Google-enabled app helping small farmers in India
Nearly 70 per cent of small farmers -- those cultivating fewer than three acres -- in India often find their crops damaged by unforeseen weather and pests. An even higher number, 74 per cent, lack access to farming-related information.
By : migrator
Update: 2019-09-02 10:43 GMT
New Delhi
To bridge this knowledge gap, Pune-based agritech startup AgroStar has a multi-lingual mobile app on Google Cloud Platform that is helping boost crop yields and encourage sustainable practices for small farmers in the country.
Launched as an on-premise, e-commerce platform selling farm tools in 2008, the firm turned to Google Cloud Platform (GCP) to expand its offerings.
The firm now uses Cloud-based analytics and is deploying machine learning (ML) models to provide timely advice in five languages -- from seed optimization, crop rotation and soil nutrition to pest control and commodity price forecasting to small farmers.
"Moving to the Google Cloud Platform (GCP) reduced our time to deployment including migrations. Now, we are able to do all the deployment during the day on Kubernetes clusters provided by Google," Pritesh Gudge, AgroStar, software engineer, told IANS.
The shift to Google Cloud helped the firm speed loan processing, detect crop disease and enhance supply-chain logistics.
AgroStar has reached over a million farmers through its Android app called "the AgroStar Agri-Doctor". Farmers can also follow local and national market trends that help forecast crop prices.
"Operating in Gujarat, Maharashtra, Rajasthan, Odisha, Bihar and Karnataka, AgroStar is closing the knowledge gap with a full-service, cloud-based SaaS solution -- the only one of its kind in the country," informed Gudge.
"Today, just by clicking through our Android application, farmers learn about new, effective farming practices and receive advice customized to their crop and soil," Gudge added.
AgroStar is also extending its analytics platform with AI-powered sales planning and forecasting.
Using linear regression models implemented in TensorFlow and powered by Cloud ML Engine, the capability will enhance supply chain logistics as the company scales its operations across India.
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