Andreas Georgiou, Marina Sofokleous, Christos Laoudias, Aristotelis Savva, Christos G. Panayiotou

To improve mobility, enhance public services, and align with EU regulations, the Ministry of Transport, Communications, and Works of Cyprus (MTCW) is introducing Intelligent Transport Systems (ITS) across the island. In collaboration with the KIOS Research and Innovation Centre of Excellence at the University of Cyprus (KIOS CoE), the MTCW is planning the deployment of ITS using evidence-based scientific results produced by KIOS CoE and aggregated from existing literature.
As part of this initiative, an integrated Geographical Information System (GIS)-based ecosystem, called GNOSIS, has been developed to streamline mobility data collection, analysis, management, and dissemination. GNOSIS integrates advanced GIS technologies to provide a user-friendly platform for data-driven transport planning and decision-making. The ecosystem consists of three key components: a Desktop Application built on a customized version of QGIS that offers several functionalities that enhance the everyday workflow of end-users in data management, analysis, and visualization; a Mobile Application designed to support data collection and fieldwork that enables users to gather essential information in real-time and; a Web Portal that provides remote access to visual data, allowing users to view and interact with transport data from anywhere. These components, support the Cyprus National Access Point (CyNAP), facilitating the easy exchange, access, and reuse of transport-related data.
One objective of this work is to showcase the GIS ecosystem developed for ITS and demonstrate how open-source components can be effectively integrated to deliver a comprehensive and efficient solution for digital transformation and sustainability of mobility services. Another objective is to highlight the role of such solutions in enhancing the productivity and accountability of public services. Ultimately, this initiative lays the foundation for the Cyprus Transport Networks Digital Twin, enabling more accurate simulations, smarter infrastructure planning, and improved transport efficiency.