False alarms are a major cost driver for owners of alarm systems. To remedy this problem, we develop a novel alarm verification service by leveraging the power of an alarm data warehouse. By analyzing live streams of alarms, comparing them with historic alarms and enriching them with information from open data, our system learns how to identify false alarms, which helps human responders in their decision about triggering costly intervention forces or not.

In this project we will apply modern big data technology such as Spark SQL und Spark Streaming as well as state-of-the-art information retrieval and machine learning algorithms to solve this challenge with our industry partner Sitasys – one of the international leaders in secure alarm transmission.