Background: GeoInformation, is very valuable for a range of fields ranging from location based services and navigation to smart cities and homes. On the other hand today many fields benefit from Internet of Things (IoT) implementations, where the machine-to-machine and machine-to-human transmission of GeoInformation frequently occurs. This transmission usually occurs in multi-source/multi-target and multiplatform IoT environments. Problem Statement: In many cases real-time GeoInformation stays in its own island of automation, and thus its real value cannot be uncovered. This happens mainly due to inefficiencies and problems that occur in the storage, sharing and exchange of real-time GeoInformation as a result of multi-source/multi-target and multi-platform nature of the IoT architectures. Research Approach: Integration appears as a critical paradigm which should be focused in order to store, manage and transfer of GeoInformation efficiently in these complex environments. In this context, the focus of the study was to test the applicability of different technologies and integration methods for acquisition, transmission and visualisation of multi-source GeoInformation through implementing an IoT Integration Testbed Architecture which is utilizing low-cost hardware (to acquire information), graph databases(to store information) and standard IoT protocols (to exchange information). The implementation explained in this paper covers acquisition of real time GeoInformation from a set of real and virtual sensors, storage of this GeoInformation in Graph Databases, exchange of information through two different communication models (request/response and publish/subscribe) based on standard IoT protocols, and visualization of information by web pages, web mapping services and using a GIS software. Results: The implementation results demonstrated a proof-ofconcept on how multi-source GeoInformation acquired from different type of IoT nodes can be integrated, stored and visualised on different platforms by utilising a standard IoT communication paradigms and multiple communication models.