Smart agriculture

CocoaMate Pro

IoT and AI-assisted monitoring from cocoa crop to fermentation and drying.

Follow cocoa conditions through three production stages in one dashboard. CocoaMate Pro brings together sensor readings, hourly history, warnings and AI-assisted guidance to help farmers and processing teams review conditions and decide what to do next.

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Specifications

Hardware, connectivity, power and expansion details.

Monitoring stages: Crop, fermentation and drying
Crop parameters: Soil moisture, soil temperature, soil pH, EC, nitrogen, phosphorus and potassium
Ambient parameters: Air temperature and humidity
Fermentation parameters: Solid temperature, slurry pH, air temperature and humidity
Drying parameters: Grain moisture, air temperature and humidity
Air sensor integration: SHT40 temperature and humidity sensor
Soil sensor integration: Seven-in-one soil sensor through serial communication
Temperature sensor integration: Dallas temperature sensor
Integration status: The described software includes placeholders for pH and grain-moisture sensor integration
Dashboard refresh: Every 60 seconds
History: Hourly records with stage, sensor values and status; date-based review
AI insights: About one minute of averaged samples; insight refresh every five minutes
Daily analysis: Selected-day history summaries and recommended actions
AI service: Gemini integration when configured; rule-based fallback when unavailable
Development mode: Simulated sensor readings for demonstrations

Core features

What it can do.

Dedicated Crop, Fermentation and Drying monitoring views
Soil moisture, temperature, pH, EC and NPK monitoring
Air temperature and humidity monitoring
Fermentation temperature and slurry pH views
Drying view for grain moisture and ambient conditions
Hourly history with date selection and daily summaries
Stage-based AI insights with rule-based fallback
PIN-based dashboard access

Suitable applications

Where it fits.

Cocoa crop monitoringFermentation monitoringDrying progress trackingFarm condition reviewProcessing historyAgricultural IoT education

Communication and interfaces

How it connects.

These are the supported hardware interfaces and protocols stated for this product.

Soil sensor connection

Serial communication connects the seven-in-one soil sensor to the device backend.

Temperature and humidity

The described backend includes SHT40 and Dallas sensor integrations. pH and grain-moisture hardware integrations remain to be completed in that version.

Device dashboard

A web dashboard reads stage-specific measurements, history and insights from the device service.

AI and local rules

Configured Gemini access provides AI-assisted guidance. Local rules provide fallback recommendations when the AI service is unavailable.

Student view

How to understand this product.

Understand how sensor measurements become useful decisions across crop monitoring, fermentation and drying. Follow a reading from the device through the dashboard, history and guidance.

What you can learn

Stage-specific sensor selection and data collection
Soil moisture, pH, EC and NPK data interpretation
Time-series logging and daily summaries
AI-assisted recommendations versus rule-based fallback
Testing simulated data before connecting real sensors

A simple project flow

Choose Crop, Fermentation or Drying to view the relevant parameters.
Read the live values and compare them with the recorded history.
Review the guidance and decide on an appropriate manual action.

Real-world applications

Example projects showing what this product can read, control and report. Each requires the appropriate sensors, connected equipment and application software.

Cocoa farm monitoring

Example: monitor soil moisture, temperature, pH, EC and NPK alongside air conditions. A farmer reviews readings and trends to identify plots needing attention and plan irrigation or nutrient checks.

Fermentation batch review

Example: follow solid-temperature readings and, with the pH sensor integrated, slurry acidity during a batch. Operators use the history and guidance to review changing conditions and decide when to inspect or turn the beans.

Drying progress tracking

Example: once grain-moisture sensing is integrated, review bean moisture alongside air temperature and humidity. Workers track drying progress, inspect unusual conditions and assess readiness against their validated process targets.