That digital agricultural initiative in India is celebrating the recent pilot launch of a new sowing app specifically created to help farmers know when and what to plant for their next harvest. The app is being used in conjunction with a personalized village advisory dashboard developed by Microsoft and International Crops Research Institute for Semi-Arid Tropics (also known as Icrisat). For now, the dashboard is localized to the area of Andhra Pradesh, a southeastern coastal state of India.
Through the partnership of Icrisat, Microsoft, and the Andhra Pradesh government, data is able to be collected, analyzed, and redistributed in easier-to-understand findings to improve agriculture. Together, with manually collected data from a multitude of farms across 13 districts, the Personalized Village Advisory Dashboard is able to provide information about soil health, fertilizer options, and a weeks’ worth of upcoming weather forecast. All of this information is stored in Microsoft’s Azure Cloud.
The app builds on these tools to send farmers the information they need such as a prediction of the ideal sowing week. It includes a major use of Microsoft Cortana Intelligence Suite’s, particularly in the case of Machine Learning and Power Business Intelligence. With the current pilot just recently released, users in Telugu were sent the predicted sowing date through a simple SMS system.
Anil Bhansali from Microsoft India praised the sowing application and the dashboard for providing and utilizing a large amount of information pertaining to crop failures and increased harvest yield. “This is a significant start for digital agriculture and can reap benefits in multiple ways as governments and stakeholders discover the potential for technology to unlock and offer multiple solutions for farmers,” Bhansali said according to Business Standard.
Microsoft has always been a fan of improving agricultural advancements through technology, and likely it won’t end here. With the data provided by these tools, farmers are able to understand and adapt to providing more natural food for a better tomorrow.Further reading: agriculture, Artificial Intelligence, Azure, Machine Intelligence, Machine Learning, Microsoft