Data is becoming increasingly significant in the management and use of transport systems. Across all modes of transport, there is now a considerable quantity and diversity of data available for operators to improve performance, efficiency, service provision, safety and security. This Insight by Matthew Clarke at ATKINS Transportation explores Big Data management, best practice and challenges.
The trend to larger data sets is a result of the plethora of information that can now be derived from the analysis of a single data set. Increasingly, data is being gathered by information-sensing mobile devices, remote sensing, software logs, cameras, microphones and wireless sensor networks. In transport, the increase in data is manifested in the availability of traffic information, particularly through sat nav applications. Similar passenger information applications provide departure information for public transport users. Payment for transport (ticketing and tolling) is increasingly reliant on data-dependent technology, applications and services.
Global technological information per-capita capacity has approximately doubled every 40 months since the 1980s. Predictions show that data production will be 44 times greater in 2020 than it was in 2009. Data sets are becoming so large and complex that they become difficult to process using traditional data processing applications and existing data management tools. As a result, capturing, storing, searching, sharing, transferring and analysing the data sets can be a significant challenge.
This Insight by Matthew Clarke at ATKINS Transportation explores Big Data management, best practice and considers the challenges and developments ahead for those responsible for Big Data in a transport environment. It will enable the reader to gain a better understanding of the opportunity and value of data sets, and their impact on a future society through the internet of things.
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