Agriculture & Agribusiness

Artificial Intelligence for Agriculture

Optimize harvests, anticipate agricultural equipment failures, and manage your supply chain with precision based on data and computer vision.

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Before

  • ✕Manual quality inspections
  • ✕Static weather forecasts
  • ✕Reactive pest control
  • ✕Inefficient routing for perishables

With Mobizze

  • ✓Quality analysis via computer vision
  • ✓Micro-local predictive models
  • ✓Early anomaly detection
  • ✓Real-time optimized logistics

Frequent Problems Solved

Crop Waste

Losses due to diseases detected too late or harvesting at suboptimal times.

Logistical Costs

Inefficient routes in transporting perishable goods increase costs and reduce shelf life.

Labor Shortages

Chronic difficulty in recruiting staff for field sorting and monitoring.

How It Works in Practice: Workflow Example: Pest Detection & Intervention

1

Image Capture

Drones or fixed cameras capture regular images of the crops.

2

Computer Vision Analysis

The AI processes the images and identifies patterns of discoloration or early pests.

3

Targeted Alert

The system notifies the agronomist with the exact GPS coordinates of the problem area.

4

Precision Action

Treatment is applied only in the affected zone, saving chemicals and protecting the rest of the harvest.

Software & Integrations

IoT Sensor SystemsSAP AgriFleet Management SoftwareWeather APIsERP Billing Systems

Required Data

  • Historical local weather data
  • Past harvest and loss records
  • Regional pest catalog
  • Field maps and planting zones

Solution Limitations

The AI provides recommendations based on past data and images, but unprecedented extreme weather anomalies or uncatalogued pests require human agronomic analysis.

Human Validation

Approval for massive chemical purchases, structural irrigation changes, and decisions to clear crop areas always require the Agronomist's endorsement.

Implementation Estimate

4 to 6 weeks, depending on sensor installation or integration with existing systems.

Case Study

15% Reduction in Pesticide Use

"

A vineyard implemented predictive analysis for leaf humidity and temperature. Instead of calendar-based preventive spraying, the AI dictated interventions only when the risk exceeded 80%, resulting in drastic chemical savings and higher environmental certification.

Sector FAQs

Is it necessary to have drones or expensive hardware? +
Not necessarily. We can start by optimizing your distribution chain and ERP planning before moving to computer vision in the field.
Does AI work in areas with poor internet? +
Yes. Local Edge AI systems can store data and sync with the central cloud only when a connection is available.
How do you measure ROI? +
ROI is measured by the reduction in fertilizer/chemical usage, fuel savings in logistics, and a decrease in crop breakage percentage.

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