Modern sensor networks monitor a wide range of phenomena. They are 5 applied in environmental monitoring, health care, optimization of industrial pro-6 cesses, social media, smart city solutions, and many other domains. All in all, they 7 provide a continuously pulse of the almost infinite activities that are happening in 8 the physical space—and in cyber space. The handling of the massive amounts of 9 generated measurements poses a series of (Big Data) challenges. Our work 10 addresses one of these challenges: the detection of anomalies in real-time. In this 11 paper, we propose a generic solution to this problem, and introduce a system that is 12 capable of detecting anomalies, generating notifications, and displaying the recent 13 situation to the user. We apply CUSUM a statistical control algorithm and adopt it 14 so that it can be used inside the Storm framework—a robust and scalable real-time 15 processing framework. We present a proof of concept implementation from the area 16 of environmental monitoring. 17 Keywords Big data and real-time analysis Á Environmental sensor data Á