Hardware and software complex (Object recognition): SENLA, Software Engineering Laboratory IT Services project at Qualified.One

Hardware and software complex (Object recognition) by SENLA, Software Engineering Laboratory

Some details

Customer

Schlumberger Limited is the world',s leading provider of technology for reservoir characterization, drilling, production, and processing to the oil and gas industry.

Challenge

The Customer had a large number of parts in stock with minimal difference in appearance. In order to identify the parts, there was a special employee who spent a lot of time while looking for those parts in the catalog and

identifying them. The Customer wanted a mechanism that can identify those similar parts within 5 seconds and show the results immediately.

Solution and Outcome

Firstly, our team designed a prototype of a hardware complex and decided how this complex should function. It was designed for quick recognition of any unit item with its further marking. Then we picked up components, developed a model of interaction with parts that needed identification.With the help of 3 digital cameras and electronic scales, RSM-1 could recognize objects located on the platform. Artificial intelligence could recognize objects, as well as make their comparison on the coincidence in the database of nomenclature units. RSM-1 was capable of self-learning and adding new objects to the database.During the development processes, both parties had weekly status meetings where they were discussing emerging issues. Our software engineers developed a special stand and software that all together could help in the identification of manufactured parts.

Case study link:

https://senlainc.com/hardware-and-software-complex/  

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