Embedded artificial intelligence application development proposed for a perfume engineering database treatment

Nowadays, databases are very useful for saving or registering data, information or events. Forecasting studies, autonomous decision-making control system became more accurate and easy to implement since databases had been invented. Artificial Intelligence applications show more and more effective when it comes to solving problems conventional computational algorithms cannot handle. They also show to be useful when the problem’s exceptions are unknown or cannot be easily determined. This paper also summarizes the programming and hardware platform choice process, in order to develop an AI application for treating Fragrantica’s perfume engineering unstructured database, by storing its information within structured XML documents and database. The platform choices were performed through special issues based available technologies comparative analysis. The developed AI application shall provide automatic retrieval of data from Fragrantica database, making possible the use of its information for perfume engineering related AI training. The main expected contributions are the converting procedures developed in order to turning unstructured data, as images and text, into XML structured documents which shall be extensible enough to support different context solutions.