Management public pour l'identification de la population congolaise : application d'un modèle d'intégration biométrique trimodale de reconnaissance

La RDC est butée à des problèmes importants liés à l'identification de sa population pour mieux planifier son développement par manque d'une politique cohérente en la matière. Le débat actuel dans la société congolaise est de savoir qui est congolais et qui ne l'est pas ?

The Democratic Republic of Congo (DRC) faces significant challenges related to the identification of its population, which hinders effective development planning due to the lack of a coherent policy in this area. A key debate within Congolese society today revolves around the question: Who is Congolese and who is not? This issue arises across public administration, both public and private enterprises, as well as within defense and security institutions. This article analyzes the issue of population identification in the DRC and proposes the integration of a multimodal biometric recognition model for individual identification. This innovative approach incorporates multimodal biometric systems based on three biophysical and biochemical parameters to achieve more accurate identification of the Congolese population. The proposed model combines the use of multimodal biometric technologies— fingerprint recognition, iris scanning, and DNA testing—with the development of an identification management software system and the creation of an operational database hosted on the web. This solution aims to significantly enhance the efficiency and performance of administrative functions in the Democratic Republic of Congo, particularly in terms of population identification and authentication. The multimodal biometric data collected would be stored in an operational database accessible through various devices such as tablets, laptops, and smartphones, using virtual addressing systems. The tools of the multimodal identification system proposed and analyzed in this article provide added value to population identification management, with a particular emphasis on DNA testing first, followed by iris recognition and fingerprint identification. The multimodal biometric model is based on the fusion of iris and fingerprint data, combined with the genetic parameter (DNA testing).