Smart Home Appliances

Home control and information security Smart home appliances learn to adjust to lifestyles constantly. Nuvoton technology and integrated applications enable devices to connect and communicate to detect, track, and control energy consumption and costs, air quality, lighting, access control, and information security, and the entire home can operate as a fully integrated system.

Applicable Development Board
NuMaker-HMI-MA35D1-S1	Smart Refrigerator Content Recognition and Management Install a camera inside the refrigerator to capture food and drinks. MA35D1 processes the image data from the camera and uses image recognition technology to classify the items in the fridge, such as fruits, vegetables, beverages, and dairy products. Intruder classification of smart security cameras: Deploy smart security cameras in the home environment to monitor home security. MA35D1 processes the image data captured by the camera and uses advanced image recognition technology to classify the captured objects, such as distinguishing between family members, pets, and potential intruders.
NuMaker-HMI-M467 NuMaker-IoT-M467	1. Vibration detection Example: Home appliance health monitoring Use vibration sensors to monitor the operating status of home appliances such as washing machines or air conditioners. Cortex-M4 processes sensor data analyzes the vibration patterns generated by the appliance during operation and detects whether the machine is operating normally. When the vibration pattern is abnormal, such as excessive or irregular, the user is prompted to check or repair it. 2. Sensor fusion Example: Smart security system Combines multiple sensors, such as door and window magnetic sensors, infrared sensors, and smoke sensors, for home security monitoring. Cortex-M4 analyzes the combined data from these sensors to provide more accurate security alerts. When abnormal conditions such as unauthorized intrusion or fire are detected, the system can automatically alarm and notify the user.
NuMaker-M55M1	1. Vibration detection Using the M55M1 development board's high-precision analog-to-digital conversion function and powerful data processing capabilities, vibration detection of home appliances can be achieved. This can be applied to predictive maintenance, such as detecting unbalanced operation of a washing machine or abnormal vibration of a refrigerator compressor. By timely detecting and analyzing these vibration data, equipment failures can be prevented, and their service life can be extended. Sensor fusion: The M55M1 development board can simultaneously process data from multiple sensors, such as temperature, humidity, light, and motion. Using this sensor data helps create more intelligent and responsive home appliance systems. For example, combining data from different sensors in an air purifier can more accurately control air quality and automatically adjust device settings to adapt to the room's environment. 2. Anomaly detection The M55M1's machine learning capabilities can enable real-time anomaly detection of smart home appliances. For example, in a smart oven, the system can identify abnormal temperature changes or smoke generation during cooking and take timely measures, such as turning off the heating element or sounding an alarm. This anomaly detection helps prevent accidents and improves user safety. Object classification: The image processing capabilities of the M55M1 development board enable object classification functions in smart home appliances. For example, in a smart refrigerator, the system can identify and classify stored food through a built-in camera and image recognition technology and provide expiration reminders or recipe suggestions. This not only improves ease of use but also helps reduce food waste.

Applicable Development Board

NuMaker-HMI-MA35D1-S1

Smart Refrigerator Content Recognition and Management

Install a camera inside the refrigerator to capture food and drinks. MA35D1 processes the image data from the camera and uses image recognition technology to classify the items in the fridge, such as fruits, vegetables, beverages, and dairy products.

Intruder classification of smart security cameras: Deploy smart security cameras in the home environment to monitor home security. MA35D1 processes the image data captured by the camera and uses advanced image recognition technology to classify the captured objects, such as distinguishing between family members, pets, and potential intruders.

NuMaker-HMI-M467

NuMaker-IoT-M467

1. Vibration detection

Example: Home appliance health monitoring Use vibration sensors to monitor the operating status of home appliances such as washing machines or air conditioners. Cortex-M4 processes sensor data analyzes the vibration patterns generated by the appliance during operation and detects whether the machine is operating normally. When the vibration pattern is abnormal, such as excessive or irregular, the user is prompted to check or repair it.

2. Sensor fusion

Example: Smart security system Combines multiple sensors, such as door and window magnetic sensors, infrared sensors, and smoke sensors, for home security monitoring. Cortex-M4 analyzes the combined data from these sensors to provide more accurate security alerts. When abnormal conditions such as unauthorized intrusion or fire are detected, the system can automatically alarm and notify the user.

NuMaker-M55M1

1. Vibration detection

Using the M55M1 development board's high-precision analog-to-digital conversion function and powerful data processing capabilities, vibration detection of home appliances can be achieved. This can be applied to predictive maintenance, such as detecting unbalanced operation of a washing machine or abnormal vibration of a refrigerator compressor. By timely detecting and analyzing these vibration data, equipment failures can be prevented, and their service life can be extended. Sensor fusion: The M55M1 development board can simultaneously process data from multiple sensors, such as temperature, humidity, light, and motion. Using this sensor data helps create more intelligent and responsive home appliance systems. For example, combining data from different sensors in an air purifier can more accurately control air quality and automatically adjust device settings to adapt to the room's environment.

2. Anomaly detection

The M55M1's machine learning capabilities can enable real-time anomaly detection of smart home appliances. For example, in a smart oven, the system can identify abnormal temperature changes or smoke generation during cooking and take timely measures, such as turning off the heating element or sounding an alarm. This anomaly detection helps prevent accidents and improves user safety. Object classification: The image processing capabilities of the M55M1 development board enable object classification functions in smart home appliances. For example, in a smart refrigerator, the system can identify and classify stored food through a built-in camera and image recognition technology and provide expiration reminders or recipe suggestions. This not only improves ease of use but also helps reduce food waste.

More to explore:

Smart Sweeping Robot

Robotic vacuum cleaners can move around on floors, detect obstacles and surface changes, and intelligently return to their charging stations to recharge.

Smart Washing Machine

Washing machines are required to clean clothes more efficiently and ensure higher safety and lower noise levels while minimizing energy, water, and detergent consumption.

Smart Coffee Machine

Coffee machines typically feature sleek touchscreen interfaces and integrate elements like high-pressure water pumps, grinders, and solenoid valves.

Smart Food Processor

Intelligent food processors can shred vegetables, grind, and juice. Also, they can process fish meat into segments, grind, and even stir and cook to complete multiple steps in a recipe.