Analysis and Visualization of Urban Emission Measurements in Smart Cities

Cities worldwide aim to reduce their greenhouse gas emissions and improve air quality for their citizens. Therefore, there is a need to implement smart city approaches to monitor, model, and understand local emissions to better guide these actions. We present our approach that deploys a number of low-cost sensors through a wireless Internet of Things (IoT) backbone and is thus capable of collecting high-granular data. Based on a flexible architecture, we built an ecosystem of data management and data analytics including processing, integration, analysis, and visualization as well as decision-support systems for cities to better understand their emissions. Our prototype system has so far been tested in two Scandinavian cities. We present this system and demonstrate how to collect, integrate, analyze, and visualize real-time air quality data

Urban Traffic Prediction through the Second Use of Inexpensive Big Data from Buildings

Department of ComputingDepartment of Building Services Engineerin