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CityPulse: Large Scale Data Analytics Framework for Smart Cities (2016)
Puiu, Dan ; Barnaghi, Payam ; Tönjes, Ralf ; Kümper, Daniel ; Intizar Ali, Muhammad ; Mileo, Alessandra ; Xavier Parreira, Josiane ; Fischer, Marten ; Kolozali, Sefki ; Farajidavar, Nazli ; Gao, Feng ; Iggena, Thorben ; Pham, Thu-Le ; Nechifor, Cosmin-Septimiu ; Puschmann, Daniel ; Fernandes, Joao
Our world and our lives are changing in many ways. Communication, networking, and computing technologies are among the most influential enablers that shape our lives today. Digital data and connected worlds of physical objects, people, and devices are rapidly changing the way we work, travel, socialize, and interact with our surroundings, and they have a profound impact on different domains,such as healthcare, environmental monitoring, urban systems, and control and management applications, among several other areas. Cities currently face an increasing demand for providing services that can have an impact on people’s everyday lives. The CityPulse framework supports smart city service creation by means of a distributed system for semantic discovery, data analytics, and interpretation of large-scale (near-)real-time Internet of Things data and social media data streams. To goal is to break away from silo applications and enable cross-domain data integration. The CityPulse framework integrates multimodal, mixed quality, uncertain and incomplete data to create reliable, dependable information and continuously adapts data processing techniques to meet the quality of information requirements from end users. Different than existing solutions that mainly offer unified views of the data, the CityPulse framework is also equipped with powerful data analytics modules that perform intelligent data aggregation, event detection, quality assessment, contextual filtering, and decision support. This paper presents the framework, describes ist components, and demonstrates how they interact to support easy development of custom-made applications for citizens. The benefits and the effectiveness of the framework are demonstrated in a use-case scenario implementation presented in this paper.
Nutrient Recovery from Biogas Digestate by Optimised Membrane Treatment (2018)
Gienau, Tobias ; Rosenberger, Sandra
Biogas plants produce nutrient rich digestates as side products, which are usually used as local fertilisers. Yet the large amount and regional gradients of biogas plants in Germany necessitate management, conditioning, and transportation of digestates, in order to follow good fertilising procedure and prohibit local over-fertilisation. With a membrane-based treatment chain, i.e. centrifugation, ultrafiltration, and reverse osmosis, digestates can be separated into a solid N,P-fertiliser, a liquid N,K-fertiliser, and dischargeable water. Up to now, the high energy demand of the process chain, in particular the ultrafiltration step, limits the economical market launch of the treatment chain. A reduction of the energy demand is challenging, as digestates exhibit a high fouling potential and ultrafiltration fluxes differ considerably for digestates from different biogas plants. In a systematic screening of 28 digestate samples from agricultural biogas plants and 6 samples from bio-waste biogas plants, ultrafiltration performance could be successfully linked to the rheological properties of the digestate’s liquid phase and to its macromolecular biopolymer concentration. By modification of the fluid characteristics through enzymatic treatment, ultrafiltration performance was considerably increased by factor 2.8 on average, which equals energy savings in the ultrafiltration step of approximately 45%. Consequently, the energy demand of the total treatment chain decreases, which offers potential for further rollout of the membrane-based digestate treatment.
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