## 5 Experiments
### Test of the Proposed Method
#### 5.1.2 Application of the Method to the Scenarios  
In the subsequent sections, the realization of the method for each scenario is provided by aligning the stages and steps of each scenario case with those of the proposed method. Requirements: Layer/Stakeholder Goal Identification  
Process Flow--Step 1, Step 2: Stakeholder and Stakeholder Goal Identification  
Example stakeholders for each scenario, along with their goals, priorities, and the QA trade-offs are provided in Table 1.  
Specification Layer/Hardware and AI Model Quality Specification  
Process Flow--Step 3: Quality Specification (Define QM, Relevant QAs, and Sub-QAs)  
Process Flow--Step 4: Measurement Metrics and Measurement Methods Specification (Define Metrics and Measurement Methods for HW and AI Model Aspects)  
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Scenario ID, Name** & **Stakeholder** & **Goal** & **Priority, Impact** & **Trade-Offs** \\ \hline Scenario I: Low-Cost, Low-Power MAV for Simple Object & Small-scale Users: Organizations or individuals using MAVs in controlled environments (e.g., farms, industrial facilities). & Build a lightweight, low-cost, reliable MAV capable of performing simple object detection tasks, such as detecting a person or large static obstacles (e.g., cars, buses) in controlled environments. & Lightweight design, cost-efficiency, and low power consumption are critical to enhance agility and extend operational time in constrained environments. & The MAV does not need advanced AI processing capabilities, but must be agile, power-efficient, reliable, and operate in environments where only basic detection algorithms are sufficient. & The MAV does not need advanced AI processing capabilities, but must be agile, power-efficient, reliable, and operate in environments where only basic detection algorithms are sufficient. & The UAV should handle real-time object detection without requiring high-end AI processing. Balancing power consumption with AI performance is critical for efficiency in tasks like monitoring or surveillance. & Balanced performance, energy efficiency, and cost. The UAV must perform moderately complex tasks like running machine learning models (YOLO, SSD) while keeping power consumption in check to maintain flight time. & The UAV should handle real-time object detection without requiring high-end AI processing. Balancing power consumption with AI performance is critical for efficiency in tasks like monitoring or surveillance. \\ \hline Scenario III: Cost-Effective, General-Purpose UAV for Outdoor & Environmental Monitoring Operators: Organizations using UAVs to inspect areas such as forests, agricultural land, or urban landscapes for environmental changes, wildlife monitoring, or security. & Cost-efficiency is the highest priority. Flash that performs general-purpose outdoor object detection. & The system should reflect a balance between physical priority. Flash memory and RAM are next in importance to handle basic processing and data storage needs. & The system should reflect a balance between computational power and cost, being capable of processing moderate amounts of data from standard-resolution cameras and sensors while maintaining low power consumption. \\ \hline Scenario IV: High-Performance UAV for Real-Time & Search and Rescue & A high-performance teams: Organizations using UAVs for lifesaving, where precise object tracking (e.g., people, vehicles) is critical. & High performance and precision are paramount. The UAV for real-time advanced object detection and tracking & Processing power takes priority, as the UAV needs to perform heavy-duty AI processing for real-time tracking. Cost and power consumption is secondary as to allow for moderate-duration operations in critical applications. & The UAV to perform heavy-duty AI processing for real-time tracking. Cost and power consumption is secondary as to allow for moderate-duration operations in critical applications. & The UAV to perform heavy-duty AI processing for real-time tracking.