How Can Artificial Intelligence and Satellite Monitoring Advance Agriculture?

Artificial intelligence carries out major promises to drive businesses across industries. And agriculture is not an exception as the technology has the potential to revolutionize the sector from the bottom. Owing to great learning, understanding, and retorting capability to different circumstances, cognitive computing, in particular, holds the promise to become the most disruptive technology in agriculture services.

Today, the agriculture industry is undergoing a major digital revolution to meet the growing food demands of the world’s mounting population. In order to address the requirements, there are several companies along with major countries taking this into charge fulfilling the demands by introducing innovative policies and products.

In this regard, Spacenus, a Deep Learning technologies-based company, offers Artificial Intelligence-powered platforms that leverage smartphone cameras and satellite imagery for precision farming. Besides providing tailored AI-enabled solutions, the company builds and provides two products to the agricultural industry – Field boundary identification and Plant nutrient detection (PND). As Field-Boundary identification comproves automatically all the geometric data for agriculture fields as a service that are the basis for field-level digital farming, PND uses a deep learning algorithm to quantify the nutrient status in plant leaves just from a smartphone photo.

In another instance, the Maha Agri Tech project, introduced earlier this year by Maharashtra, India government, seeks out to leverage the technology to address various cultivation risks, from poor rains to pest attacks, precisely envisage crop-wise and area-wise yield and eventually to utilize this data to notify policy decisions including pricing, warehousing and crop insurance.

Initially, the Maha Agri Tech project used satellite images and analysis from the Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) in Hyderabad to analyze the acreage and the conditions of select crops in select administrative divisions. Conversely, in its second phase, various sets of data from diverse data providers will be combined to build yield modeling and a geospatial database of soil nutrients, rainfall, moisture stress, and other parameters to facilitate location-specific advisories to farmers.

Leveraging AI-enabled solutions can provide several benefits to agriculture.

Image-based Insights

In the modern agriculture landscape, precision farming is one of the most discussed areas. In this, drone-based images can assist in in-depth field analysis, crop monitoring, scanning of fields, among others. Combining computer vision technology, IoT and drone data can be useful to ensure rapid actions by farmers. And that drone image data can generate alerts in real-time to speed up precision farming.

Monitoring Health of Crops

Remote sensing solutions along with hyperspectral imaging and 3D laser scanning are indispensable to develop crop metrics across thousands of acres. The technique has the potential to bring in a revolutionary change in terms of how farmlands are monitored by farmers both from time and effort perspective. This technology will also be leveraged to monitor crops along their entire lifecycle including report generation in case of anomalies.

Thwarting Crop Devouring Insects

Destructive insects and pests have always irked farmers. However, the invention of agriculture in the future, locusts, grasshoppers, and other such crop devouring insects will still eat profits and damage grains that would otherwise feed human beings. However, leveraging AI here provides growers a weapon against cereal-hungry bugs. With AI-driven solutions, farmers can get alert on their smartphone that can help monitor their farm and protect their agricultural land from such insects.