Neural-Network-Based Time Control for Microwave Oven Heating of Food Products Distributed by a Solar-Powered Vending Machine with Energy Management Considerations
Author:
Savaniu Ioan Mihail1, Chiriță Alexandru-Polifron2, Tonciu Oana1, Culcea Magdalena3, Neagu Ancuta1ORCID
Affiliation:
1. Faculty of Mechanical Engineering and Robotics in Construction, Technical University of Civil Engineering Bucharest, 59 Plevnei Str., 010223 Bucharest, Romania 2. National Institute of Research & Development for Optoelectronics/INOE 2000, Subsidiary Hydraulics and Pneumatics Research Institute/IHP, Cutitul de Argint 14, 040558 Bucharest, Romania 3. Faculty of Building Services, Technical University of Civil Engineering Bucharest, 66 Pache Protopopescu Blvd., 020396 Bucharest, Romania
Abstract
This article presents novel research on the utilization of a neural-network-based time control system for microwave oven heating of food items within a solar-powered vending machine. The research aims to explore the control of heating time for various food products, considering multiple variables. The neural network controller is calibrated through extensive experimentation, allowing it to accurately predict optimal heating times based on input parameters such as food type, weight, initial temperature, water content, and desired doneness level. The results demonstrate that the neural-network-controlled microwave oven achieves precise and desirable heating durations, mitigating the risk of overheating and ensuring superior food quality and taste. Moreover, the solar-powered vending machine showcases a commitment to sustainable energy sources, effectively reducing dependence on non-renewable energy and minimizing greenhouse gas emissions. To maintain food quality and freshness, a food refrigeration unit is integrated into the vending machine, employing load-balancing technology to control the refrigeration chamber’s temperature effectively. Energy efficiency is prioritized in both the refrigeration unit and the microwave oven through intelligent algorithms and system optimization. The combination of a neural-network-controlled microwave oven, a solar-powered vending machine, and a food refrigeration unit introduces a novel and sustainable approach to food preparation and energy management.
Funder
Competitiveness Operational Program European Regional Development Fund
Subject
Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous),Building and Construction
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