Case Study

SmartFarm — Precision Agriculture

IoT sensor network and ML analytics to optimize irrigation and crop health.

Problem

Small and medium farms lacked affordable tools to monitor soil health and water use, leading to waste and suboptimal yields.

Approach

We designed robust, low-power sensor nodes and a cloud analytics pipeline that delivers actionable irrigation recommendations to farmers via SMS and a dashboard.

Solution

  • LoRaWAN-enabled soil moisture and microclimate sensors.
  • Time-series ML models to detect stress and predict irrigation needs.
  • Farmer-facing dashboard and SMS alert system for remote management.

Outcome

  • Average water use reduced by 30%.
  • Cultivar yields increased by 18% in the pilot season.
  • High engagement from local farmer cooperatives.

Tech Stack

Embedded C, MQTT/LoRa, Python, InfluxDB, Grafana, AWS Lambda for analytics.