Michael Lunglmayr, Günther Lindorfer, Bernhard A. Moser,
"Robust and Efficient Bio-Inspired Data-Sampling Prototype for Time-Series Analysis"
: Database and Expert Systems Applications - DEXA 2021 Workshops, Springer International Publishing, Cham, Seite(n) 119--126, 2021, ISBN: 978-3-030-87101-7
Robust and Efficient Bio-Inspired Data-Sampling Prototype for Time-Series Analysis
Sprache des Titels:
Database and Expert Systems Applications - DEXA 2021 Workshops
Data acquisition is crucial for efficient AI systems. We present a bio-inspired prototype implementation of discrepancy-based adaptive threshold-based sampling on a low-cost microcontroller. We show measurement results demonstrating that an adaptive threshold-based sampling approach can be performed only using onboard components of the microcontroller. To measure the sampling precision, we used sinusoidal signals output by a waveform generator and compared the signals after reconstruction to exact signals with the set parameters. These measurements show that, even with such low-cost components, discrepancy-based adaptive threshold-based sampling can be performed with high precision.