We might be interested in recording sound from a audio sensor located at a single place continuously, ie. 24/7. This might be useful eg. for gathering data for some exploratory analysis, building a training dataset for machine learning, and performing an actual ML task.
- car traffic activity
- presence and activity of bird species
- monitoring weather - wind, rain, ...
- human activity in cities
Consider a small Raspberry Pi mini-computer act as the sensor.
- how and where to store the data?
- raw mono PCM sampled at 44kHz take ~3.5 GB per day
- how to deliver the data to the storage?
- connectivity
- how to compress the data?
- we might assume a typical soundscape might be quite boring (ie. sparse) and could be compressed well
- see dynamic compression
- how to deal with outages?
- power outage, upgrade, ...
- how to explore the data?
- how to find typical patterns?
- how to find interesting anomalies?
- how to precisely timestamp the data?
- NTP?
- how to combine recordings from multiple sensors?
- how to combine the data with other modalities?