Test Event Generation for a Fall-Detection IoT System

Abstract

The Internet of Things (IoT) is a popular paradigm which has been applied to different areas, such as smart cities, medicine, or business processes. One of the main drawbacks of an IoT system is the amount of information it has to manage and to monitor. This information arrives as events that need to be processed in real-time in order to make correct decisions. The event processing languages (EPLs) were designed to handle this information by defining event patterns which describe relevant situations to be detected and filter the information. In the majority of the relevant situations to detect, the events have a specific behavior which must be analyzed not only to define the event patterns but also to simulate them to test the IoT system. Moreover, in several situations it is quite difficult to obtain test events with specific values: adverse environment conditions, rise or fall in blood pressure, heart attack, falls, among others. In this paper, we introduce a complete study of falls as relevant situations; we show an analysis of the fall-involved events of two types of falls based on an IoT prototype, the event patterns to detect the falls and their test using the IoT-test event generator (IoT-TEG) tool. The fall analysis has highlighted the necessity to improve IoT-TEG with a new functionality which allows defining the desired conduct by defining behavior rules.