From Measuring Instruments to Virtual Measuring on Screen

This abstract was written for the Environmental Monitoring and Forensics Conference on Wednesday 22 October at The Edge, Sheffield. The event is sponsored by two Knowledge Transfer Networks and a number of other organisations.

From Measuring Instruments to Virtual Measuring on Screen

The difficulty with measuring at nanoscale and below lies in not being able to see what is measured, when Coordinate Measuring Machines (CMM) are used. Microscopes cannot be used for measuring at nanoscale because their respective technology may invade the object or material to be magnified thus changing the characteristics and possibly distorting the specimen.

When measuring environmental conditions one, one encounters enormous complexity and amounts of data, besides the challenge of addressing short and long-term time intervals.

We will demonstrate our prototype software “Visual Data Intelligence” that visualizes any material represented by a digital image with new visual depth. This depth allows for virtual measuring on screen with a new degree of accuracy. It progressively reveals a clear image obviating the need for the kind of magnification that distorts.

We introduce a number of different metrics in order to achieve a new type of data representation without the loss of acuity. Our proprietary “complex data metrics” lead to the visualization of multivariate data in a novel way. They can therefore be used with the environmental sensors that take measurements in real time or at any interval. Our “image data metrics” can be applied to microscopes and telescopes or weather pictures taken at regular time intervals.

With a view to developing a fully-fledged ‘virtual measuring system’, our software architecture integrates proprietary mathematical algorithms with associated vocabularies and user interfaces that are adapted to different levels of expertise.

To prove the practical value of this software, we are looking for collaborators who would like to see it developed for their particular applications. For environmental purposes, sensor data relating to air, soil or water could be the input and as output, real time measurements could be made available on the web. .

Furthermore, our forecasting engine that is able to learn from historic data and forecast at short, medium and long term intervals, could also be included.


About Sabine Kurjo McNeill

I'm a mathematician and system analyst formerly at CERN in Geneva and became an event organiser, software designer, independent web publisher and online promoter of Open Justice. My most significant scientific contribution is now a solution to the Prime Number problem:
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