# A Framework for Bluetooth-Based Real-Time Audio Data Acquisition in Mobile Robotics
## 5 Novel Implementation Methodology
### Experimental Protocol  
To assess the performance of the Sound Recording Rover, a number of experiments were performed under different conditions, examining performance metrics pertinent to both locomotion and audio capture. The test scenarios of the experimental protocol were as follows:  
Static audio quality assessment: When stationary, the rover was placed in three different acoustic environments (quiet room: 40 dB, office environment: 65 dB, and busy street: \(\sim\)85 dB) to assess the audio capture performance while the rover remains fixed in an environment. This method for testing corresponds to acoustic environment characterization approaches described by [PERSON] [39].  
Combined moving and sound recording: The rover was driven in a fixed movement sequence (forward-right-backward-left-stop) recording audio at the same time, and repeated in the three acoustic environments. This test protocol includes sequential movement patterns like those reported by [PERSON] et al. [34] in their approaches for motion planning for robots.  
Distance and obstacle testing: Control latency and audio streaming quality were evaluated at increasing distances (2 m, 5 m, and 10 m) and with a variety of obstacles (walls and furniture) between the rover and control device. This assessment method is adaptive of the experimental methodologies referred to by [PERSON] et al. [20] for audio-based localization systems.  
Battery endurance testing: The rover was run in constant motion with audio streaming until the battery went empty, and function metrics were recorded at regular intervals. Thisexperimental protocol applies techniques to analyze power consumption analogous to the works of [PERSON] et al. [27] in the assessment of autonomous vehicles powered by solar energy.  
For each scenario, the following parameters were measured:  
* Command latency (time from control input to observed movement).
* Audio packet delivery rate (percentage of expected audio packets successfully received).
* Subjective audio quality (assessed through blind comparison using a five-point Likert scale similar to the Mean Opinion Score (MOS) by three independent evaluators).
* Power consumption (measured using an inline current sensor).
* CPU utilization (reported by ESP32 diagnostics).  
The structured evaluation methodology used statistical analysis techniques analogous to those used by [PERSON] et al. [32] for the quantification of robotic system performance, focusing on variance analysis across various operational conditions.  
This provided a thorough testing protocol for assessing the performance of the system over its intended operational envelope, revealing both the strengths and limitations of the present implementation. The evaluation of the multi-dimensional performance analysis adopts frameworks set up in the literature [33] for more complex robotic systems with multiple performance tasks.  
The blind comparison protocol for subjective quality assessment was modeled on standardized evaluation methodologies used in audio quality research, with evaluators rating audio samples on clarity, noise level, and overall perceptual quality. Each evaluator independently assessed the same audio samples without knowledge of the recording conditions, and scores were averaged to provide the subjective quality ratings reported in Table 2.