With the advancements of technology in the era of big data and artificial intelligence, IoT (Internet of Things) has a major role for the purpose of monitoring natural disasters like landslides. Landslides are a catastrophic disaster worldwide that alter from terrain to terrain. In the pursuit of saving communities that are endangered by landslides, many monitoring techniques are practiced. This paper is a survey of the major landslide monitoring techniques adapted in different parts of the world to monitor unstable slopes. It provides a glance into the challenges and opportunities of integrating IoT into the major landslide monitoring techniques, which are explained briefly with emphasis on real-world case studies. Each technique is presented regarding the kind of monitoring parameters, the type of landslides that it can monitor, landslide investigating phases, advantages, disadvantages, and the possibility of IoT to integrate with each techniques. This paper also aims to provide an overview of landslide monitoring in general to non-specialist in the field. The major monitoring techniques are classified based on the type (fall, topple, slide, spread, flow, slope deformation), velocity (slow, moderate, rapid), monitoring parameters (meteorological, geological, hydro-geological, physical, geophysical), monitoring phases (spatial, temporal) and early-warning systems (spatial, temporal) of landslides. This classification will serve as a guideline (but not a replacement for expert advice) for selecting appropriate landslide monitoring technique and the classifications are expressed through visual representations.