# A Framework for Bluetooth-Based Real-Time Audio Data Acquisition in Mobile Robotics
## 7 Applications and Future Directions
### Future Research Directions  
Building upon the foundation established in this work, several promising directions for future research emerge:  
Multi-microphone array: Expanding the audio input capacity with multiple spatially distributed microphone operations would allow several advanced functions like sound source localization, beamforming-based noise cancelling, and directional recording. For this, the ESP32 has two I2S interfaces that can be used to read signals from an ADC directly. On-device audio processing: Although a performance analysis revealed there is computational headroom available, the future releases may incorporate on-device audio feature extraction and classification. Such a solution can also reduce communication bandwidth because only meaningful acoustic events or statistics instead of the entire audio stream have to be transmitted. Integration of machine learning: Adding lightweight machine learning models for audio event detection and classification would transform the platform from a passive data recorder into an intelligent acoustic monitoring system. TinyML frameworks specifically designed for ESP32 could enable the on-device processing of acoustic events, reducing bandwidth requirements and enabling real-time responses to specific sounds (alarms, breaking glass, or animal vocalizations). This approach would significantly reduce reliance on continuous streaming while maintaining high-quality event detection capabilities. Advanced noise cancellation: Future implementations should incorporate sophisticated adaptive filtering techniques to address motor interference. LMS (Least Mean Squares) and NLMS (Normalized Least Mean Squares) algorithms could be implemented to dynamically cancel motor noise in real time. These adaptive filters could learn the spectral characteristics of motor interference during operation and selectively attenuate the 120 Hz and 250 Hz peaks identified in our analysis, while preserving environmental audio content. Comprehensive wireless communication analysis: Future studies should include a detailed characterization of Bluetooth signal quality across varying distances, environmental conditions, and interference scenarios. This should include RF signal strength measurements, a bit error rate analysis, and packet loss characterization to better understand the relationship between wireless channel conditions and system performance. Additionally, evaluations of alternative wireless protocols (Wi-Fi, LoRa, and ZigBee) for specific application scenarios would broaden the framework's applicability. Comparative performance evaluation: Future work should include systematic comparison with existing mobile acoustic sensing solutions where applicable. This could involve implementing comparable systems using alternative architectures and conducting controlled performance evaluations to quantify the advantages of the integrated approach presented here. Acoustic autonomous navigation: If autonomy is realized on this level, the system can search for sound sources and autonomously track them independently, and this would lead to developing novel applications such as industrial acoustic monitoring and wildlife acoustic exploration. Mesh networking: Extending the communication architecture to support mesh networking between multiple rovers would enable collaborative acoustic sensing over larger spatial regions. BLE Mesh and hybrid Wi-Fi/Bluetooth protocols could address the scalability limitations of current Bluetooth Classic implementation. This would allow platforms to communicate, share data, and coordinate mobility to maximize coverage and gather acoustic information from multiple vantage points concurrently, addressing the scalability concerns raised for multi-robot deployments. Improved power management: Improvements to the control of the power system and employment of energy scavenging devices, e.g., solar panels, could increase longevity in field scenarios, making battery replacement or recharging impractical for long-term deployments.