Bu tez projesi ben ve arkadam Alperen Akarslan ile gelitirilmi olup 2022-2023 Bahar Dnemi sonunda Dzce niversitesi Bilgisayar Mhendislii akademisyenlerinin beenisine sunulacaktr. Projenin amac restoranlarda bulunan garson ihtiyacn kaldrmak ve bu srecin mobil uygulama zerinden hzl ve kolay bir ekilde yaplmasn salmaktr. Ayrca mterilerin oluturduklar hesaplarna ykledikleri kiisel resimlerine gre grnt ileme ve derin rneme teknikleri (CNN) kullanlarak kiiinin ya, poplasyon grubu ve ya aral zelliklerinin karmn yapmaktadr. Kararl eleme algoritmas araclyla yemek tketimi veri setimizdeki veriler ile kullancnn semi olduu favori yemekleri elemektedir ve buna gre yemek nerisini yapmaktadr.
Uygulamada restoran ve kullanc girii olmak zere iki farkl girii bulunmaktadr. Restoran sahipleri restoran hesab oluturarak kendi iletmelerini uygulamamza ekleyebilmekle beraber temel kullanc ilemleri, yemek ynetimi, iecek ynetimi, mutfak ynetimi, sipari ynetimi ve gelir ynetimini kolay bir ekilde yapabilmektedir. Kullanc ise hesabn oluturarak oturduu restoran seerek sipari verebilir, restoranda beendii yemeklerini favori listesine ekleyebilir, vermi olduu siparileri grntleyebilir, yapay zeka ve grnt ileme destekli yemek nerme sistemini kullanabilir ve temel kullanc ilemlerini yapabilmektedir.
u anda projede akll yemek nerme sistemi aktif bir ekilde almaktadr.
git clone https://github.com/akaanuzman/digital_order_system
This thesis project was developed by me and my friend Alperen Akarslan and presented to Dzce University Computer Engineering staff at the end of the 2022-2023 Spring Term. The aim is to provide the wait on the servers and to perform this operation quickly and easily via the mobile application. Based on the personal pictures they upload to their accounts, they use image processing and deep learning cost (CNN) to extract the age, entry group and age range of the person. Its stable descriptions include guidelines from our extensive food use dataset, and favorite dishes that users have chosen, and recommend meals accordingly.
Two different logins in the application, restaurant and user login. While restaurant owners can add their restaurant account to our application, they can easily perform basic user operations, food management, beverage management, kitchen management, order management and revenue management. The user, on the other hand, can buy the food he likes in the house he occupies, view the orders he has according to his favorite areas, use the artificial intelligence and image processing supported food routing system, and perform basic user operations.
Currently, the smart meal guidance system is actively working in the project.
git clone https://github.com/akaanuzman/digital_order_system