An intelligence system from India seeks to save farms
Sensor technology helps farmers adapt their crop strategies
This story is a part of the Call for Code Regional Wrap-Up Series. Read more #TechforGood stories from around the world here.
The key to survival is adaptability. Case in point, a black bear in the wilderness can recognize the onset of food scarcity during the winter months and subsequently enter hibernation as a mechanism to reduce their metabolic rate, and conserve their energy until spring. The ability to better understand your environment, and thereby adjust your response accordingly can mean the difference between life and death. The same exact statement can be made when observing the farming industry.
The unpredictable weather events and temperature fluctuations, that seem to be occurring more often, pose as the Achilles heel to farms around the world. For many farmers, trying to understand weather patterns remains a moving target — and building strategies to counter these patterns continues to be a challenge. As climate change continues to reveal itself in powerfully negative ways, the need for a solution to help an industry that is most vulnerable to its force has never shined brighter. There needs to be a way for farmers to get climate information when they need it.
Meet AI Farm, a 2020 Call for Code solution from India that serves as an intelligent system aiming to provide farmers with the information they need to adapt their crop strategies to optimize water usage and control disease. This low-cost system uses sensors to monitor ground water levels, temperature, and humidity. The data is sent to the IBM Watson IoT platform and a hyperlocal weather forecast specific to the farm is created with Node-RED flows. Learn more about the solution in the video below:
AI Farm is the source of insight for farmers around the world looking to be — and stay — prepared for the unexpected twists and turns of weather events that remain their greatest adversary. Technology is bridging the gaps where it matters most.
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