Product extraction, Expiry date tracking, Email notification, Automation, Streamlit, sqlite3
Abstract
In the modern era with its time-constrained conditions, the management of the product stock and monitoring the expiration dates are key issues for businesses and consumers alike. Similarly, manually entering product and expiration date data is time-consuming and prone to mistakes. We suggest a future approach based on database management and image processing methods to address this problem.
Our project's objective is to automate the process of tracking expiration dates and extracting product data from photos. The system consists of multiple sub-systems, such as database design, expiration monitoring with email notifications, picture processing with Gemini API (Gemini Application Programming Interface), user registration and login, and data dictionary for expiry dates.
The user registration/login feature offers a safe method for users to access the system. Users only need to log in to the system to input photos and product information. The necessary data is extracted from the photos using a Gemini API and presented to the user for confirmation.
They can then enter the expiration dates for each product when the information has been retrieved. One is unable to enter dates that are later than the current time with such a system. The entered data is stored in the database for future review.
The system periodically searches the database for products that are approaching their expiration dates in order to provide expiration monitoring. When a product's expiration date approaches, the system automatically sends the consumer an email reminding them to use the product before it expires within ten days.
Therefore, our system is useful since it provides an intelligent and automatic solution for product management and expiration date tracking. The powerful and unfailing system ensures proper inventory management and timely use of perishable commodities through image processing, database administration, and email notification.
Article Details
Unique Paper ID: 163983
Publication Volume & Issue: Volume 10, Issue 12
Page(s): 30 - 34
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