Approach for simulating vehicle-based supply of sellable data products in smart cities – Parking space data as a use case

Abstract

Mobile devices, sensors, 5G networks, digital platforms and data marketplaces provide emerging possibilities for smart cities and data business. This paper introduces a novel Data Market Simulation (DMS) approach that assists data suppliers in the following: optimising vehicle-based supply of sellable data and creation of value from data; evaluating vehicle routes and the quality of data that the vehicles on these routes will produce; and reviewing how well the routes will serve the potential data users before beginning the supply of data in cities. The DMS approach supports iterative development and optimisation of routes and route parameters. If the goals are not achieved in the route plan, the data user can use the previous simulation results as a start point, develop the routes and route parameters in the simulation model, and then evaluate the updated route plan in simulations. The route development and simulation can be continued until the desired targets are met in the route plan. The DMS approach is evaluated in a small-scale experiment that simulated the use of autonomous busses and drones for the supply of parking space data in the LuxTurrim5G+’s smart pole pilot network in the city of Espoo in Finland.

Keywords

• Simulation
• Data business
• Data economy
• Sellable data product
• Autonomous vehicle
• Smart city