Građevinski fakultet - 4G Monitor

Obrisani Korisnik — Tue, 13 Oct 2026 14:01:07 GMT

CONTACT

Obrisani Korisnik — Wed, 14 Oct 2026 08:24:15 GMT

PROJECT LEADER

professor Meho Saša Kovačević, PhD

University of Zagreb Faculty of Civil Engineering

Department of geotechnics

GENERAL INFORMATION

Obrisani Korisnik — Wed, 14 Oct 2026 08:24:02 GMT

Project reference	100-017/26
Host institution	University of Zagreb Faculty of Civil Engineering
Project leader	professor Meho Saša Kovačević
Duration	1 October 2025 - 30 September 2029 (48 months)
Budget	80.463,00 EUR

Research focus

Obrisani Korisnik — Tue, 13 Oct 2026 13:48:24 GMT

Site characterisation. Geological, geotechnical and spatial data to support the selection and description of pilot sites.

Sensor system development. Integration of magnetic and gravity sensors, accelerometers and other measurement components into a modular IoT system.

Data processing and interpretation. Development of machine learning algorithms and criteria for detecting changes relevant to early warning.

Field validation. Validation at pilot sites, with guidelines and an interface for data visualisation.

4G brings together geotechnics, geology, geophysics and geodesy.

Obrisani Korisnik — Wed, 14 Oct 2026 08:47:01 GMT

Monitoring the behaviour of soil, rock and geotechnical structures requires the integration of knowledge from geotechnics, geology, geophysics and geodesy – the 4G approach. The aim of 4G-MONITOR is to develop a modular IoT sensor system for remote monitoring of terrain and infrastructure, with a focus on areas at risk. The system will use highly sensitive gravity and magnetic sensors, together with artificial intelligence algorithms, to process data and generate early warning models. Particular attention will be paid to the timely identification of rockfall, landslide and flood defence embankment collapse risks. The project will be carried out in collaboration with companies and practitioners working in monitoring, geophysical investigations and satellite measurements, supporting knowledge transfer into practice and the development of innovative solutions to protect people and infrastructure. Its scientific contribution lies in the development and validation of AI models for geotechnical monitoring and in multidisciplinary research. Its intended societal and economic benefits include risk reduction, guidelines for key stakeholders and the potential for commercialisation.