Description
Handbook of Mobility Data Mining: Volume Three: Mobility Data-Driven Applications introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. The book contains crucial information for researchers, engineers, operators, administrators, and policymakers seeking greater understanding of current technologies' infra-knowledge structure and limitations.The book introduces how to design MDM platforms that adapt to the evolving mobility environment—and new types of transportation and users—based on an integrated solution that utilizes sensing and communication capabilities to tackle significant challenges faced by the MDM field. This third volume looks at various cases studies to illustrate and explore the methods introduced in the first two volumes, covering topics such as Intelligent Transportation Management, Smart Emergency Management—detailing cases such as the Fukushima earthquake, Hurricane Katrina, and COVID-19—and Urban Sustainability Development, covering bicycle and railway travel behavior, mobility inequality, and road and light pollution inequality.- Introduces MDM applications from six major areas: intelligent transportation management, shared transportation systems, disaster management, pandemic response, low-carbon transportation, and social equality- Uses case studies to examine possible solutions that facilitate ethical, secure, and controlled emergency management based on mobile big data- Helps develop policy innovations beneficial to citizens, businesses, and society- Stems from the editor's strong network of global transport authorities and transport companies, providing a solid knowledge structure and data foundation as well as geographical and stakeholder coverage
Table of Contents
Part I: Intelligent Transportation Management1. Mobile Big Data in Dynamic Road Pricing System2. Mobile Big Data in P2P Bidding System for Transportation Services3. Mobile Big Data in Bicycle-sharing System4. Mobile Big Data in Ride-sharing System5. Mobile Big Data in Customized Bus SystemPart II: Smart Emergency Management6. Mobile Big Data in Disaster Migration detection7. Mobile Big Data in Disaster Relief Detection8. Mobile Big Data in Social Close Contact Detection9. Mobile Big Data in Pandemic Simulation10. Mobile Big Data in Pandemic PredictionPart III: Urban Sustainability Development11. Mobile Big Data in Bicycle Travel Behaviour12. Mobile Big Data in Railway Travel Behaviour13. Mobile Big Data in Mobility Inequality14. Mobile Big Data in Road Pollution Inequality15. Mobile Big Data in Light Pollution Inequality
