Since the 1990s, the value of data has been recognized as surpassing that of the hard drives it is stored on. There has been a persistent need for technology that can predict hard drive failures and provide relatively safe data protection. Current industry practices use threshold judgment methods to analyze S.M.A.R.T (Self-Monitoring, Analysis, and Reporting Technology) data of well-functioning disks. However, these methods often suffer from low accuracy, unclear real disk conditions, and insufficient emphasis on potential failures.

In response to the growing demand for portable data sets and expectations for data security and stability, our organization has developed the S.M.A.R.T Disk Array Failure Prediction System. This system leverages genetic algorithms, Temporal Convolutional Network (ECN) and transfer learning to enhance the prediction of disk failures.

• Advanced Monitoring 📊: Monitors various hard disk attributes such as data throughput performance, and motor startup time, and seeks error rate against standard values.
• Weighted Impact Analysis ⚖️: Sets different weights according to the impact of each attribute, addressing the issue of data imbalance.
• Feature Selection with Genetic Algorithm 🧬: Utilizes Genetic Algorithm to automatically select the most relevant features for prediction based on the recent period.
• Advanced AI Algorithms 🧠: Utilizes TCN (Temporal Convolutional Network) for incremental iterative training.
• Transfer Learning 🔄: Adapts the model across different disk models from the same manufacturer, reducing the number of models that need to be trained while ensuring high predictive accuracy.

• Enhanced Prediction Accuracy 🎯: Provides finer predictions of disk lifespan and potential failures.
• Adaptability 🛠️: Generalizes across various models, significantly broadening the usability of the system.
• Data Security 🔒: Enhances the safety and stability of data storage.

The S.M.A.R.T Disk Array Failure Prediction System has a wide range of applications, from corporate data centers to individual users who value data integrity. Its ability to predict failures before they occur helps in proactive data management and reduces the risk of data loss.

To begin using the S.M.A.R.T Disk Array Failure Prediction System, please follow the steps below:

1. Installation 💿

   • Ensure your system meets the hardware requirements.
   • Install Docker on your system. You can follow the official Docker installation guide for your specific operating system.
   • Clone our repository using git clone <repository_url>.
   • Navigate to the cloned repository directory.
   • Build the Docker image using docker build -t <image_name> ..
   • Run the Docker container using docker run -d -p <host_port>:<container_port> <image_name>.

2. Configuration ⚙️

   • Configure the system settings according to your disk array setup.
   • Adjust the attribute weights as necessary for your specific hardware.

3. Monitoring 🖥️

   • Start the system to monitor the health of your disk arrays.
   • Regularly check the prediction reports for any signs of potential failures.

For more information, and support, or to provide feedback, please visit our support page or contact our helpdesk at lrt2436559745@gmail.com. We are committed to continuously improving our systems and appreciate your input.

• Website Maintainers: Phillweston
• Documentation Maintainers: TommyVCT
• Machine Learning Project: Phillweston and TommyVCT and MichaleDS
• Dashboard Development: Waiting for the member to be assigned
• Backend Service: Phillweston
• Marketing: Waiting for the member to be assigned

Interested in contributing? We welcome contributions from the community. Please refer to our contributing guidelines in the repository for more information on how you can contribute to the development of the S.M.A.R.T Disk Array Failure Prediction System.

Thank you for choosing our system to ensure the safety and longevity of your data storage. 🙏