Technology company Hewlett Packard Enterprise (HPE) said that its centre of excellence (CoE) in Chittoor, Andhra Pradesh, has helped farmers save upto 40% water, increase crop yields and remotely monitor their farms during the Covid 19 lockdown.
With internet of things (IoT)-enabled feedback on irrigation, soil treatment, nutrition and harvesting, the CoE has been helping farmers leverage technology for improved results since July last year, as per a statement.
The CoE also upskills students in IoT and programming to bring better job prospects into the community, it said.
Through HPE Pointnext Services Global Centre, the local partner of the San Jose, California-based company, students trained through the CoE programme work with IoT experts and agronomists to learn how edge-to-cloud technology can be applied to farming, it said.
“The artificial intelligence and machine learning work achieved as part of this initiative has immensely helped the local students and farming community,” Ramji Raghavan, founder and chairman, Agastya International Foundation, said.
Through the past year, the company has deployed solutions such as collection of information through drone imagining and analysis, onsite IoT modules, as well a dashboard and user interface-based devices to monitor various on-ground parameters.
The images collected from drones and satellites were used to plot normalised difference vegetation index (NDVI) with the help of HPE’s edge computing tool to demonstrate how the solution could be deployed to larger farms, the statement said.
The company also deployed deep learning analytics to allow farmers to have better visibility on the current and future soil and climatic conditions, it added.
Additionally, farmers were helped by students in the CoE programme to understand how much water to use, the right type of manure for their crops, soil moisture, leaf wetness, acidic value, temperature and humidity levels, it said. All these parameters were captured by the IoT modules, it added.
“This ensured the irrigation on the fields was based on scientific recommendations and the correct manure and fertiliser were used according to the soil type and weather conditions,” HPE said.
When these values were crunched into machine learning algorithms, farmers were able to lower water consumption by 40%, compared to traditional models, the statement added.