Pocket Agronomist: Smart Card-Based Precision Farming System

Fahim Rahman

Abstract:

Introduction: Smallholder farmers face challenges in adopting precision agriculture due to high costs, lack of digital literacy, and limited access to advanced technologies. Existing solutions such as drones, IoT devices, and satellite imaging are effective but remain impractical in resource-limited settings. This project introduces a low-cost, farmer-friendly smart card system that delivers personalized precision agronomy advice through shared community kiosks.

Methodology: 1) Each farmer receives a Smart Agronomy Card, storing soil, land, and crop data. 2) Farmers insert the card into a solar-powered kiosk/device. 3)The device integrates the following: 4)soil data, 5) satellite weather information, and 6) AI crop growth models. 7) Weekly recommendations are delivered via text, audio (local language), or printed slips. 8)The data are then aggregated to build a digital agronomy map for community-level insights.

Tools: Smart Agronomy Cards, solar-powered shared kiosks/devices, AI-based advisory software, cloud database for soil and crop records, and weather data integration APIs (Application Programming Interfaces) are all utilized in this study.

Budget (Approximately):

(1) Smart card per farmer: $2–3. (2) Shared solar-powered kiosk: $250–300 per village. (3)Software and AI integration: $2,000–3,000 (one-time purchase). (4) Maintenance and training: minimal (community-managed).

Benefit for Farmers: Personalized advice without the need for smartphones or internet, reduced fertilizer and water costs (20–30% savings), improved crop yield, reduced pest/disease losses, accessible in their local languages (which leads to trust and easy adoption), and the community model reduces individual cost burden. One kiosk can serve 50–100 hectares of farmland. For example, a village with 200 smallholder farmers (each with 0.2–0.5 ha) can all use one kiosk.

Problems: A) Farmer literacy and digital skills. B) Limited access to kiosks. C) Data accuracy and reliability. D) Infrastructure challenges. E) Farmer trust and adoption. F) Maintenance and technical support. G) Scalability.

Time: Prototype development: 6–8 months. Field testing: 1 cropping season (4–6 months). Full deployment in a region: 1–2 years.

Results: 1) Increased input efficiency and crop yield. 2) Lower production costs for smallholder farmers. 3) Creation of a digital agronomy network at grassroots level. 4)Scalable model for national and international adoption.