Overview
Smart farming technologies
The future of agriculture is shifting. The demand to improve food safety, quality and sustainability requires new technologies.
To increase crop yields and profitability, growers need to improve farming practices using stable internet connectivity and the big data available at their fingertips. Focusing on technological advancements that include farming equipment, crop monitoring, robotics, weather condition forecasting, communications technologies and IoT devices helps infuse crucial real-time data into decision making.
The smart farming revolution utilizes machine learning and IoT solutions that will modernize agricultural production and farming systems.
Faster decisions with smart farming technology
Make faster, smarter decisions for agriculture
As the agriculture industry moves more towards smart farming to help improve food production and farming techniques, overcoming obstacles to digital transformation is imperative. Combining the power of Artificial Intelligence (AI), data analytics and predictive insights with unique agricultural data, the expertise of food and agribusiness industry leaders and decades of IBM research is the first step.
IBM offers a suite of customized cost-effective solutions that help stakeholders make faster, more informed real time agricultural decisions.
Benefits
Increased profitability
Access insights to enable precision farming to help yield more bushels or tons per hectare across targeted crops using analytics on a variety of data types.
Improved sustainability
Gain deeper insights into factors including crop input optimization, energy consumption, land and water use, soil conservation and climate change.
Higher quality crop output
Apply unique precision agriculture data insights to generate higher quality crops such as increased protein content in barley or sugar content in beets.
Improve decisions
Improve decisions across the entire agriculture ecosystem
Smart farming automates data between stakeholders for a more transparent, connected ecosystem, driving value for non-growers:
- Food producers: Greater farm management, harvest timing and volume predictability.
- Commodities traders: Price stability with custom data collection and predictive queries.
- Agriculture lenders: Validate yield performance versus potential.
- Insurance agents: Providers can improve risk insight and claims processing.
- Governments: Refine food security and independence strategies.
