A Dynamic Pricing System For E-Scooter Based On Demand Prediction Using Neural Network

  • M.S Antony Vigil


Due To The Rise Of Pollution In Our Environment, There Is An Increase In The Demand For Recyclable Vehicles, Which Help In Controlling Pollution. To Make The Environment Pollution-Free And To Provide A Convenient Mode Of Transport To The People, We Have Introduced A Suitable Method For Usage Of E-Scooters. The Demand For E-Scooters At Each Dock On Different Day’s And Time Is Predicted Using Neural Networking And Managed Using A Dynamic Pricing System. With The Help Of Dynamic Pricing, The Supply Of E-Scooters At Each Dock Can Be Well Managed By Charging The Price Of E-Scooters According To Its Requirement. The Proposed System Concentrates On The Advanced Prediction Of The Demand Over The E-Scooters Using Which Pricing Is Done Dynamically. Since The Spatio-Temporal And Other External Factors Influence The Usage Of E-Scooter In Each Geographical Location. The Neural Network Is Used To Gain Sufficient Information From The Pre-Existing Data Set. As A Result, The Demand For The E-Scooters At Each Location Is Predicted Hence The Pricing Can Be Done Dynamically.