Lionel AFFOGNON

Affiliated project IoT-SDC Affiliated CEA Université Gaston Berger / MITIC & Université d'Abomey-Calavi / SMIA Title: Organoleptic qualification and nutritional and medicinal characterization of local products using an electronic robot coupled with an intelligent data classifier.

Start date : 01/08/2021

Issue :
Knowing what we are capable of producing, and understanding its economic, nutritional and sensory benefits, is of the utmost importance. All this is supported by the theory that a person's nutritional and sensory needs must be met by the resources also present in their environment. A better understanding of the potential of our local products begins with a better analysis of their nutritional and organoleptic capacity. Then, proposals for food innovation will enable people to realize the opportunity that local consumption represents.

On the other hand, the multiplication of mobile applications and services and advances in telecommunications networks are having a major impact on IoTs, due to the spectacular increase in data flows across networks. The aim of IoT is to enable as many objects as possible to communicate with each other. Each object supplies data to provide information on its status and situation. This information can be useful or not, reliable or not, and tends to saturate the network.

The question then arises as to how to manage all this data, and how to classify it so as to retain the most essential data. To deal with this situation, we believe it is necessary to insert an intelligent information processing system into IoTs. This leads us to the use of neural networks, defined as the pooling of several artificial neurons to solve a problem. This will bring greater flexibility to data quality in the Internet of Things, and further reduce human intervention.