The rapid urbanization and increasing vehicle ownership in urban areas have led to significant challenges in parking management, contributing to traffic congestion, pollution, and inefficient use of urban space. This study explores the integration of global navigation satellite systems (GNSS) and Internet of Things (IoT) technologies to develop a smart parking (SP) concept tailored for urban environments. The proposed idea leverages GNSS for real-time vehicle positioning and IoT-enabled sensors for monitoring parking space availability. By combining these technologies, the concept provides drivers with accurate, real-time information on available parking spots, reducing the time spent searching for parking and minimizing traffic congestion. The study discusses the architecture of the SP concept, including the deployment of IoT sensors, data communication protocols, and user interface design. Additionally, the concept of intelligent parking demonstrates the potential of GNSS- and IoT-assisted SPs to enhance urban mobility, reduce environmental impact, and improve the overall quality of life in cities. It addresses also the challenges of scalability, data security, and integration with existing urban infrastructure. The study concludes with future research directions and recommendations for policymakers and urban planners to adopt and implement SP solutions effectively for future parking management, traffic optimization, and integration with smart city concept coming into existence in the near future not only in developed countries but also in developing countries. Space technology development at country level is highly needed especially in developing countries to deal with cities’ problems such as traffic jams caused by lack of effective parking, poor road networks, increased number of vehicles, as well as flooding due to lack of several technologies including spatial technologies of constructing modern drainage water channels to drain unwanted water in designed location and space technology from satellites to share updated climate real-time data used in early warning systems and development of flooding management mechanisms before the incident occur.