P328 - EnviroInfo 2022

Permanent URI for this collectionhttps://dl.gi.de/handle/20.500.12116/39388

Authors with most Documents  

Gómez, Jorge Marx
2
Wagner vom Berg, Benjamin
2
Akyol, Ali
1
Appold, Christian
1
Bader, Tobias
1

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Author: search.filters.author.Gómez, Jorge Marx

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  • Conference Paper
    BITS: A Key Performance Indicators (KPIs) supported approach to assess traffic safety for cyclists at intersections in the Netherlands
    (Gesellschaft für Informatik e.V., 2022) Schering, Johannes; Gómez, Jorge Marx; Wohlgemuth, Volker; Naumann, Stefan; Arndt, Hans-Knud; Behrens, Grit; Höb, Maximilian
    Traffic safety is an important factor in the decision process whether people decide to use the bicycle or not. Critical situations that do not lead to an accident are often not reported to the police. To fill this knowledge gap, several regions as the city of Zwolle and the Province of Friesland (Netherlands) have started to detect near accidents at intersections among vehicles and bicycles by 3D camera data to evaluate traffic safety. Four intersections in Friesland and Zwolle were monitored. Different types of intersections (e.g. shared space concept) were considered. Near accidents can be divided into different conflict categories depending on vehicle speed and time to collision (Post-Encroachment Time PET). The preprocessed data including Key Performance Indicators (KPIs) to make cycling safety at the intersections measurable and comparable are provided. Based on the numbers and visualizations, it will be discussed which of the discussed intersections show critical profiles regarding numbers of near accidents, distribution and amount of very critical situations. With the results the intersections can be adjusted to increase traffic safety.Encroachment Time PET). The pre-processed data including relevant Key Performance Indicators (KPIs) to make cycling safety at the intersections measurable and comparable are provided. Based on the numbers and visualizations, it will be discussed which of the dis-cussed intersections show critical profiles regarding the total numbers of near accidents, its distribution and the amount of very critical situations. Based on the results the intersections can be adjusted to increase the safety situation in a city.
  • Conference Paper
    Living lab research project "5G Smart Country" - Use of 5G technology in precision agriculture exemplified by site-specific fertilization
    (Gesellschaft für Informatik e.V., 2022) Bhatti, Moid Riaz; Akyol, Ali; Rosigkeit, Henrik; Matzke, Linda; Grabenhorst, Isabel; Gómez, Jorge Marx; Wohlgemuth, Volker; Naumann, Stefan; Arndt, Hans-Knud; Behrens, Grit; Höb, Maximilian
    The research project "5G Smart Country" aims at developing ideas for the development and testing of 5G applications for agriculture and forestry under real conditions. Agricultural and forestry data are collected from a wide variety of sources, such as satellites, drones, and robots with special sensors. Artificial intelligence (AI) and data analytics algorithms help make the required decisions, particularly for automatic differentiation between crops and weeds for mechanical weed control, demand-driven fertilization (variable rate application, VRA)—also by means of small-scale application (pointed fertilizing)—automated tracking of wildlife populations, real-time assessment of harvest (smart harvesting), forest inventory maintenance, and targeted logging. Here we present a system architecture and software model for digital crop management and show how multispectral analysis is used to develop vegetation indices to conduct VRA.
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