Dynamic Pricing of Parking Charges

Vishal Lakha | Apr 3, 2020
Dynamic Pricing of Parking Charges

Objective

Provide a suggestion to select the optimal pricing tiers based on demand in a parking lot.

Description

Data Flow
II have trained a machine learning model using Prophet (Generalized Additive Model) which predicts the occupancy percent of a parking lot for next 3 hours. this forecast is used to derive the selection of optimal pricing tier based on given options.

Based on the forecast, the Parking lot administrator would receive a pop notification on his dashboard about the recommendation to change the pricing due to predicted change in the parking lot utilization.

 

solution

 

Technology Stack

Python, Prophet, Time Series, MQTT, SQL

Click Here to see the code. This is not the full code, but just a module representation

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