Application of the spherical fuzzy dematel model for assessing the drone apps issues

• Autorzy: Pandey Mamta , Litoriya Ratnesh , Pandey Prateek

Identyfikatory

DOI

10.14313/JAMRIS/2‐2023/14

• Języki publikacji: EN

Abstrakty

EN

During the past few years, the number of drones (unmanned aerial vehicles, or UAVs) manufactured and purchased has risen dramatically. It is predicted that it will continue to spread, making its use inevitable in all walks of life. Drone apps are therefore expected to overrun the app stores in the near future. The UAV’s software is not being studied/researched despite several active research and studies being carried out in the UAV’s hardware field. A large‐scale empirical analysis of Google Play Store Platform apps connected to drones is being done in this direction. There are, however, a number of challenges with drone apps because of the lack of formal and specialized app development procedures. In this paper, eleven drone app issues have been identified. Then we applied the DEMATEL (Decision Making Trial and Evaluation Laboratory) method to analyze the drone app issues (DIs) and divide these issues into cause and effect groups. First, multiple experts assess the direct relationships between influential issues in drone apps. The evaluation results are presented in spherical fuzzy numbers (SFN). Secondly, we convert the linguistic terms into SFN. Thirdly, based on DEMATEL, the cause‐effect classifications of issues are obtained. Finally, the issues in the cause category are identified as DI’s in drone apps. The outcome of the research is compared with the other variants of DEMATEL, like rough‐Z‐number‐ based DEMATEL and spherical fuzzy number, and the comparative results suggest that spherical fuzzy DEMA‐ TEL is the most fitting method to analyze the interrela‐ tionship of different issues in drone apps. The findings revealed that highest influenced values feature request (DI9 ) 3.12, Customer support (DI6) 2.91, Connection/Sync ((DI4) 2./72, Cellular Data Usage ((DI3) 2.51, Battery (DI2) 2.31, Advertisements ((DI1) – 0.3, Cost (DI5) – 0.5, Additional cost (D11) – 0.5, Device Compatibility (DI7) – 0.96, and Functional Error (DI10) – 1.2. The outcome of this work definitely assists the software industry in the successful identification of the critical issues where professionals and project managers could really focus.

Słowa kluczowe

EN

drone app; issues; multi-criteria decision making; spherical fuzzy DEMATEL

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2023
• Tom: Vol. 17, No. 2
• Strony: 36--50
• Opis fizyczny: Bibliogr. 66 poz., rys.

Twórcy

autor

Pandey Mamta

• Mahatma Gandhi Institute of Technology, Hyderabad, India

autor

Litoriya Ratnesh

• Medi‐Caps University, Indore (Madhya Pradesh), India

autor

Pandey Prateek

• Jaypee University of Engineer‐ ing and Technology, Guna (Madhya Pradesh), India

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).