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SUMMARY: Spatio-Temporal Data Collection and Analysis for Developing Trans
 port related Services - Rohit Verma (Computer Lab)
DTSTART:20200521T140000Z
DTEND:20200521T150000Z
UID:TALK140035@talks.cam.ac.uk
CONTACT:Srinivasan Keshav
DESCRIPTION:In this seminar\, I will be talking about my PhD thesis at a b
 road level. In this era of connected systems that have penetrated everywhe
 re\, 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 a
 spects\, is utilized for a plethora of services like travel assistant syst
 ems\, multi-modal transport solutions\, real-time travel information\, sma
 rt parking\, autonomous vehicles\, to name a few. With the current buzz of
  sustainable transport\, the use of public transport systems has been popu
 larized owing to the economic and environmental savings. The popularity of
  ride-hailing options like Uber/Lyft has been diminishing the use of publi
 c 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 syste
 m\, we emphasize addressing the problems from each of their perspectives 
 — commuters in public transport and drivers in ride-hailing options. I w
 ill 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 rela
 tionship between driver stress and driving behavior of drivers in ride-hai
 ling firms\, thus helping reduce the chances of possible accidents.\n\n*Bi
 o*: 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 t
 hen worked at Schneider Electric India as an SDE till 2015\, before joinin
 g 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 Ph
 D he had been utilizing such information towards developing systems suppor
 ting transportation units. 
LOCATION:Webex Meeting number: 140 388 203 Password: ZApmfTb7h56 https://m
 eetingsemea10.webex.com/meetingsemea10/j.php?MTID=mf0c350ff1fab96540218f57
 67c51d098
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