Microclimate audit
Evaluate temperature, humidity, VPD, hotspots, spatial compliance, and cooling response from multi-sensor data.
- • Problem map
- • Performance metrics
- • Prioritized recommendations
Areas of support
Services grounded in real facilities and real data
We do not sell one technology as the answer to every problem. Recommendations must fit the facility, data quality, operating risk, and the partner’s implementation capacity.
Sensor & IoT architecture
Design sensor placement, data acquisition, MQTT, edge–cloud pipelines, dashboards, and device monitoring.
- • System architecture
- • Sensor zoning
- • Data and dashboard flow
Climate control & AI
Assess rule-based, PID, and reinforcement-learning strategies with energy and spatial safety constraints.
- • Control baseline
- • Evaluation strategy
- • Safe test protocol
Data analysis & validation
Clean and synchronize sensor, actuator, and energy data; test claims; and communicate uncertainty.
- • Structured dataset
- • Reproducible analysis
- • Findings and limitations
Training & capacity building
Practical training in agricultural IoT, Grafana, microclimate analysis, AI/ML, and control.
- • Focused modules
- • Real case studies
- • Practice and assessment
Pilot projects & joint research
Design experiments, prototypes, field validation, publications, and proof-of-concept projects.
- • Defined scope
- • Measurable milestones
- • Documented results
Engagement models
Start with a scope that can be verified
A small pilot with clear indicators is usually more valuable than a large project built on untested assumptions.
01
Focused consultation
For design review, diagnosis, or a data-informed second opinion.
02
Dataset audit
For teams that already have sensor, actuator, energy, or dashboard records.
03
Pilot project
For testing sensing, control, dashboards, or AI before wider deployment.
04
Academic collaboration
For proposals, joint experiments, supervision, datasets, and publications.
Working process
Four steps before a recommendation is deployed
01
Frame the need
Clarify the problem, users, facility, data, risks, and target.
02
Inspect the evidence
Test data quality and assumptions before choosing a method.
03
Define the plan
Agree on scope, indicators, deliverables, schedule, and ownership.
04
Test and evaluate
Compare results with a baseline and document limitations.
Evidence
Start with findings that can be examined
Initial discussion
Describe the problem before selecting the technology
Include the facility type, primary problem, available data, intended outcome, location, and timeline.
Send a brief