Cooking Hood Vent with Camera-Based Predictive Exhaust Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing cooking hood systems require manual control for ventilation, leading to inefficiencies such as lag in exhaust air flow rate adjustments and unnecessary energy consumption due to reactive responses to sensed air quality or temperatures.
Innovation Solution
A cooking exhaust hood system equipped with cameras and an image processing controller that monitors cooking appliances, adjusts exhaust fan speed based on detected cooking conditions, and communicates with a make-up air unit to optimize ventilation dynamically, using a trainable algorithm to recognize cooking loads and events like fires or cleaning activities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual control is used for ventilation, then the system is simple to operate, but the exhaust air flow rate cannot be dynamically adjusted to cooking conditions
Solution Approach 1:
The system performs preliminary actions by detecting cooking conditions in advance (food placement, cooking start) and proactively adjusting exhaust fan speed before air quality deteriorates. The camera-based system identifies cooking events and triggers ventilation adjustments ahead of time, eliminating lag and preventing the need for complex reactive control systems.
Solution Approach 2:
The patent replaces manual mechanical control with an automated vision-based system. Cameras capture images of cooking appliances, image processing algorithms analyze the visual data to detect cooking conditions, and this information automatically controls the exhaust fan motor speed, substituting manual operation with an intelligent automated system.
2Speed
If reactive control based on sensed air quality is used, then the system responds to cooking conditions, but lag time results in insufficient exhaust air flow rate
Solution Approach 1:
The system detects cooking conditions (food on appliance, cooking start) in advance and triggers exhaust fan speed increases before air quality parameters deteriorate. This proactive approach eliminates the lag inherent in reactive sensing, ensuring adequate exhaust capacity is available immediately when cooking begins.
Solution Approach 2:
The system implements continuous feedback by monitoring cooking conditions via camera and dynamically adjusting exhaust fan speed in real-time. The feedback loop continuously compares actual cooking load with ventilation capacity and makes immediate adjustments, ensuring exhaust air flow rate always matches cooking demands without lag.
3Reliability
If high exhaust fan speed is maintained to ensure adequate ventilation, then air quality is maintained, but energy is wasted heating or cooling make-up air
Solution Approach 1:
The system dynamically adjusts exhaust fan speed based on real-time cooking conditions detected by the camera system. Fan speed increases when cooking activity is detected and decreases when cooking stops or load reduces, ensuring ventilation capacity matches actual demand at all times, thereby minimizing energy waste in conditioning make-up air while maintaining air quality.
Solution Approach 2:
The system changes the operational parameters of the exhaust fan based on detected cooking conditions. The fan speed parameter is continuously adjusted according to the cooking load parameter detected by the vision system, creating a proportional relationship between cooking activity and ventilation capacity that optimizes energy efficiency while maintaining air quality.
4Reliability
If continuous high exhaust flow is used, then ventilation adequacy is ensured, but unnecessary energy consumption occurs during low or no cooking conditions
Solution Approach 1:
The system uses periodic monitoring of cooking conditions via camera and adjusts exhaust fan operation accordingly. The fan runs at high speed only during periods when cooking activity is detected, reduces speed during low activity, and can stop or run at minimum speed during no-cooking periods, creating a periodic operation pattern that matches cooking demands and eliminates continuous energy waste.
Solution Approach 2:
The vision-based system automatically detects cooking conditions and self-regulates exhaust fan speed without manual intervention. The system serves itself by monitoring its own operational context and adjusting ventilation capacity accordingly, ensuring adequate ventilation during cooking while automatically reducing energy consumption during non-cooking periods.
Data Source
Figure 1
Figure 2~6
Figure 7
AI summary
A cooking exhaust hood system, that has an exhaust hood adapted to be located over at least one cooking appliance and an exhaust fan connected to the exhaust hood, with the exhaust fan having a controllable exhaust air flow volume. A camera monitors a surface of the at least one cooking appliance and provide an image signal representing a visual status of the at least one cooking appliance. An image processing controller is connected to an image database and is configured to receive the image signal and to compare the visual status of the at least one cooking appliance based on the image signal to stored images in the image database. The image processing controller then output a cooking appliance status signal. An exhaust fan controller is provided that is connected to the exhaust fan. The exhaust fan controller is configured to receive the cooking appliance status signal and adjusts the exhaust fan accordingly.