Panagiotis Papageorgas

In this paper, we conducted a state-of-the-art survey on the current state of IoT platforms suitable for the development of smart city (SC) applications. Both commercial and open-source IoT platforms are presented and compared, addressing various significant aspects and characteristics of SC applications, such as connectivity, communication protocols, dashboards/analytics availability, security, etc. The characteristics of all the investigated platforms were aggregated so that useful outcomes regarding the technological trends of the IoT platforms could be derived. Furthermore, an attempt was made to identify any discrepancies between the needs of smart cities and the capabilities provided by the relevant platforms. Moreover, IoT platforms referring to the domains of industry, agriculture, and asset tracking were also included, alongside platforms that purely target smart cities, as parts of them are also applicable to smart city applications. The results of the comparison proved that there is a lack of open-source IoT platforms targeted at smart cities, which impedes the development and testing of connected smart city applications for researchers.

Digital Twins serve as virtual counterparts, replicating the characteristics and functionalities of tangible objects, processes, or systems within the digital space, leveraging their capability to simulate and forecast real-world behavior. They have found valuable applications in smart farming, facilitating a comprehensive virtual replica of a farm that encompasses vital aspects such as crop cultivation, soil composition, and prevailing weather conditions. By amalgamating data from diverse sources, including soil, plants condition, environmental sensor networks, meteorological predictions, and high-resolution UAV and Satellite imagery, farmers gain access to dynamic and up-to-date visualization of their agricultural domains empowering them to make well-informed and timely choices concerning critical aspects like efficient irrigation plans, optimal fertilization methods, and effective pest management strategies, enhancing overall farm productivity and sustainability. This research paper aims to present a comprehensive overview of the contemporary state of research on digital twins in smart farming, including crop modelling, precision agriculture, and associated technologies, while exploring their potential applications and their impact on agricultural practices, addressing the challenges and limitations such as data privacy concerns, the need for high-quality data for accurate simulations and predictions, and the complexity of integrating multiple data sources. Lastly, the paper explores the prospects of digital twins in agriculture, highlighting potential avenues for future research and advancement in this domain.