Precision Agriculture for Development (PAD) is adapting precision agriculture technologies for developing countries. We are developing an intelligent platform that provides smallholder farmers with individualized agricultural recommendations through their mobile phones. Through environmental monitoring, weather forecasting, satellite imagery, remote sensing, and machine learning, PAD’s platform makes personalized recommendations that improve production and increase profit for farmers.
PAD’s technology is always evolving. In addition to dispensing advice, the platform also gathers and incorporates information from farmer inputs, ensuring its recommendations continuously improve.
Our mission is to sustainably improve the livelihoods of 100 million smallholder farmers and their families through providing highly customized, practical and affordable information and advice on how to improve farm productivity, profitability and environmental sustainability.
PURPOSESmallholder farms support more than two billion people worldwide, but many rely on inefficient and environmentally unsustainable agricultural practices. Localized information can greatly improve production, reduce unnecessary fertilizer and pesticide and increase profit, yet smallholder farmers often face barriers to accessing that information such as:
High Costs: Localized quality information can be prohibitively expensive.
Ineffective Providers: Private sector actors often stand to profit from providing inaccurate information, while public sector agricultural extension efforts tend to be dysfunctional.
Lack of Personalization: Increased access to mobile phones has led to a number of successful agricultural initiatives, but few focus on delivering context-relevant, localized, and customized information.PAD’s platform presents a scalable solution that seeks to solve these problems. Using two-way communication and information aggregation, PAD’s platform provides targeted predictions of optimal local farming practices given a participant’s crops, local soil and weather conditions, socioeconomic characteristics, labor supply, access to inputs, and other variables.
These inputs, combined with direct communication and experimentation with farmers, will help build a data set of unprecedented richness that allows for not only an improvement of the information available to farmers, but also our understanding of information-finding systems.
Several studies have found that small changes in agricultural practices can substantially improve their farming productivity and profitability, dramatically improving the lives of some of the world’s poorest populations. In India, mobile-based IVR agriculture advisory service with 1,200 cotton Gujurat showed a 26% increase in yield, a 30% reduction in pesticide/fertilizer usage, and an estimated return of $10 per $1 USD invested. In Kenya, an SMS messaging system with agricultural advice for smallholder sugarcane farmers increased yields by 11.5% and supported two-way communication to reduce delivery delays for fertilizer by 22%.