A better parking infrastructure is essential in a developing country like Bangladesh where both the population and the number of vehicles are rapidly increasing. The number of vehicles in use is rising swiftly, but there aren't enough parking spaces to accommodate all of them, which forces drivers to park their cars on the streets, which leads to significant congestion on the roads and slow traffic growth. Even if searching for parking spaces takes a lot of time, searching unannouncedly has a negative influence on the environment due to the release of terrible and toxic gases from moving vehicles. By burning fuel, this discharge pollutes the atmosphere by emitting different gases as well as CO2. Additionally, traffic slows down as people look for parking spaces. To tackle the above-mentioned limitation, this research propose a new car parking method based on UWB technology. This research also covered the idea of pattern classifiers. The apriori algorithm is used to build frequent rules for cars that are regularly parked, and the system then uses those rules to automatically assign parking slot for the cars. The user can find parking without wasting time by using apriori. This research experimental result shows that the proposed system needs less searching time when compared with the existing system. Basically, this system addressed how to improve the existing system with the new dimension of technology like how to switch automated parking to smart parking, add advanced booking facility etc.

Apriori; UWB; Internet of Things; Parking Lot; RFID; Frequent rule