Connected farming: Putting tech to meaningful use

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Published: June 11, 2020 3:30 AM

HPE Centre enables AP farmers to increase crop yield, nutritional value and revenue

“The AI and ML work achieved as part of this initiative has immensely helped the local students and farming community,” said Ramji Raghavan, founder and chairman, Agastya International Foundation.“The AI and ML work achieved as part of this initiative has immensely helped the local students and farming community,” said Ramji Raghavan, founder and chairman, Agastya International Foundation.

Hewlett Packard Enterprise (HPE) has said that its Centre of Excellence (CoE) for IoT-based agriculture in Gudipalli, Chittoor district, Andhra Pradesh, has generated significant benefits for local farmers by enabling them to increase crop yields, nutritional value, and revenue from their produce by applying technology. The CoE announced in July last year, was designed and implemented by HPE Pointnext Services Global Customer Solution Center, Bengaluru.

The CoE is focused on upskilling students in areas of Internet of Things (IoT) and programming to improve their employment prospects and also supports local farmers to help them achieve higher food production from finite land resources. As part of this initiative, students from nearby colleges have had the opportunity to work with IoT experts from the HPE Pointnext Services Global Centre and certified agronomists on edge-to-cloud technology.

“The AI and ML work achieved as part of this initiative has immensely helped the local students and farming community,” said Ramji Raghavan, founder and chairman, Agastya International Foundation.

The solutions included edge compute (HPE Edgeline EL300), onsite IoT modules, drone imaging and analysis, a user interface and dashboard for monitoring and reporting of various on-ground parameters and activities at the fields. Images from drones and satellites are used to plot NDVI (normalised difference vegetation index) to demonstrate how it can be applied when scaled to larger farms.

The technology and deep learning analytics were deployed to improve the farmers’ decision-making capabilities by providing them visibility into the current conditions of soil and by modelling possible future trends. The machine learning algorithms were used to test the soil conditions resulting in approximately 40% savings in water consumption when compared to traditional methods.

The CoE, which currently covers 2.5 acres of land, also helped the farmers during the Covid-19 pandemic lockdown by enabling them to remotely monitor the crops and make decisions related to the irrigation, soil treatment, nutrition and harvesting without the need to visit the fields.

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