KR-20260065388-A - AI-based fan speed control method according to indoor air quality and temperature in workplaces such as kitchens

Abstract

The present invention relates to an artificial intelligence-based fan speed control method for maintaining air quality and temperature inside a kitchen or other workplace, and to a technology for managing temperature, humidity, and air quality within the workplace by comparing with data obtained through external public data. The artificial intelligence-based fan speed control method according to the present invention, which responds to indoor air quality and temperature in a kitchen or other workplace, identifies and matches a sensor ID to connect with a device and uses a wireless communication protocol to receive detected result values from a sensing unit that measures temperature and humidity, an end effector (EOAT) equipped at the end of a cooking appliance or work robot, and a sensing unit that detects harmful substances such as fine dust, leaked gas, and oil vapor generated from at least one of a gas stove, induction cooker, hot plate, oven, or microwave oven. By analyzing the above result values with current external public temperature and humidity data, measures such as activating a dust collection filter as an option or providing an alarm to a user terminal are taken to reduce the pollution level of the workplace, while simultaneously adjusting the fan speed in stages to efficiently use energy and manage workplace air quality, including the dust collection filter and ventilation fan operating unit and the sensing unit. It includes a control unit that performs wireless communication between an artificial intelligence-based control unit and the workplace air quality management server.

Inventors

• 이혜은

Assignees

• 이혜은

Dates

Publication Date

20260508

Application Date

20241101

Claims (4)

1. An artificial intelligence-based fan speed control method in response to indoor air quality and temperature in a kitchen or other workplace, comprising: a first step of detecting hazardous air quality and temperature and humidity inside the workplace; a second step of determining whether to control hazardous air quality and ambient temperature inside the workplace; a third step of determining a fan speed that minimizes power consumption by considering the hazardous air quality inside the workplace, external air quality and temperature and humidity conditions, data amount, average data amount, and internal temperature correlation; and a fourth step of controlling the speed of a ventilation fan according to the determined fan speed.
2. An artificial intelligence-based fan control method according to claim 1, characterized in that the determined fan speed returns to the first step according to a value set as a threshold of time, etc. and harmful substances.
3. An artificial intelligence-based fan control method according to claim 1, characterized in that the target temperature of the second stage is determined by calculation through air quality state control.
4. An artificial intelligence-based fan control method according to paragraph 2, wherein the third step is characterized by lowering the speed from the uppermost speed of the fan and lowering it by a certain ratio during idle/waiting time.

Description

AI-based fan speed control method according to indoor air quality and temperature in workplaces such as kitchens The present invention relates to a method and system capable of controlling the speed of a fan according to changes in hazardous air quality and temperature at a work site to maintain the performance of an indoor workplace. Specifically, it relates to a method and system capable of minimizing power consumption while maintaining an optimal temperature for normal operation of the workplace by adaptively controlling the fan speed according to the temperature and conditions of the workplace. Dining out and institutional catering are services that provide meals to a large number of people. Cooking fumes from kitchens contain harmful compounds such as benzene, polycyclic aromatic hydrocarbons, and aldehydes. As the number of users increases, the volume of food to be prepared also increases; therefore, the energy consumption and number of personnel required may vary depending on the scale of the service. Management is necessary for this, and periodic hygiene inspections of the workplace are conducted to prevent food poisoning, maintain food hygiene, and protect the health of workers. As the volume of food ingredients, such as meat, being grilled or steamed increases to provide large-scale meals in the workplace, significant heat is generated by gas stoves, leading to increased energy consumption. If this heat generation intensifies and indoor temperatures rise excessively, workers experience increased fatigue and decreased work efficiency; furthermore, severe cases may result in industrial accidents such as pulmonary nodules, lung cancer, and suffocation. Amidst increasingly severe extreme heatwaves, it is necessary to operate fans to maintain normal levels of harmful air, temperature, and humidity to manage freshness and keep the workplace comfortable, thereby minimizing risks of spoilage for workers and food. It has been proven through various papers and meta-analyses that exposure to cooking fumes increases the risk of lung cancer by 1.74 times, and the impact of the presence or absence of ventilation equipment is 2.11 times greater. To reduce the risks associated with cooking oil smoke exposure for non-smoking female workers in China, Taiwan, and Korea, employers need to take immediate measures to minimize potential health and safety risks by removing the causative substances of involuntary daily exposure from contaminated workplaces. This involves installing ventilation equipment in workrooms, using air collection filters, and controlling temperature and humidity, while additionally controlling parameters for various emission sources to identify various hazardous gases and substances through sensor measurements including PM measurement using portable aerosol monitors, offline VOC sampling, and analysis using TD-GC/MS, thereby minimizing chronic exposure. Accordingly, the present invention aims to solve the problems described above by providing a cooling fan control method that minimizes power consumption and maximizes data processing efficiency by taking into account the situation and conditions of the workplace. In addition, the present invention aims to provide an AI-based air-cooled fan control method that controls temperature by setting target values according to the conditions of the workplace, so that workplaces with different conditions can each achieve maximum efficiency. Figure 1 is an example of a ventilation fan at an actual work site. FIG. 2 is a block diagram of a system for performing an artificial intelligence-based fan control method according to one embodiment of the present invention. FIG. 3 is a process flowchart of an artificial intelligence-based fan control method according to an embodiment of the present invention. FIG. 4 is a wiring diagram of an artificial intelligence-based fan control method according to an embodiment of the present invention. Hereinafter, an "artificial intelligence-based fan speed control method in response to indoor air quality and temperature in a kitchen or other workplace" according to the present invention will be described in detail with reference to the attached drawings. The embodiments described are provided to enable those skilled in the art to easily understand the technical concept of the present invention, and the present invention is not limited thereby. Furthermore, the details depicted in the attached drawings are schematic drawings intended to easily explain the embodiments of the present invention and may differ from the actual forms implemented. Meanwhile, each component described below is merely an example for implementing the present invention. Accordingly, in other embodiments of the present invention, other components may be used within the scope of the spirit and scope of the present invention. Furthermore, each component may be implemented purely as a hardware or software configuration, or it may be implemented as a combination