Intelligent Parking System via Big Data analytics

Universität Ulm

BA Abschlussvortrag, Lars Eckel, Ort: Online, Datum: 26.11.2020, Zeit: 12:30 Uhr

Finding a parking space for a car is getting a more and more difficult task in modern societies. One of the reasons for this is the the increasing amount of cars in the last decades. For example, 14,554 more cars were registered in Munich, Germany in 2019 compared to 2018. Another reason is the reclaiming of streets into bicycle streets or pedestrian zones. Many cities focus solely on off-street solutions as parking areas to counter these effects. But on the other hand they often neglect on-street parking solutions due to their high complexity in management. Therefore, many companies and organizations created new approaches with installing hardware near the parking lot or they try to use algorithms to predict the availability of them. The goal of this thesis is to further improve the efficiency of on-street parking. The research question of this thesis is asked in the following: Is it possible to create and implement an intelligent parking system for on-street parking without installing hardware on or near the parking lots? To answer this research question, a new idea is introduced which is based on servers containing the parking lot data combined with integrated software on the entertainment system. The idea is described via creating a general concept and thereof showing an implementation example to increase the understandability of the idea. The thesis provides a new approach which can increase the efficiency of on-street parking in the future. On this basis, further research has to be done towards testing in real life scenarios.