This paper explores various types of parking slots and the detection technologies used in smart parking systems. It categorizes detection technologies into sensor-based and vision-based methods, highlighting their respective advantages and limitations. Sensor-based approaches, including ultrasonic, infrared, magnetic, and RFID sensors, provide real-time occupancy updates. Vision-based methods leverage machine learning, deep learning, and image processing for accurate parking detection. IoT and AI combination enhances the efficiency and effectiveness of smart parking systems. Though technology has improved, environmental conditions, sensor accuracy, and computation requirements are the challenges that remain. Future studies need to address enhancing detection accuracy, lowering the costs, and employing 5G and edge computing for real-time computation. This review wants to inform researchers and urban planners about the deployment of advanced parking management technologies to make smart cities, ultimately decreasing congestion and enhancing traffic flow.