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Auflistung nach Schlagwort "mobile application"

1 - 5 von 5
  • Konferenzbeitrag
    A digital weed counting system for the weed control performance evaluation
    (42. GIL-Jahrestagung, Künstliche Intelligenz in der Agrar- und Ernährungswirtschaft, 2022) Pamornnak, Burawich; Scholz, Christian; Becker, Silke; Ruckelshausen, Arno
    The weed counting method is one of the keys to indicate the performance of the weed control process. This article presents a digital weed counting system to use instead of a conventional manual counting system called “Göttinger Zähl- und Schätzrahmen” or “Göttinger Rahmen” due to the limitation of human counting on big-scale field experiment areas. The proposed method demonstrated on the maize field consists of two main parts, a virtual weed counting frame and a weed counting core, respectively. The system was implemented as a mobile application for the smartphone (Android) with server-based processing. The pre-processed image on the mobile phone will be sent to the weed counting core based on the pre-trained convolution neural network model (CNN or deep learning) on the server. Finally, the number of detected weeds will be sent back to the mobile phone to show the results. In the first implementation, 100 frames on a 1-hectare field area were evaluated. The absolute weed counting errors were categorized into three groups, A-Group (0-10 weeds error) achieves 73 %, B-Group (11-20 weeds error) achieves 17 %, and C-Group (21-30 weeds error) achieves 10 %, respectively. For overall performance, the system achieves the  = 0.97 from the correlation and 12.8 % counting error. These results show the digital version of “Göttinger Rahmen” has the potential to become a practical tool for weed control evaluations.
  • Textdokument
    The Integration of Diverse User Data to derive User Requirements
    (INFORMATIK 2017, 2017) Halama, Josephine; Döbelt, Susen
    The user-centered design process demands for the collection of user requirements. Thereby, the process of integrating diverse user data poses several challenges. The aim of our research project AndProtect is to develop a usable tool that provides users a risk evaluation of their apps. Therefore, we captured requirements of smartphone users and applied diverse methods and questioning techniques. For this, we conducted a survey (N = 227) and a user experience assessment (N = 31). Thereby, challenges with regard to the feasibility of user requirements, the consideration of the frequency of responses, and contradictory statements occurred. As a result, we present how we dealt with these challenges and purpose strategies for the requirements integration. Our purposes can guide other researchers, since different methods, techniques and samples commonly used in a user-centered process. Moreover, the discussion on this article could support the identification of new approaches to integrate diverse user data.
  • Conference Paper 
    A mobile campus application as a sensor node for Personal Learning Environments
    (DELFI 2019, 2019) Geßner, Hendrik; Kiy, Alexander
    For many web-based applications, there is at least one corresponding mobile applica­tion. By leveraging a mutual exchange of the cross-device user context between mobile and web-based application, guidance and processes can be improved and therefore simplified. This article presents an infrastructure to enable cross-device and cross-service personalization and adaption while aiming at high interoperability between heterogeneous systems. As a proof-of-concept, an existing mobile campus app framework was extended by a hybrid context-framework to capture user data, which is stored in a Learning Record Store (LRS) by the use of the Experience API.
  • Konferenzbeitrag
    PrecRec: supporting older adults sharing recipes
    (Mensch und Computer 2020 - Tagungsband, 2020) Tullius, Gabriela; Dogan, Gamze
    Due to decreased mobility or families living apart, older adults are especially vulnerable to the issue of social isolation. Literature suggests that technology can help to prevent this isolation. The present work addresses an approach to participate in society by sharing knowledge that is cherished. We propose the cooking recipe exchange application PrecRec for older adults to make them feel precious and valued. PrecRec has been developed and evaluated in an iterative process with eleven older adults. The results show that a broad perspective has to be taken into account when designing such systems.
  • Konferenzbeitrag
    “Ready for Autonomy (R4A)”: concept and application for autonomous feeding
    (43. GIL-Jahrestagung, Resiliente Agri-Food-Systeme, 2023) Pamornnak, Burawich; Scholz, Christian; Gode, Eduard; Sommer, Karen; Novak, Timo; Hellermann, Steffen; Wegmann, Benjamin; Ruckelshausen, Arno
    This paper presents the development of the “Ready for Autonomy (R4A)” application for evaluating the feasibility of integrating an autonomous feeding machine Strautmann Verti-Q into farmyards and evaluating the machine’s performance. The proposed application consists of three main R4A checklists for telling whether the farmyard, the machine, and the farmer are ready for autonomy or not. The farmyard is the first part to be checked with the R4A application with the Verti-Q system requirements. The R4A result will be instantly generated from the application based on the Boolean function. The second part is the machine operation record which tells the overall performance of the Verti-Q machine as the R4A distribution results, e.g., excellent, good, and failure. The final part is the farmer operation training in manual and autonomous modes, in which farmers have to go through every topic to be ready to use the machine. From the experimental results, seven farmyards were observed with the R4A application. Therefore, the four farmyards are ready for autonomy with different R4A levels. The minimum working condition of the Verti-Q machine has been tested on the lowest R4A level farmyard. The distribution results from the prototype machine with 218 autonomous feeding jobs, achieving 42% in excellent distribution, 38% in good condition, and 21% in failure caused by various reasons, e.g., hardware, software, and user error, respectively. These results show the possibility of using the improved version of the autonomous feeding machine in the farmyard for sustainable farming in the future.