Daniel Puschmann

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Internet of Things is a generic term that refers to interconnection of real-world services which are provided by smart objects and sensors that enable interaction with the physical world. Cities are also evolving into large interconnected ecosystems in an effort to improve sustainability and operational efficiency of the city services and infrastructure.(More)
The term Internet of Things (IoT) refers to the interaction and communication between billions of devices that produce and exchange data related to real-world objects (i.e. things). Extracting higher level information from the raw sensory data captured by the devices and representing this data as machine-interpretable or human-understandable information has(More)
With the growing popularity of information and communications technologies and information sharing and integration, cities are evolving into large interconnected ecosystems by using smart objects and sensors that enable interaction with the physical world. However, it is often difficult to perform real-time analysis of large amount on heterogeneous data and(More)
The emergence of the Internet of Things (IoT) has led to the production of huge volumes of real-world streaming data. We need effective techniques to process IoT data streams and to gain insights and actionable information from real-world observations and measurements. Most existing approaches are application or domain dependent. We propose a method which(More)
Analysis and processing of time-series data has been studied over the past decades and has resulted in several promising algorithms. Clustering continuous data is an interesting subset of unsupervised learning models to process and categorise the data. Over a long period and with a large number of samples most conventional data streams will converge to(More)
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