#sensor data analysis consulting

I run a mathematics consulting business that specializes in designing software / algorithms for many applications, including sensor fusion and sensor data analysis.

We can design custom-built and sophisticated algorithms for your multiple sensor applications including

Noise removal / compensation

Sensor fusion

Data transformations

Machine learning

If the information is there somewhere in the data, there’s almost no limit to the sophisticated mathematical techniques that you can apply, including machine learning, data transformations, noise compensation/removal.

There are many machine learning techniques that are excellent for use in sensor algorithms.

Many simple statistical techniques that were formally simply considered part of statistics, such as linear regression (or non-linear regression for that matter), are now considered “machine learning”. And these techniques are integral to most sensor data algorithms, or to any kind of data analysis.

Whether using regression or much more impressive techniques like neural networks or reinforcement learning, the essential application is the same. The algorithm needs to take some noisy, partial, spatially distorted data, or perhaps several partial datasets which overlap with discrepancy, and condense this data down to a single category or number.

You can do this by generating a large number of input datasets, labelled by the required output, allowing the algorithm to “learn” the relationship.

I run a mathematics consulting business that specializes in designing complex algorithms for many applications, including sensor fusion and sensor data analysis. We’re happy to explore how machine learning could be applied to build a decision making system on your sensor data. Check us out below!