AgriBrain

AgriBrain is a cloud-native smart agriculture platform based on Spring AI Alibaba, JDK 17, and Alibaba Cloud ACK (Container Service). It integrates DeepSeek Large Model, Milvus Vector Database, and Nebula Graph Database to provide precise farmland management, crop prediction, pest and disease detection, and intelligent decision support. It supports local container deployment and cloud-native AIOps, enabling flexible deployment both on-premise and in the cloud, with AIOps technology for intelligent operations management.

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Features

• Farmland Management: Provides accurate farmland environment monitoring and management recommendations, helping farmers efficiently manage their land.
• Crop Prediction: Predicts crop growth trends, harvest outcomes, and potential risks based on big data and deep learning technologies.
• Pest and Disease Detection: Uses deep learning and computer vision to automatically detect pests and diseases, offering precise control measures.
• Intelligent Decision Support: Combines agricultural domain knowledge with graph databases, providing scientific decision support based on large models.
• Cloud-Native Architecture: Implements containerized deployment on Alibaba Cloud ACK, supporting high scalability and high availability.
• Local Container Deployment: Supports local deployment and management using Docker and Kubernetes, facilitating development and testing.
• AIOps: Leverages cloud-native AIOps technologies for intelligent monitoring, fault diagnosis, performance optimization, and automated operations management.

Tech Stack

• Spring AI Alibaba: Integrates Alibaba Cloud AI services, providing efficient AI algorithms and services.
• JDK 17: Uses the latest version of Java (JDK 17) to build the backend application, offering better performance and modern features.
• Alibaba Cloud ACK (Container Service): Utilizes Alibaba Cloud ACK for cloud-native deployment, supporting automated containerized application management and elastic scaling.
• DeepSeek Large Model: Leverages the DeepSeek large model platform for training and inference of agricultural-related models, enhancing predictive capabilities.
• Milvus Vector Database: Uses Milvus for storing and efficiently retrieving large-scale vector data, supporting similarity search.
• Nebula Graph Database: Uses Nebula to build knowledge graphs in the agricultural domain, analyzing complex relationships between farmland data.
• Docker & Kubernetes: Supports local containerized deployment, and Kubernetes for cloud-native container orchestration.
• AIOps: Integrates AIOps technologies to optimize system monitoring, alerting, log analysis, and fault resolution.