Sometimes you need to acquire data from several different locations that are separated far enough from each other that they cannot be acquired by a single, multichannel system. This defines the need to synchronize readings from two or more data gathering systems. In situations like that, how you solve the problem is dependent upon the nature of the data you need to acquire and the time frame that you need to acquire it.
In a previous post I talked about clock accuracy in the form of a parts per million (PPM) specification. It’s possible to rely only on clock accuracy to effectively synchronize measurements from geographically separated data loggers. For example, if we assume that temperature measurements from two different locations need to be acquired over a period of two months using a low cost data logger product like this, we can easily determine the worst case accumulated error over that time frame. That figure can be compared to the requirements of our unique situation to determine if the approach is feasible. If the data logger’s clocks are speced at ±20 PPM, then we know that worst case drift of any single logger will be ±104 seconds (60 · 24 · 60 · 60 · ±20 ÷ 1,000,000). Since the PPM spec is a plus and minus number, then worst case separation will occur when one logger runs at the high end of the spec and another at the low end, or 208 seconds (3 minutes and 28 seconds). If you determine that temperature cannot change significantly between multiple locations within this time frame then you may be justified to use a low cost approach and rely solely upon clock accuracy for synchronization. Should you determine that the approach will not work, you can seek a logger with better clock accuracy as measured by its PPM spec to tighten the time difference, or you might need a solution that guarantees data acquisition synchronization to the microsecond level.