Laundry Revolution! COSMOPlat AIoT AI Algorithm Reshapes the Intelligent Core of Washing Machines

In the wave of smart home appliances, embedded AI is evolving from being a“functional add-on” to becoming the core engine of products. COSMOPlat AIoT has made a breakthrough by embedding AI algorithms into the control system of a front-load washing machine. Through a dynamic perception–decide–optimize closed loop, it tackles long-standing industry challenges such as vibration noise and excessive energy consumption.

Traditionally, load weighing and imbalance detection in front-load washing machines rely mainly on mechanical sensors and pre-set algorithms. However, these methods face significant limitations in complex scenarios, making it difficult to model the relationship between vibration and weight accurately. By integrating AI algorithm models into embedded AI controllers, COSMOPlat AIoT introduces new solutions for load weighing, imbalance detection (OOB, Out of Balance), and diagonal imbalance detection (DOOB, Diagonal Out of Balance).

Technical Insights: AI Algorithm Model

The development of COSMOPlat AIoT’s washing machine AI model follows three key stages: data collection, model training, and model deployment.

Data Collection – The technical team simulated the rotation process using eccentric blocks and load blocks, continuously adjusting their positions and weights. Sensors such as accelerometers and motor current sensors were used to capture vibration signals and motor state data during operation.

Red - eccentric block, green - load block

Model Training – Using neural network models such as Convolutional Neural Networks (CNN) or Recurrent Neural Networks (RNN), the collected data was trained to learn the mapping between load weight, imbalance levels, and vibration signals, as well as subtle correlations with fabric types. Through large-scale deep learning, the model gained strong generalization capability, enabling it to adapt to diverse and complex scenarios.

Neural Network Training

The optimized AI algorithm model is embedded into the controller system. During real-world operation, the AI model evolves through incremental learning, iteratively upgrading without reconstructing the algorithm, thus forming a dynamic optimization closed loop.

Advantages of AI

Strong Generalization

Traditional algorithms often depend on rigid formulas or rules, which struggle to adapt to varying scenarios. In contrast, AI models, trained on large and diverse datasets, generalize well to unseen conditions. For example, during training, the model can learn from both light fabrics and heavy towels, allowing it to accurately identify different load types in actual use.

Powerful Learning Capability

AI algorithms do not require pre-defined logic rules. Instead, they directly fit the mapping between inputs and outputs from massive sample data, enabling the capture of subtle features often missed by traditional algorithms—such as how different fabric materials affect vibration signals.

Data-Driven and Rapid Iteration

AI models can be quickly updated and optimized with new data, without the need to redesign logic. This allows products to rapidly adapt to evolving market trends and user demands.

High Efficiency of Edge AI

In washing machines, AI runs on the device itself (edge side) rather than in the cloud. This ensures low latency and high efficiency. Real-time detection and control occur locally, eliminating the need for constant data uploads and cloud response delays.

Application Outcomes

In practical applications, the AI algorithm model from COSMOPlat AIoT delivers a revolutionized laundry experience:

Energy Saving & Efficiency – With precise load detection, washing programs (e.g., water level, wash time) can be dynamically adjusted, reducing energy consumption. Experimental data shows AI-enabled washing machines save around 15% energy compared with conventional models.

Improved Imbalance Detection Accuracy – AI technology enhances imbalance detection accuracy by approximately 20%.

Noise Reduction – By monitoring load distribution in real time and adjusting drum speed accordingly, AI reduces vibration and operating noise during washing.

AI Leading the Future

The application of AI in front-load washing machines demonstrates the transformative potential of artificial intelligence in traditional home appliances. Looking ahead, as AI technology continues to advance, washing machines will become even smarter—capable of automatically adjusting modes based on user habits—bringing truly human-centered smart home experiences to life.