A BSTRACT  
1 Introduction  
2 Related Work  
2.1 Bluetooth applications  
2.2 Noisy labels in machine learning classifiers  
3 Methods and Materials  
3.1 Sensing platform  
3.2 Experiment setup and data  
3.3 Wizard of Oz for P2D ground-truth collection  
3.4 Data preparation and classifiers for BIBO  
3.5 Simulation of Error Distributions  
4 Results  
4.1 People errors during ground-truth collection  
4.2 BIBO Classification Performance  
4.3 BIBO Resilience to Label Flipping  
5 Conclusion