Hi, Mr. Jaiswal,

I'm involved in a AI project. So I can recommend you:

https://www.mm-network-ing.de/

The Dres. speak English.

Try your luck.

Regards

Matthias G. Bumann

Very interesting question. Hyperspectral sensors look at objects using a vast portion of the electromagnetic spectrum. Certain objects leave unique 'fingerprints' in the electromagnetic spectrum. Known as spectral signatures, these 'fingerprints' enable the identification of the materials that make up a scanned object. This technology is continually becoming more available. Organizations such as NAZA have catalogs of various minerals and their spectral signatures and have posted them online to make them readily available for researchers. Geological samples, such as drill cores can be mapped for nearly all minerals of commercial interest with hyperspectral imaging. So theoretically speaking this can be done for concrete. But there are limitations: you are getting 2-D information and can be missing stereological effects; you will also need to acquire training data so that deep learning can link input images to outputs specific to cement-based materials.

Dear Aman Jaiswal.

Hyperspectral sensors look at specimen utilizing a tremendous segment of the electromagnetic range. Certain items leave interesting 'fingerprints' in the electromagnetic spectrum. Thus, the 'fingerprints' can be used to identify materials such as concrete, cement. Nevertheless, research- work must be carried out, protocols established concerning the application in concrete. Besides, i found the link below given by Matthias very useful.

https://www.mm-network-ing.de/

Thank you