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Growing of smart IoT has generated many major impacts on transportation development, of which one underlying big story is the thriving of big data driven smart transportation nowadays. We are moving from IT to data technology (DT) time, and we are entering a “results driven” era in transportation. As the front and center of the smart IoT transformed mobility, transportation data sets grow rapidly while they are increasingly gathered from more connected sensors, devices, actuators in real-world applications. In 2016, over 823.0 million air trip passengers were reported by U.S. airlines and over 25 million public transit trips was generated daily.
The data traffic associated with mobility and transportation is estimated to be roughly 0.6 exabytes every month by 2020 (about 9 percent of total US wireless data traffic), and will grow to 9.4 exabytes every month by 2030. Although the quantity of the data available is indeed large, that is not the most striking characteristic of “big data” in the smart IoT era concerning transportation. The challenge in big data driven transportation rarely refers to the large volume or size of data; rather, it often refers to extracting value from data with certain innovative methods, i.e. how to analyze the data and to gather meaningful insights that can be used to inform decisions makers.
Many concurrent novel technologies and employments have emerged within the big data driven smart mobility ecosystem, emanating from the transportation needs of different stakeholders for better safety, reliability, sustainability, and automation.
For public transportation, big data analytics have transformed both the plan and operations phases on planning and demand modeling, predictive maintenance, and event response. New big data tech-savvy has brought more personalized services to public transportation users, such as offering ancillary services to providing recommendations about additional destinations to visit as part of an upgrade to the passenger’s journey, etc.
The big data driven smart public transportation influences both automated and human decision-making, which has clearly played a big part in re-energizing public transport network, and has offered plenty of opportunities to improve the public transportation experience with improved reliability and safety.
Learn more / En savoir plus / Mehr erfahren:
https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data..
Growing of smart IoT has generated many major impacts on transportation development, of which one underlying big story is the thriving of big data driven smart transportation nowadays. We are moving from IT to data technology (DT) time, and we are entering a “results driven” era in transportation. As the front and center of the smart IoT transformed mobility, transportation data sets grow rapidly while they are increasingly gathered from more connected sensors, devices, actuators in real-world applications. In 2016, over 823.0 million air trip passengers were reported by U.S. airlines and over 25 million public transit trips was generated daily.
The data traffic associated with mobility and transportation is estimated to be roughly 0.6 exabytes every month by 2020 (about 9 percent of total US wireless data traffic), and will grow to 9.4 exabytes every month by 2030. Although the quantity of the data available is indeed large, that is not the most striking characteristic of “big data” in the smart IoT era concerning transportation. The challenge in big data driven transportation rarely refers to the large volume or size of data; rather, it often refers to extracting value from data with certain innovative methods, i.e. how to analyze the data and to gather meaningful insights that can be used to inform decisions makers.
Many concurrent novel technologies and employments have emerged within the big data driven smart mobility ecosystem, emanating from the transportation needs of different stakeholders for better safety, reliability, sustainability, and automation.
For public transportation, big data analytics have transformed both the plan and operations phases on planning and demand modeling, predictive maintenance, and event response. New big data tech-savvy has brought more personalized services to public transportation users, such as offering ancillary services to providing recommendations about additional destinations to visit as part of an upgrade to the passenger’s journey, etc.
The big data driven smart public transportation influences both automated and human decision-making, which has clearly played a big part in re-energizing public transport network, and has offered plenty of opportunities to improve the public transportation experience with improved reliability and safety.
Learn more / En savoir plus / Mehr erfahren:
https://www.scoop.it/t/21st-century-learning-and-teaching/?&tag=Big+Data..