Leveraging HyperSoft Set to Optimize Livestock in the Era of Unmanned Aerial Vehicles

Due to urbanization and industrialization, rapid global change and the potential loss of arable land, agricultural output must rise in production levels and harvest, distribute, and use resources more efficiently. It is believed that using technology on livestock would help meet the expanding population's demand for food. Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) integration in conventional farming has transformed operations, providing farmers with greater productivity, improved decision-making, and sustainability. We assume that there are enough UAVs to cover the entire pasture, and our goal is to identify the best UAVs. Accordingly, determining the best type of UAVs for livestock management that embraces information and communication technologies (ICT) such as the IoT, UAVs to be precise and smart is inevitable. Therefore, this study constructed a robust paradigm to take responsibility for selecting the best type of UAVs for livestock management. Opinion Weight Criteria Method (OWCM) to obtain weights and wherein these weights are utilized in Root Assessment Method (RAM) to rank UAVs and recommend the optimal UAV as well as the worst UAV based on set of attributes and attributes values. These techniques are implemented under the uncertainty theory of Neutrosophic which combined with soft sets notion to generate Triangular Neutrosophic HyperSoft (TrNSHSS). For validating the robustness of the constructed paradigm, we applied it into real case study and comparing it with other methods. The findings of the applied methods agree with constructed paradigm's findings.