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Evaluation of user feedback in smart home for situational context identification., , , , , , and . PerCom Workshops, page 20-25. IEEE Computer Society, (2015)Reduce the Number of Sensors: Sensing Acoustic Emissions to Estimate Appliance Energy Usage., , , , , , and . BuildSys@SenSys, page 12:1-12:8. ACM, (2013)Empirical investigation of the effect of the door's state on received signal strength in indoor environments at 2.4 GHz., , , , , , , and . LCN Workshops, page 652-657. IEEE Computer Society, (2014)Hybrid Model for Large Scale Forecasting of Power Consumption., , , and . IWANN (1), volume 10305 of Lecture Notes in Computer Science, page 661-672. Springer, (2017)Fine-Granular Sensing of Power Consumption - A New Sensing Modality for an Accurate Detection, Prediction and Forecasting of Higher-Level Contextual Information in Smart Environments.. Darmstadt University of Technology, Germany, (2016)Electricity-Metering in a Connected World: Virtual Sensors for Estimating the Electricity Consumption of IoT Appliances., , , , and . FiCloud, page 317-324. IEEE Computer Society, (2015)CPaaS: Context Processing as a Service., , , , , , , and . Praxis der Informationsverarbeitung und Kommunikation, 36 (1): 47 (2013)Activity Recognition in Multi-User Environments Using Techniques of Multi-label Classification., , , and . IOT, page 15-23. ACM, (2016)Situation Detection based on Activity Recognition in Disaster Scenarios., , , , , , and . ISCRAM, ISCRAM Association, (2018)Reducing the electricity consumption of largeoutdoor LED advertising screens., , , , and . e-Energy, page 209-210. ACM, (2014)