Accepted papers – EAI Urb-IoT 2020

Person-Flow Estimation with Preserving Privacy using Multiple 3D People Counters	Nagata, Yoshiteru (Nagoya University); Yonezawa, Takuro (Nagoya University); Kawaguchi, Nobuo (Nagoya University)
Calibration of Low-cost Particulate Matter Sensors with Elastic Weight Consolidation (EWC) as an Incremental Deep Learning Method	Schlund, Rainer (Karlsruhe Institute of Technology (KIT), TECO); Riesterer, Johannes (Karlsruhe Institute of Technology (KIT), TECO); Köpke, Marcel (Karlsruhe Institute of Technology (KIT), TECO); Kowalski, Michal (Helmholtz Zentrum München, German Research Center for Environmental Health (HMGU)); Tremper, Paul (Karlsruhe Institute of Technology (KIT), TECO); Budde, Matthias (Karlsruhe Institute of Technology (KIT), TECO); Beigl, Michael (Karlsruhe Institute of Technology (KIT), TECO)
Quality and Reliability Metrics for IoT Systems: A Consolidated View	Klima, Matej (Czech Technical University in Prague); Rechtberger, Vaclav (Czech Technical University in Prague); Bures, Miroslav (Czech Technical University in Prague); Bellekens, Xavier (University of Strathclyde); Hindy, Hanan (Abertay University); Ahmed, Bestoun S. (Karlstad University)
A Crowd-sourced Obstacle Detection and Navigation App for Visually Impaired	Kim, Edward (University of Washington); Sterner, Joshu (University of Washington); Mashhadi, Afra (University of Washington)
An ecosystem approach to the design of sensing systems for bicycles	José, Rui (University of Minho); Cabral, Ricardo (Centro Algoritmi, University of Minho, Portugal); Peixoto, Eduardo (Centro Algoritmi, University of Minho, Portugal); Carvalho, Carlos (Centro Algoritmi, University of Minho, Portugal)