BRIEF RESEARCH REPORT article
Front. Earth Sci.
Sec. Geohazards and Georisks
Volume 13 - 2025 | doi: 10.3389/feart.2025.1662640
This article is part of the Research TopicMonitoring, Early Warning and Mitigation of Natural and Engineered Slopes – Volume VView all 6 articles
A new low-cost inclinometer for landslide related structural health monitoring
Provisionally accepted
- 1Department of Sciences and Technologies, University of Sannio, Benevento, Italy
- 2Universita degli Studi del Sannio, Benevento, Italy
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Monitoring activities are fundamental for properly assessing landslide dynamics and safety of infrastructures exposed to landslide risk. Considering the expense of professional instruments, building a dense sensor network to collect distributed data is often challenging. A low-cost Arduino©- based 3-axis inclinometer is presented here as an alternative and valuable solution for widespread monitoring on low-budget projects. This sensor was developed to perform structural health monitoring (SHM), and assess the damage level and its growth rate by measuring the angular rotations of structures. In particular, the device takes measurements along three directions (x, y and z axes) in a full range of rotation and is characterized by very compact size and low power consumption. These characteristics represent major advantages compared to most professional inclinometers, which usually measure tilt angles along one or two directions in a range of less than 90°. The open-source Internet of Things (IoT) based instrument - equipped with capacitive 3D-MEMS technology (Micro Electro Mechanical Systems) and developed with an SPI (Serial Peripheral Interface) digital interface chip, an online data sending system and local data storage - finds applications in several environmental settings. Preliminary field tests were carried out in different landslide contexts, to evaluate the reliability and versatility of use of the device.
Keywords: landslide monitoring1, structural health monitoring2, low-cost inclinometer3, 3D-MEMS4, Arduino©5, Internet of Things (IoT)6
Received: 09 Jul 2025; Accepted: 29 Sep 2025.
Copyright: © 2025 Cifaldi, Leone, Mazza and Revellino. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Daniele Cifaldi, daniele.cifaldi@unisannio.it
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