SMART FOOD WASTE MANAGEMENT ORGANIZER
RAJASULOCHANA S (ASSISTANT PROFESSOR), ABHISHEK BABU P S, KISHOORKUMAR K, MEGHAPREETHI K G, RATHNAGIRISHWAR S, SURAJ KONGAN SHIV
(INFORMATION TECHNOLOGY)
SNS COLLEGE OF TECHNOLOGY, COIMBATORE, TAMILNADU, INDIA
ABSTRACT:
Food waste is a significant problem in the hospitality industry, especially in hotels where large amounts of food are prepared and served daily. The aim of this paper is to describe a machine learning approach to food waste management in hotels. The proposed system involves using a neural network to predict the amount of food that will be wasted each day, based on data collected from various sources such as food orders, inventory and kitchen waste. The system also includes a feedback loop to adjust food production based on predicted wastage. The results of the project show a significant reduction in food waste, which leads to cost savings and environmental benefits. This research shows innovative ways to deal with uncertainty in production planning using modern operations research methods. These tools improve classical methods and provide production managers with valuable information to assess the economic benefits of improved machinery or process control. As a result, accurate predictive models can potentially improve the profitability of food companies as well as reduce their environmental impact.
In recent years, a sharp gradual increase in food waste can be observed. According to the Food and Agriculture Organization, one-third of the food produced by humans for human consumption is wasted worldwide, which is almost 1.3 billion tons per year, on the other hand, twenty percent of people in the entire population seriously struggle for food. food shortages according to the World Health Organization report. This web application helps collect food from donors and distribute it to people in need. This is the basic concept and main goal of this project. The proposed scheme is to create an outline that contains general information for solving similar kinds of problems. With just a few initiatives, we were able to reduce food waste in our hotel.
