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AI for Good Innovate for Impact

4�11� Category 11: Smart Agriculture

Use Case 1: AI-Enabled Soil Analysis and Weather Station for Local Agriculture 4.11: Smart

Farmers

Country: Ghana

Organization: CSIR - Institute for Scientific and Technological Information

Contact Person(s): Dennis Agyemanh Nana Gookyi, dennisgookyi@ gmail .com, Fortunatus
Aabangbio Wulnye, Michael Wilson, John Awotwi, Yaw Twum Barimah, Paul Danquah, Roger
Kwao Ahiadormey

1 Use Case Summary Table

Item Details
Category Smart Agriculture

Problem Smallholder farmers often lack access to real-time, localized soil and
Addressed weather data, which hinders their ability to make informed decisions about
crop management. Traditional data collection methods are typically slow,
imprecise, or difficult to access, resulting in inefficient farming practices,
suboptimal resource use, and reduced agricultural productivity. This project
seeks to address this critical gap by delivering accurate, real-time soil and
weather insights to support data-driven decision-making for both farmers
and agricultural policymakers.

Key Solution Real-time soil and weather data including temperature, humidity, pH, NPK,
and rainfall are collected using fixed sensors without moving parts. This data
powers AI models that generate localized forecasts, while a TinyML-enabled
device provides on-site crop recommendations based on current soil condi-
tions. All data is visualized through Grafina dashboards and made publicly
accessible to support informed decision-making by farmers, researchers,
and policymakers.

Technology Artificial Intelligence (AI), soil analysis, weather station, real-time data,
Keywords predictive modelling, IoT, sensors

Data availability Public - The data will be available upon completion of the project

Metadata (type of Environmental data (rainfall, temperature, humidity, pressure)
data) Soil data (temperature, humidity, pH, NPK, conductivity)

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