Smart Suggestions - Part I

Transcript

1. Driver navigation systems for last-mile
   shipping efficiency
   Mid-term Presentation | Sricharan Chiruvolu | BL.EN.U4CSE12505
   

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2. Company Overview
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3. • Hyper-local logistics service.
   • One of the largest fleet of delivery drivers.
   • Merchant and driver platforms.
   • B2B. Food, Groceries…11 others.
   • 25000 orders a day.
   • McDonalds, Pizza Hut, KFC…4000 others.
   • Tech Stack: Rails, MySql, MongoDb, Redis,
   Angular, Android, Scala, NodeJS and Django.
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4. Tasks and Projects
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5. Tasks and Projects
   1. Driver reassignment by merchants for a live order.
   2. Driver navigation to last-mile customer location.
   3. Smart suggest for drivers.
   4. Order stockout analytics fixes. (End-term presentation)
   5. Cross locality preferences analytics. (End-term presentation)
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6. Driver Reassignment
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7. Driver Reassignment
   • Add an option for the merchant to reassign the driver for
   an order during cancellation.
   • Decrease the number of cancellations.
   • Assign to the next nearest free driver.
   • Reasons for reassignment:
   1. Delivery driver refused to come.
   2. Driver didn't come for a long time.
   • Reassignment workflow.
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8. start
   stop
   Reassign Order?
   active_leg?
   &&
   next_driver_available?
   &&
   correct_cancellation_reason?
   Cancel Order
   Order reassign to next free driver
   active_leg?
   Cancel Order?
   Error Message
   No No
   Yes Yes
   

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9. Driver Navigation to Customer
   Location
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10. Driver Navigation
    • Last mile navigation.
    • Capture customer location.
    • Send customer location for a live trip.
    • MQTT(MQ Telemetry Transport) and GCM (Google
    Cloud Messaging) protocols.
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11. Last-mile navigation
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12. MQTT activity at Runnr
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13. Smart suggest
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14. Smart suggestions
    • Demand - supply gaps in localities.
    • Demand prediction and supply input.
    • Calculating demand and supply percentile.
    • Surge pricing prerequisite.
    • Driver application and operations dashboard
    views.
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15. Smart suggest on operations dashboard
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16. Smart suggest on driver application
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17. Smart suggest on driver application (offline flow)
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18. Next…
    • Stockout data fixes:
    • Find stockout orders and predict stockout
    quotient.
    • Cross-locality orders:
    • Cost prediction (machine learning)
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19. Thank you.
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    NAME
    SRICHARAN
    (BL.EN.U4CSE12505)
    EXT. GUIDE
    Mr. MUKUNDA & Mr. MOHIT
    AGARWAL
    INT. GUIDE Ms. SANGITA KHARE
    

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