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The negative effects of traffic, such as air quality problems and road congestion, put a strain on the infrastructure of cities and high-populated areas. A potential measure to reduce these negative effects are grocery home deliveries (e-grocery), which can bundle driving activities and, hence, result in decreased traffic and related emission outputs. Several studies have investigated the potential impact of e-grocery on traffic in various last-mile contexts. However, no holistic view on the sustainability of e-grocery across the entire supply chain has yet been proposed. Therefore, this paper presents an agent-based simulation to assess the impact of the e-grocery supply chain compared to the stationary one in terms of mileage and different emission outputs. The simulation shows that a high e-grocery utilization rate can aid in decreasing total driving distances by up to 255 % relative to the optimal value as well as CO 2 emissions by up to 50 %.
Unter Crowdsensing versteht man Anwendungen, in denen Sensordaten kollaborativ von einer Menge von Freiwilligen erhoben werden. So kann Crowdsensing eingesetzt werden um die Luftqualität an Orten zu messen, an denen keine fest installierten Sensoren verfügbar sind. In Crowdsensing-Systemen müssen die Teilnehmer koordiniert und die Messdaten verarbeitet werden, um relevante Daten zu erhalten. Im Rahmen der Abschlussarbeit wurde ein System konzipiert und prototypisch umgesetzt, das auf einem Raspberry Pi (unter Einsatz geeigneter Sensoren) Sensordaten erhebt und mit der Complex Event Processing Technologie verarbeitet.