Current fall risk assessment and prevention strategies typically take a reactive approach, which makes it difficult to predict an individual’s first fall. This paper introduces an Internet of Things (IoT) system as a complex network designed for continuous falls risk screening in the home environment using millimetre-wave (mm-wave) radar technology. This system operates without the need for user interaction and enables real-time monitoring of activity levels and gait parameters. By collecting detailed and consistent data, the proposed system provides a proactive approach to predicting future falls, thereby improving early intervention strategies. The system facilitates long-term analysis of gait patterns, allowing both improvements and deteriorations in mobility to be detected over time. The integration of mm-wave radar into IoT systems represents an advancement in fall prevention, providing a more comprehensive and predictive tool for maintaining mobility and safety in the home.