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Processing Sensor Data
From Online Learning June 27, 2017
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Autonomous systems need to process large volumes of data which can arrive from multiple, diverse sensors such as RADAR, LIDAR and cameras. In this video, Dr Lyudmila Mihaylova explains how her research is tackling this challenge, by developing intelligent algorithms that can extract meaningful information from these large data sets.
Lyudmila also discusses her research with the SETA consortium, which is helping to change the way that mobility is organised, monitored and planned in large metropolitan areas. By collecting and processing dynamic data from people, cars, city sensors and distributed databases, this project hopes to inform decision makers on how to improve town planning and infrastructure, as well as allowing individuals to plan their journeys in a more efficient and sustainable way.
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Lyudmila also discusses her research with the SETA consortium, which is helping to change the way that mobility is organised, monitored and planned in large metropolitan areas. By collecting and processing dynamic data from people, cars, city sensors and distributed databases, this project hopes to inform decision makers on how to improve town planning and infrastructure, as well as allowing individuals to plan their journeys in a more efficient and sustainable way.
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