The problem of landslides has been reported across the globe in the recent past. Specifically, in Rwanda, the landslide problem has been witnessed in Nyabihu district, western province of Rwanda for many years with a most recent event being reported in May 2021. When this happens it leads to losses due to destruction of properties and even sometimes death. Recently over 100 homes were damaged, 39 homes reportedly completely destroyed and 117 families were displaced as a result. However, there are no proper ways of alerting residence before such events occur so as to minimize the eventual impacts. Attempts have been made to come up with solutions but most of those are not applicable to the unique African setting due to connectivity, cost and power challenges. The emerging technologies of Internet of Things and Artificial Intelligence provide capabilities which can be exploited in coming up with improved solutions. This thesis project therefore was aimed at designing and prototyping an IoT based landslide monitoring and early warning system. A qualitative research method was used to collect and analyze data during the system analysis phase. This system is made up of an Arduino microcontroller unit (MCU), a soil moisture sensor, accelerometer sensor and a vibration Sensor. Based on the values collected by these sensors landslide prediction is done based on fuzzy logic on the microcontroller and appropriate warning alerts sent to the users via GPRS/GSM. The device is also fitted with a GPS module for tracking in case of landslides. The collected data is stored on the Thing Speak cloud platform for analytics and visualization. The implementation of the system will lead to a reduction in losses and deaths as a result of the landslides. The collected data can also be used for planning and further research by the government and other agencies.