NEURAL NETWORK MODEL FOR OPTIMIZED MANAGEMENT OF MEDICINES IN A UNIVERSAL FIRST AID KIT

A modified convolutional neural network model MediPackNet was developed with an accuracy of 92%, which correctly recognized all 5 test images of medicines.It showed good results at the level of 6 models based on already known ones, namely: InceptionV3, Xception, ResNet50V2, MobileNetV2, NASNetMobile and DenseNet169.In addition, AES, RSA data encryption methods and a combination of these algorithms were implemented.Based on the results of the analysis, it was concluded that hybrid encryption is the best for the developed software.A mobile application for the accounting of medicines for a universal first aid kit was created, with stable performance and the possibility for further development.The developed application has the potential to significantly facilitate the process of managing medicines stocks and contributes to more efficient use of medical resources and procurement optimization.In addition, the ability to track the course of treatment contributes to a more accurate following of medical recommendations and ensures more effective health monitoring.The use of the mobile application also has a significant impact on the environment, as it reduces the amount of hazardous waste associated with improper storage and disposal of expired medicines.