Flood Early Warning Systems Using IoT Telemetry: A Review of System Components and Applications

Samuel M. Nyaanga, Duncan. Mbuge D., Abraham Nyete

Abstract: Flood disasters are increasing globally due to climate change, rapid urbanization, and unsustainable land use. Traditional flood monitoring approaches often fail to provide timely warnings, particularly in developing countries. The emergence of Internet of Things (IoT)-enabled Flood Early Warning Systems (FEWS) offers transformative potential by integrating real-time sensors, telemetry networks, cloud-based data processing, and multi-channel alert dissemination. This paper presents a systematic review of global and Kenya-specific applications of IoT telemetry in FEWS, highlighting system components, implementation strategies, challenges, and opportunities. Key components discussed include hydrological and meteorological sensors, communication technologies such as GSM, LoRaWAN, and satellite telemetry, data analytics and predictive models, and alert dissemination platforms. Lessons from pilot deployments in Kenya?s Tana River, Nyando, and Nairobi River catchments illustrate improvements in lead time, situational awareness, and community preparedness. Challenges such as connectivity gaps, high costs, and limited technical capacity are identified, alongside opportunities for low-cost, sustainable sensor networks and integration with predictive analytics. The study concludes with recommendations to enhance IoT-enabled FEWS in Kenya and similar developing countries, promoting resilient flood management infrastructure and informed disaster response.

Keywords: Data Analytics, Disaster Risk Reduction, Flood Early Warning Systems, IoT telemetry, Real-time Monitoring, Sensors, Telemetry Networks, Predictive Flood Modelling