makeover to digital customer engagement, The Digital Proposition Pivot to data-powered, digital solutions. The Definitive Guide is informed by the work of Fred Geyer at Prophet, a leading digital transformation consultancy, and Joerg Niessing at INSEAD, a global standard-bearer for business education. Rich case studies from Maersk, Michelin, Adobe, and Air Liquide with best practices from IBM, Salesforce.com, Thyssenkrupp, and scores of leading B2B companies illustrate how putting customers at the heart of digital transformation drives uncommon growth. Fred and Joerg map the route from customer insight to in-market implementation for each transformational shift in four steps: Where to Play - Identify top customer growth opportunities, How to Win - Build the strategy to win customer preference, What to Do - Effectively deliver the strategy, Who is Needed - Assemble the team to make it happen. The two biggest barriers to successful digital transformation, effectively using customer data and enabling employees, are addressed by outlining a clear path to navigate forward based on best practices from other leading companies. The guide has won rave reviews from B2B leaders: This book illuminates the secret sauce of digital transformation in the B2B space – David Aaker, renowned brand strategist and bestselling author. A thought-provoking exploration of three crucial transformational shifts for B2B companies – Vincent Clerc, CEO, Maersk Ocean & Logistics This is a great guide to applying best practices to the formidable challenge of digital transformation in complex markets and supply chains. – Dr. Lars Brzoska, Chairman of the Board of Management, Jungheinrich AG. By providing case examples and step by step assistance in determining where to play, how to win, what to do and who to win, this book fulfilled my need for inspiring and pragmatic transformation guidance – Lindy Hood, Chief Customer Experience Officer, Zurich Financial North America |
如何看待 JetBrains 推出的轻量级编辑器 Fleet？ - 知乎
期待未来 Android Studio 也会基于 Fleet 吧。其实 JB 自己想收费无可厚非，反正 Android 开发这部分永远是免费的，那就无所谓了。 补充： VSC 这个怎么说呢，什么都能做，但什么都不是做得最好的 …
jetbrains fleet怎么设置为中文? - 知乎
要在 JetBrains Fleet 中设置中文界面，以下是步骤： 1.首先，你需要安装 JetBrains Fleet。对于Windows和macOS系统的用户， installation程序会自动检测你的语言设置。 2. 在开始菜单中找到 …
fleet 相比 vscode 有什么优势？ - 知乎
Fleet 简单体验了一下。其实优缺点就这么几个。 优点. 页面设计的更现代，加了一些圆角设计，会比 VSCode 默认的页面好看很多; 提供和 VSCode 非常相似的插件系统，但大部分功能都有官方集成。 …
如何看待 JetBrains 推出的轻量级编辑器 Fleet？ - 知乎
Fleet 中 C++ 好歹还是有 Smart Mode 的，很多语言连 Smart Mode 都还没有，然而插件功能至今遥遥无期。 JetBrains 自己不愿意给 Fleet 做好各种语言的支持、开发更多语言的支持，也没给其他有能 …
有问题，就会有答案 - 知乎
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业、友善的社区 …
如何评价Jetbrains Fleet Public Preview? - 知乎
如何评价Jetbrains Fleet Public Preview? - 知乎
2025年6月PyCharm和VSCode哪个更好用？ - 知乎
PyCharm：内置AI补全和调试，JetBrains Fleet（实验性轻量编辑器）也在探索更智能的开发体验。 VSCode：Copilot直接起飞，2024年你还能嵌入个人专属AI，实时生成、优化代码。 结论：需要AI …
对于被 JetBrains 系 IDE 惯坏了的学生，如果不得不放弃使用，有 …
剩下的什么 zed、fleet 还是半成品, emacs 中文资料少估计也折腾不明白, 还是算了吧 差点忘了, 还有俩纯粹的编辑器, mac 上的 textmate 和 win 上的 notepad++ 展开阅读全文
各位大佬请教一下，为什么pycharm添加不了conda创建的环境？
原文. Q Sir：解决pycharm中添加conda environment 问题. 针对有些pycharm使用爱好者，添加python interpreter时，想通过conda environment 来添加，结果发现conda environment 中显示conda …
如何在默认打开方式设置中去掉已失效\已删除的应用选项？ - 知乎
是上面的这个问题么? 计算机\HKEY_USERS\S-1-5-21-4024916612-1691460616-483768494-1001\Software\Classes\Applications
如何看待 JetBrains 推出的轻量级编辑器 Fleet？ - 知乎
期待未来 Android Studio 也会基于 Fleet 吧。其实 JB 自己想收费无可厚非，反正 Android 开发这部分永远是免费的，那就无所谓了。 补充： VSC 这个怎么说呢，什么都能做，但什么都不是做得最好的 …
jetbrains fleet怎么设置为中文? - 知乎
要在 JetBrains Fleet 中设置中文界面，以下是步骤： 1.首先，你需要安装 JetBrains Fleet。对于Windows和macOS系统的用户， installation程序会自动检测你的语言设置。 2. 在开始菜单中找到 …
fleet 相比 vscode 有什么优势？ - 知乎
Fleet 简单体验了一下。其实优缺点就这么几个。 优点. 页面设计的更现代，加了一些圆角设计，会比 VSCode 默认的页面好看很多; 提供和 VSCode 非常相似的插件系统，但大部分功能都有官方集成。 …
如何看待 JetBrains 推出的轻量级编辑器 Fleet？ - 知乎
Fleet 中 C++ 好歹还是有 Smart Mode 的，很多语言连 Smart Mode 都还没有，然而插件功能至今遥遥无期。 JetBrains 自己不愿意给 Fleet 做好各种语言的支持、开发更多语言的支持，也没给其他有能 …
有问题，就会有答案 - 知乎
知乎，中文互联网高质量的问答社区和创作者聚集的原创内容平台，于 2011 年 1 月正式上线，以「让人们更好的分享知识、经验和见解，找到自己的解答」为品牌使命。知乎凭借认真、专业、友善的社区 …
如何评价Jetbrains Fleet Public Preview? - 知乎
如何评价Jetbrains Fleet Public Preview? - 知乎
2025年6月PyCharm和VSCode哪个更好用？ - 知乎
PyCharm：内置AI补全和调试，JetBrains Fleet（实验性轻量编辑器）也在探索更智能的开发体验。 VSCode：Copilot直接起飞，2024年你还能嵌入个人专属AI，实时生成、优化代码。 结论：需要AI …
对于被 JetBrains 系 IDE 惯坏了的学生，如果不得不放弃使用，有 …
剩下的什么 zed、fleet 还是半成品, emacs 中文资料少估计也折腾不明白, 还是算了吧 差点忘了, 还有俩纯粹的编辑器, mac 上的 textmate 和 win 上的 notepad++ 展开阅读全文
各位大佬请教一下，为什么pycharm添加不了conda创建的环境？
原文. Q Sir：解决pycharm中添加conda environment 问题. 针对有些pycharm使用爱好者，添加python interpreter时，想通过conda environment 来添加，结果发现conda environment 中显示conda …
如何在默认打开方式设置中去掉已失效\已删除的应用选项？ - 知乎
是上面的这个问题么? 计算机\HKEY_USERS\S-1-5-21-4024916612-1691460616-483768494-1001\Software\Classes\Applications
