This report describes the design and implementation of an interface subsystem for a fall detection system using a pressure based floor sensor. The goal of the fall detection system is to detect and alarm when an elderly person has fallen. The subsystem covers communication between hardware and software, using the WiFi protocol MQTT. The communication is fast enough so that it does not limit other subsystem performance and allows for high expandability to accommodate the hardware’s modular design. The interface module receives a probability of fall occurrence from the separate processing module, from which an average is taken over a 30 second time window to avoid false positives. Alarming is done through the use of text-to-speech voice API to make automated phone calls that retrieve user input to confirm or deny that help is on the way. A habit tracker proof of concept is provided that could improve the accuracy of fall detection by checking if the client is showing anomalies during a given day. A user interface is implemented using the Kivy environment. This environment has its own language which allows for separation of functionality and layout, which keeps the interface elements separate and leads to ease of use. Overall, this results in a strong alternative for fall detection that could be used to improve the time an elderly person can live at home safely without the need to move to a nursing home.