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Full-Stack Proprietary R&D · 100+ Independent IP Assets

AI Core
9-in-1 Greenhouse Brain

Over 12 years of development — nine independently developed intelligent management modules covering the full chain of smart greenhouse production, from climate-control decisions to workforce management.

Smart Modules
9 Modules · Full-Stack Intelligence
Each module independently refined; deeply interconnected through data, forming a full-lifecycle intelligent management system for greenhouses.
Climate Control
Multi-sensor fusion decision-making automatically generates the optimal control strategy for unattended 24/7 high-precision environment management.
AI Model: Built on VPD (vapour pressure deficit) theory and crop demand curves, integrating multi-dimensional parameters — temperature, humidity, light, CO₂ — to construct a multi-variable co-regulation model that computes optimal control commands in real time.
Multi-Param CoordinationWeather LinkageClosed-Loop Feedback
Fertigation
Precise water and nutrient ratio control — on-demand irrigation and precision fertilization to reduce resource waste and boost per-house profitability.
AI Model: Driven by real-time soil moisture and EC/pH data, combined with crop growth stage water and fertilizer demand models, dynamically formulates irrigation recipes — achieving precision on-demand inputs that save 30%+ water and fertilizer.
Precision FormulaAuto IrrigationProfit Analysis
Crop Growth
Periodic collection of multi-dimensional phenotypic data to build a crop digital twin, quantifying growth progress and forecasting yield 14 days ahead.
AI Model: A thermal-accumulation–growth-stage–phenotype digital twin model, collecting periodic plant height and leaf area data to quantitatively predict yield milestones — providing harvest plan support 14 days in advance.
Growth ModelingThermal AccumulationYield Prediction
Farm Operations
Converts agricultural experience into executable digital workflows, coordinating multi-house farm scheduling with traceable execution records.
AI Model: Translates expert agronomic experience into standardised digital SOPs; combines growth-stage progress to intelligently push farm scheduling — forming a traceable execution chain from assignment to completion.
Production CalendarHarvest AnalysisTraceability
Crop Management
Establishes full-batch digital records from variety selection through post-harvest shipping, supporting continuous multi-season profitability optimization decisions.
AI Model: A three-dimensional digital archive linking variety, batch, and greenhouse — connecting the full lifecycle from seedling to harvest — supporting continuous multi-season profitability comparison and variety screening decisions.
Batch RecordsHarvest TraceabilityProfitability Compare
Plant Protection
Fuses image recognition and environmental prediction models for early pest and disease warning and precision control, managing pesticide use compliance end to end.
AI Model: Fuses AI image recognition with environmental risk prediction models to complete warnings before pest or disease outbreaks; combines a compliant-use pesticide knowledge base to output precision control plans — reducing pesticide use by 40%+.
AI RecognitionRisk PredictionProtection Records
Workforce
Full-process automation of task assignment, hours calculation, and quality assessment — quantifying workforce efficiency through data to continuously optimise staffing structure.
AI Model: Task metering at its core — automatically collects farm work quantities, hours, and quality ratings to build a workforce efficiency quantification model, supporting granular payroll calculation and continuous staffing structure optimisation.
Work LoggingQuality RatingCost Accounting
Energy
Fine-grained monitoring of electricity, water, heat, and cooling — combining peak/off-peak tariff analysis to identify quantifiable cost reduction opportunities.
AI Model: Sub-meters water, electricity, heat, and cooling by category; combines equipment operating curves with peak/off-peak tariff models to automatically identify abnormal energy consumption and recommend better strategies — achieving 10%+ overall cost savings.
Energy MonitoringStrategy OptimisationAnomaly Alerts
Safety
A multi-layer protection system covering equipment health, equipment effectiveness, and environmental risk — shifting from reactive response to proactive prevention for continuous production and personnel safety.
AI Model: A three-layer protection model covering equipment health, equipment effectiveness, and environmental risk — 24/7 continuous inspection; alerts issued before anomalies occur, shifting from passive emergency response to active prevention.
Equipment HealthEnvironment AlertsEmergency Management
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