High cost barrier01
High investment
Greenhouses, processing lines, and smart equipment are expensive, so most institutions struggle to give every student enough practice time.
Agricultural AI Training Platform for Industry-Education Integration
Build a practical smart-agriculture AI training center for vocational institutions
Escher provides vocational institutions with an integrated platform for agricultural digital twins, AI agents, course resources, and training assessment, helping schools bring real industry scenarios into the classroom.
4digital-twin industry scenarios
32+standardized training tasks
3layers of teaching, training, and enterprise collaboration access
70%standard modules plus configurable delivery
Agricultural Digital Twin AI Training CockpitTraining sync
Virtual GreenhouseClimate ControlAI Teaching AssistantQ&A and ReviewTask Work OrdersTraceable OperationsCapability ProfilesProcess Evaluation
ReplayableanomalyCourseresourcesProjectapplications
Institutional Needs
Vocational institutions do not need another slide deck. They need a real training system that can support broader program-cluster development.
Modern agriculture is moving from experience-driven management to data-driven operations, and agriculture-related majors need upgraded training conditions as well. The platform supports classroom teaching, project training, competitions, social training, and employability development.
Scenario Reproduction Challenge02
Hard to reproduce
Critical scenarios such as pest outbreaks, extreme weather, or processing-quality exceptions occur sporadically and are hard to reproduce in class.
Evaluation03
Missing process records
Traditional training often focuses only on final results, while parameter choices, decision logic, and troubleshooting paths are not fully recorded.
Industry-Education Integration04
Hard to integrate
Schools need to turn real enterprise operations into courses, work orders, grading rules, and reusable teaching outcomes.
Platform Architecture
Integrated platform capabilities built on real industry data, linking courses, training, and assessment
With digital twins and AI at the core, the platform organizes greenhouse space, sensors, work records, course tasks, and student capability assessment into reusable teaching assets.
3DGS digital twin + AI agents + data governance
Used for real-scene reconstruction, parameter simulation, anomaly drills, and industry case accumulation.
Teaching and training center + industry case center
Designed for classroom practice, project-based learning, enterprise case reviews, and regional showcase use cases.
Teacher portal, student portal, and training assessment system
Teachers assign tasks and trigger scenarios, students execute work orders, and the system generates process-based evaluation.
Course packs, task packs, case library, and assessment reports
Forms reusable, extensible, and continuously updated teaching assets.
Training Scenarios
Break the agricultural value chain into training modules that schools can teach, compete with, and use in applications
The platform supports flexible deployment based on program clusters and existing campus facilities. Schools can start with one core training scenario or expand into a comprehensive center covering cultivation, post-harvest, operations, quality control, and regional industry services.
Core scenario
Controlled-environment agriculture digital twin and climate-control training
For controlled-environment agriculture, modern agriculture, horticulture, and IoT majors.
- Greenhouse modeling, sensor mapping, and climate parameter calibration
- Growth simulation for flowers, blueberries, vegetables, and other protected crops
- AI alert interpretation plus supplemental light, fertigation, and temperature-humidity strategy drills
- Outputs control strategy sheets and anomaly review reports
AIoT foundation
Farm agent and device-operations training
Turns Nongxiaoxin into an agriculture-specific teaching foundation for IoT and intelligent manufacturing.
- Device onboarding, alert handling, task orchestration, and field troubleshooting
- Coordinated training for edge boxes, gateways, cameras, and actuators
- Outputs O&M logs, work orders, and device health reports
Cross-discipline sharing
Post-harvest grading, traceability, and supply-chain collaboration training
Connects agriculture, logistics, e-commerce, quality management, and data-analysis majors.
