use of technology in managing support infrastructure
TRANSCRIPT
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BIG DATA IN PUBLIC TRANSPORT
Jaspal SinghUITP India Office
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WHAT IS ITS??Automatic
Vehicle Location System
Passenger Information
System
Automatic Fare Collection
System
Journey Planner Depot
Management System
Fuel Management
System
Financial Management
Bus Management
System
Smart Phone App
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BIG DATA IS..
a term that describes the large volume of data – both structured and unstructured – that inundates a
business on a day-to-day basis
But it's not the amount of data that's important. It's what organizations do with
the data that matters.
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DATA AND TRANSPORT
Open Data – Information that the agencies make freely available to power travel information apps and other tools
Big Data – The analysis of one or more large data sets to reveal patterns or trends and enable action to be taken
Data is emerging as game changer for transport industry
Data Mining - is a collection of techniques for efficient automated discovery of previously unknown, valid, novel, useful and understandable patterns in large databases. The patterns must be actionable so they may be used in decision making.
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WHO SHOULD USE BIG DATA??
Private Operator(Net Cost)
Private Operator
(Gross Cost)
Public Operator
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DATA IS IMPORTANT FOR ALL…
Private Operator(Net Cost)
Private Operator
(Gross Cost)
Public Operator
• To increase Revenue
• To reduce Cost
• To reduce Cost• To minimize Penalty
• To improve efficiency
• To reduce cost
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SOURCE OF BIG DATA
Transport Assets
Vehicle Location Data
Fare Collection Data
Traffic Information
Customers / Users
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USE OF BIG DATA
• Information related to status and performance of transport systems help to improve efficiency, safety and accessibility
• Data from vehicles, trains, roads etc. helps to plan, design, maintain and invest more effectively
• Data on travel patterns/behaviour enables informed choices in real-time for customers
• Analyse and predict the demand of service in future
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CASE STUDY – DELHI CLUSTER SCHEME
• Transport Department introduced Delhi Cluster Scheme to corporatize the bus sector
• There are 6 players which are operating 9 clusters in Delhi
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CASE STUDY – DELHI CLUSTER SCHEME
• Delhi has one of the best contracting model in India, as the operational and fleet efficiency is good compared to public operator
• All buses are equipped with GPS / GPRS and online ETM machines
• DIMTS is using data analytics and bus management system to monitor the operation Still Operators are losing around 6-10% of
total revenue towards Performance Deduction
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CASE STUDY – DELHI CLUSTER SCHEME
Out of 6 players, only one operator is using ERP / MIS system but without analytics
Operators feel that there is minimal need of analysis under Gross Cost System as revenue
is fixed…
Operators receive (vehicle location) and generate (operation) data but don’t use it…
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CASE STUDY - LONDONTfL is collecting large amount of data
everyday..
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LONDON – MANAGING CONGESTION
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LONDON – CUSTOMER SEGMENTATION
TfL uses data to build customer segmentation to understand and plan ticket facilities, signage and
commercial offering
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