Humans have a unique ability to solve new problems that arise. However, some tasks are best left for machines or done utilizing artificial intelligence.
Below is an explanation on why we believe measuring and counting logs is one of these tasks that would benefit from more machine intervention.
The task of how to measure logs is well-defined – it is done the same way every time, and you don’t need to use any creative problem-solving. This is perfect for AI because machine learning algorithms rely on finding a set of rules for how to complete its job. If the algorithm attempted to solve an entirely novel situation, it would probably not do an outstanding job. However, because logs do look similar in appearance, recognizing them is something that is very much doable.
How AI is reducing log calculation times
Measuring logs tends to take a human a substantial length of time. It is slow to physically move to a log, place your ruler on it and then to read and calculate the measurement. Admittedly, this does only take some seconds, yet if you measure a pile of hundreds of logs, this time adds up, moving from a few seconds to tens of minutes in several cases. However, an algorithm can process the whole image at once, much the same way a person can immediately guess the rough size of a pile merely by looking at it.
AI needs data to ‘learn’
Using artificial intelligence is only appropriate if doing it on a large scale. For one, to create a sound detector, you need a lot of training data, meaning the gathering of hundreds of thousands of images to learn from.
Secondly, developing the algorithm itself is time-consuming and costly. In many situations, the investment required to create this detector will never pay for itself. However, with Timbeter, the program has been created once for a large number of companies, and each customer has only to pay for a fraction of the cost of development through subscription fees.
Sounds fascinating? Why not try it for free and contact us for a free trial.