- Grading and traceability for flowers, blueberries, vegetables, and other agri-products
- Simulation of packaging, cold chain, loss, and fulfillment processes
- Outputs grading sheets and business-analysis reports
Focus Area
Core Product Modules
Matched Courses
Assessment Outputs
Controlled-environment agriculture
Virtual greenhouse, crop growth models, climate-control agent, and post-harvest collaboration
Protected horticulture, smart agriculture, modern agriculture, and IoT applications
Climate-control strategies, anomaly-handling reports, and project presentation materials
Medicinal crops
Planting digital twins, seed/spawn quality assessment, disease recognition, processing QA drills, and knowledge-graph AI teaching assistants
Standardized medicinal-crop cultivation, medicinal-crop processing and quality control, and medicinal-crop AI data analysis
Quality grading, disease assessment, processing parameter reports, and student capability profiles
Regional industry-education integration
Industry case library, showcase dashboard, teacher-side management, and social-training task library
Shared course clusters, extracurricular programs, dual-mentor projects, and enterprise staff training
Course coverage, trainee count, utilization rate, and application-support materials
Teaching Loop
The task system progresses by capability, helping students move from understanding to judgment
Each training task is designed around real job capabilities, covering knowledge, standard operations, parameter decisions, and anomaly handling, so teachers can record the full learning journey.
01
Cognitive
Learn the industry chain, equipment objects, crop stages, workflows, and key quality indicators.
02
Operational
Execute SOPs, complete device integration, parameter setup, image labeling, and processing-flow simulation.
03
Decision-making
Adjust climate, fertigation, pest control, or processing parameters and observe changes in yield, quality, and cost.
04
Troubleshooting
Handle device exceptions, disease risks, quality fluctuations, and order-collaboration issues, then generate review reports.
Implementation Options
Three implementation tiers for stages from course pilots to provincial demonstration bases
Based on a school's existing greenhouses, labs, program-cluster goals, and industry-education targets, the platform provides tiered options from course pilots to comprehensive bases.
Light pilot edition
Launch one AI training course first
Quick startSuitable for secondary vocational schools, standard colleges, and first-time pilot departments.
- SaaS platform accounts and case-data packs
- Basic sensing kits and teaching work orders
- Teacher training and demo-class support
Standard training edition
Build an on-campus digital-twin training center
Standard buildoutSuitable for top-tier institutions, program-cluster initiatives, and campus-base upgrades.
- Digital-twin training pods or greenhouse retrofits
- Gateways, control systems, course packs, and assessment packs
- Operations services and project showcase dashboards
Flagship base edition
Build a regional industry-education demonstration base
Joint operationsSuitable for provincial demonstration schools, vocational universities, and industry-education alliances.
- School-enterprise co-built productive training base
- Regional case library and enterprise work-order integration
- Joint certification, competitions, and social-training operations
Expected Outcomes
Make the training center truly serve teaching, program development, and regional industry
95%+student participation target
70%+per-student training cost reduction target
3xeffective training-hours target
4-6school-enterprise digital textbook target
Service Support
From solution design to classroom rollout, help schools make the platform usable and durable
Escher provides hardware-software integration, course resources, faculty training, data security, and continuous O&M services to lower the barrier to adoption.
Current-state diagnosis
Solution design
Platform delivery
Faculty training
Continuous operations
Course resources delivered with the platform
Teaching-readyProvides slide decks, task sheets, operation manuals, scoring rules, and student report templates so teachers can organize classes quickly.
Supports retrofits of existing greenhouses and labs
Manageable deploymentCan be deployed according to the school's existing site, equipment, and network conditions to reduce repeated investment.
Case library and AI capabilities keep evolving
Continuously updatedThe platform can continuously add new crops, devices, diseases, processes, and industry cases to support long-term program development.
Book a Consultation
Start with one demonstration course and build the school's own smart-agriculture AI training center
Book a platform demo. We will combine your program direction, existing training conditions, and build goals to recommend matching scenarios and rollout paths.
- For school leadership: application-ready, showcase-ready, and capable of producing flagship outcomes.
- For departments: suitable for courses, practical training, competitions, and program-cluster development.
- For teachers: low maintenance, reusable, and able to generate assessment reports automatically.
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