University of Cambridge > Talks.cam > Computer Laboratory Systems Research Group Seminar >  Spatio-Temporal Data Collection and Analysis for Developing Transport related Services

Spatio-Temporal Data Collection and Analysis for Developing Transport related Services

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Srinivasan Keshav.

In this seminar, I will be talking about my PhD thesis at a broad level. In this era of connected systems that have penetrated everywhere, transport units have become a significant source of data, collected from commuters, vehicles, drivers, or any section being touched by the transport system. This data, which has both spatial as well as temporal aspects, is utilized for a plethora of services like travel assistant systems, multi-modal transport solutions, real-time travel information, smart parking, autonomous vehicles, to name a few. With the current buzz of sustainable transport, the use of public transport systems has been popularized owing to the economic and environmental savings. The popularity of ride-hailing options like Uber/Lyft has been diminishing the use of public transport; however, this cheaper alternative is still preferred by the majority population. In light of the prevailing scenario, we will look into the problems linked to public transport units as well as ride-hailing firms. Commuters and drivers being essential parts of the transport system, we emphasize addressing the problems from each of their perspectives — commuters in public transport and drivers in ride-hailing options. I will discuss systems leveraging over the vast pool of spatio-temporal data that could be obtained from different transport units. The first class of these systems would help to improve the travel experience of commuters in public transport. While the second class of systems would establish a relationship between driver stress and driving behavior of drivers in ride-hailing firms, thus helping reduce the chances of possible accidents.

Bio: Rohit Verma joined as a Postdoctoral Researcher at the Computer Lab in February 2020. He received his B.Tech (Computer Science and Engineering) degree from the National Institute of Technology, Durgapur, India. He then worked at Schneider Electric India as an SDE till 2015, before joining PhD at the Indian Institute of Technology, Kharagpur (2016-2019) where he was a TCS Research Fellow. His research has been in the field of sensor data collection and analysis obtained from multi-modal sources. In his PhD he had been utilizing such information towards developing systems supporting transportation units.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2020 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity