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GlovIris

The context

Every year in Africa, millions of farmers lose part of their harvests.
The reason? A lack of reliable information about their soil and delayed diagnosis of plant diseases.

Yet the land is fertile. The know-how exists. What’s missing is a smart, accessible, and tailored tool.

That’s where GlovIris comes in.
A mobile app built for precision agriculture in Africa : offline-first, low-cost, and grounded in the reality of the field.

What is GlovIris?

GlovIris is a mobile application designed to empower African farmers by giving them instant, offline access to critical agricultural insights.

In a continent where over 60% of the population depends on agriculture, smallholder farmers often operate "in the dark", without soil analysis, without technical guidance, and without modern tools.

GlovIris addresses this gap by offering simple, intelligent features tailored for use even in remote, low-connectivity regions.

Key Features

1. Plant Disease Diagnosis

From the "Plants" tab, users can:

Take a photo or an instant video of a sick leaf, fruit, vegetable or crop with their smartphone
Get an instant diagnosis, thanks to on-device AI using computer vision
Receive clear recommendations on treatment or mitigation steps

No more waiting for an expert : GlovIris puts the solution directly in the farmer’s hands.

2. Soil Quality Analysis

Using a Bluetooth-connected IoT sensor device (based on Arduino), GlovIris collects and analyzes:

Soil moisture, pH, temperature, and conductivity
Determines soil fertility
Recommends the best-suited crops for that plot

A simple yet powerful way to maximize every square meter of land.

3. User Settings & Management

From the "Settings" tab, users can:

Access diagnosis history
Change language preferences
Manage user profiles
Synchronize data when a connection is available

GlovIris adapts to the user's pace, context, and language.

Why We Built It

We were driven by:

The untapped potential of African agriculture
The technological gap faced by rural farmers
The heavy crop losses due to undiagnosed diseases
The misuse of fertilizers and costly inputs

We wanted to bridge the tech divide and make AI useful where it’s most needed.

How We Built GlovIris

General Architecture

Mobile App: Flutter (offline-first)
Backend : Django
IoT Module: ESP32 + sensors (moisture, pH, temperature, conductivity)
AI models based on African agricultural data and crops for :
- Plant diagnosis
- and Soil fertility

Core Capabilities

Real-time disease detection via smartphone
Soil-based crop recommendations
Fully offline
Multilingual and intuitive UI, even for semi-literate users

Challenges We Faced

Collecting reliable african field data to train robust AI models
Optimizing AI for low-resource, local execution
Ensuring sensor reliability under extreme environmental conditions
Designing for inclusive usability, especially in low-literacy contexts

What’s Next for GlovIris?

Expand to more African regions
Partner with NGOs, agricultural institutes, and cooperatives
Add local languages and dialects
Enrich the disease and soil knowledge base
Satellite vision for wider analysis
Integrate future modules (weather, satellite, drone data)

We believe every farmer deserves tools to make smart decisions.

We believe that innovation must be inclusive.

GlovIris – Smart farming. African roots. Global impact.