Low-cost sensors and intelligent systems for landslide monitoring: a systematic literature review

Resumen

Landslides represent one of the major socio-environmental risks worldwide, with socio-economic impacts intensified by unequal urbanization and the increasing frequency of extreme events associated with climate change. In this context, monitoring and early warning systems based on low-cost sensors emerge as a strategic alternative to expand the coverage and accessibility of these technologies, particularly in areas with poor or inadequate infrastructure. This paper presents a Systematic Literature Review (SLR), conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, aiming to analyze the state of the art of such systems. The search was carried out in the Scopus and Web of Science databases, considering articles published between 2020 and 2025, resulting in a final selection of 69 studies. Bibliometric, thematic, and qualitative analyses made it possible to identify application contexts, employed technologies, and criteria adopted for defining low cost. The results indicate a predominance of studies associated with intense rainfall events, the integration of in situ sensors, the Internet of Things (IoT), and applications in mountainous rural areas, as well as the emerging use of digital twins as a strategy for multiscale synthesis and predictive support. It is concluded that low-cost solutions have a high potential to democratize early warning systems, although challenges related to calibration, reliability, and durability remain.