Smart Agriculture Management Platform
1.Intelligent Analysis: AI algorithms automatically generate management recommendations. For example, the accuracy of pest and disease identification through image recognition exceeds 90%, and the error rate for pest classification is less than 5%.
2.Multi-dimensional Visualization: A 3D GIS map integrates over 1,200 monitoring indicators, supporting real-time data and historical curve viewing on both PC and mobile devices.
3.Closed-loop Linkage: Seamless integration with water-fertilizer integration equipment and smart agricultural machinery enables full-process automation from "monitoring - early warning - adjustment".
Product Overview
A comprehensive smart agriculture management system centered on IoT, big data, and artificial intelligence technologies. It provides precision decision-making support for agricultural production through real-time monitoring and intelligent analysis of farmland moisture, crop growth, pest infestations, and disaster risks.
System Composition
1. Sensing Layer
Deploy devices including soil moisture sensors (monitoring humidity, temperature, pH, etc.), intelligent pest lamps (automatically trapping pests and capturing images for identification), weather stations (collecting wind speed, rainfall, light intensity, etc.), and HD cameras (monitoring crop growth and disasters) to form a full-domain sensing network.
Integrate drone and satellite remote sensing data to achieve "sky-ground" integrated monitoring, covering all-dimensional indicators of farmland environments and crop growth.
2. Transmission Layer
Adopt hybrid networking technology of 4G/5G and LoRa to ensure stable data transmission in remote farmland areas. Local storage supports 72-hour data caching during power outages or network disruptions.
3. Platform Layer
Based on cloud platforms and big data analysis engines, the system achieves data aggregation, visual modeling, and intelligent decision-making—for example, generating historical moisture trend graphs and predicting pest/disease outbreak patterns.
Core Functional Modules
Moisture Monitoring
Soil humidity sensors provide real-time data to guide precision irrigation and fertilization, reducing water waste.
Crop Growth Monitoring
Image recognition technology analyzes parameters such as plant height and leaf area, identifying seedling shortages, weak seedlings, and early symptoms of pest/disease infestations with alerts.
Pest Infestation Monitoring
Intelligent pest lamps automatically trap pests; AI algorithms classify and count pests to generate a pest database and recommend biological control solutions.
Disaster Early Warning
Combining meteorological data with disaster models, the system issues early warnings for droughts, floods, and other risks 72 hours in advance and seamlessly coordinates with irrigation equipment to execute disaster prevention protocols.
Key Technical Features
AI-Driven Analysis: Pest/disease identification accuracy via image recognition >90%, pest classification error rate <5%.
Multi-Dimensional Visualization: 3D GIS maps integrate over 1,200 monitoring indicators, supporting real-time data and historical trend viewing on PC/mobile devices.
Closed-Loop Automation: Seamless integration with water-fertilizer integration systems and smart agricultural machinery enables fully automated "monitoring-early warning-regulation" workflows.
