Leveraging Big Data Platform Technologies and Analytics to Enhance Smart City Mobility Services
| Autor: | Ying Qian, Robin G. Qiu, Tianhai Zu, Lawrence Qiu, Youakim Badr |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
010504 meteorology & atmospheric sciences
Computer science business.industry Big data 020206 networking & telecommunications 02 engineering and technology computer.software_genre 01 natural sciences Data science Digital ecosystem Analytics Smart city 0202 electrical engineering electronic engineering information engineering Data analysis Real-time data business Mobility management computer 0105 earth and related environmental sciences Data integration |
| Zdroj: | Handbook of Service Science, Volume II ISBN: 9783319985114 |
| DOI: | 10.1007/978-3-319-98512-1_25 |
| Popis: | The Internet of Things (IoT) allows objects to be sensed and managed over networks, creating opportunities for beneficial interactions and integration between the physical world, computer-based systems, and human beings. The recently enabled people-centric sensing or social sensing transforms how we sense and interact with the world. For instance, social sensing via mobile apps complements physical sensing (e.g., IoT) by substantially extending the horizon we know about our living communities and environments in real time. This chapter presents how we can integrate physical and social sensing to enable better and smarter services in great detail. With the support of big data technologies, we use city mobility services to demonstrate the great potential of the proposed data integration and aggregation. Specifically, real time data from Citi Bike and Twitter.com are collected, processed, and modelled. The developed prototype in support of city mobility management and operations shows numerous potential benefits of the proposed digital ecosystem platform. |
| Databáze: | OpenAIRE |
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