A prototype of a low-cost GNSS (Global Navigation Satellite System) monitoring system was installed on a deep-seated landslide in north-western Slovenia to test its performance under field conditions. The system consists of newly developed GNSS stations based on low-cost, dual-frequency receivers and open-source GNSS processing software. It automatically receives GNSS data and transmits them over the Internet. The system processes the data server-side and makes them available to the end user via a web portal. The detected surface displacements were evaluated through a comparison with the network of classic geodetic measurements. The results of a nine-month monitoring period using seven GNSS stations provided a detailed insight into the spatial and temporal pattern of deep-seated landslide surface movements. The displacement data were correlated with precipitation measurements at the site to reveal how different parts of the landslide react to rainfall. These data form the basis for the further development of an early-warning system which will help to manage the risk the landslide poses to the local population and infrastructure.

The use of autonomous robots for certain tasks within agriculture applications can bring many advantages. The H2020-funded GreenPatrol project has developed an autonomous system for pest detection and treatment within commercial greenhouses. In this system the robot will navigate autonomously and regularly inspect crops using an array of cameras and algorithms to detect and treat pests at an early stage in order to improve yield, reduce pesticide use and improve worker conditions. A key enabler for this application is the localization and navigation function of the robot platform. In order to operate independently and autonomously, the robot must know in real-time its precise location and direction of pointing, it must be able to plan a route through the greenhouse from its current location to where it needs to go, it must be able to control its movements to reach its required destination, and it must be able to identify and avoid obstacles that may obstruct its route. In order to achieve these goals the robot sub-systems include an absolute localization function, to provide precise absolute position and heading in a global reference frame in real-time, a relative localization function, to provide more fidelity of the exact location and orientation of the robot with respect to its surroundings in the greenhouse, and a navigation function, to plan the route through the greenhouse and provide movement instructions to the robot platform. This paper describes the localization system of the GreenPatrol robot and presents results of testing for each of the functions. The tests include simulations as well as data collections and tests of the real-time system using the robot platform. The results show the high performance of the positioning capability and heading information for the individual systems.

Geodetic Integrated Monitoring System (GIMS) has been developed as a low-cost solution for detecting and measuring ground movements (https://www.gims-project.eu/). The prototype has been tested on the landslide on Potoška planina in the north of Slovenia that has been monitored by the seven GIMS units. These units, consisting of GNSS receiver and inclinometer, provide live monitoring data with millimetric precision. In this paper, the project consortium presents the first results of the prototype measuring system and estimate its applicability in modern landslides monitoring. The GIMS measurements have been validated by the wire crackmeter located at the site. The data were correlated to the groundwater level in a piezometer and to the amount of precipitation detected at the rain gauge. Results of GIMS units show good comparability to the wire crackmeter measurements and increased precision in detecting variations in landslide movements. The latter enables us to precisely define the rainfall threshold value for the particular landslide as crucial information needed for a reliable early warning system.