Designing, Implementing, and Testing Smart Cities Use Cases concerning practical Internet of Things Applications

Abstract

Porsgrunn Kommune faced several challenges related to traffic management and parking efficiency. The existing systems needed more real-time monitoring capabilities, making it challenging to assess traffic conditions accurately. Additionally, the lack of an intelligent parking system resulted in inefficient parking utilization, increased search time for parking spaces, and congestion in parking areas. These challenges led to frustrated commuters, traffic congestion, and suboptimal use of urban space.

To address these issues, the thesis project focused on developing an image recognition-based traffic monitoring system and a smart vehicle parking system. The image recognition traffic monitoring system utilizes cameras and advanced algorithms to detect and classify vehicles in real time, providing accurate traffic data for better decision-making. The smart parking system uses image recognition technology to automate the identification of available parking spaces, enabling drivers to locate vacant spots and reducing congestion quickly. By implementing these systems, Porsgrunn Kommune can overcome the challenges of inefficient traffic management and parking utilization. The image recognition-based solutions offer real-time monitoring, data analysis, and enhanced convenience to improve the overall transportation experience and create a more efficient and sustainable urban environment.