Research & Student Innovation

Agriculture Projects

AI, machine learning, sensors and IoT-driven projects focused on precision agriculture, soil monitoring, crop protection, plant health and sustainable farming.

01

Agr-E

AI-autonomous agricultural rover concept designed to support crop selection, soil analysis, crop growth monitoring and intelligent farm management.

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Team Members:
Kunal Badgali, Basavraj Chinagundi, Aaryan Arora, Megha Singh, Rishab Aggarwal, Rishabh Kumar

Salient Features

  • Multiple high-precision nutrient sensors for soil composition analysis and data collection.
  • Machine-learning-based analysis of soil composition and nutrient conditions.
  • Camera-based identification and selective spraying of undesirable weeds.
  • Estimation of the expected period required for crop growth.
  • Generation of soil moisture and nutrient-content maps for field-level analysis.
02

AgriFarmsGo

Smart irrigation and farm-monitoring system designed to support efficient water management and provide farmers with real-time field information.

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Team Members:
Divyansh Kalia & Smriddhi Sahni

Salient Features

  • Automatic and manual irrigation control.
  • Real-time soil moisture monitoring.
  • Intelligent irrigation management for improved water conservation.
  • Voice-assistant support for farmers.
  • Real-time agricultural information through a mobile application.
03

Crop Saviour

AI-based crop-health solution designed to assist farmers in identifying plant diseases, understanding possible remedies and improving cultivation practices through accessible technology.

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Team Members:
Naman Chopra, Manav Sidana, Manan Sharma

Overview

The project focuses on assisting farmers in identifying crop diseases and providing possible solutions to help mitigate disease spread. It also aims to communicate cultivation and seeding recommendations in the farmer's native language.

Goals

  1. Reduce crop losses caused by diseases affecting major agricultural crops.
  2. Help protect farmers' agricultural investment through early identification of crop problems.
  3. Introduce farmers, particularly in low-literacy regions, to practical applications of AI for agricultural decision-making.
04

Smart Farming

Portable and real-time soil nutrient monitoring research for sustainable agriculture, focusing on soil nitrogen and phosphorus assessment.

Research Paper
Research Team:
Harpreet Singh, Neeraj Halder, Balraj Singh, Jaskaran Singh, Sandeep Sharma, Yosi Shacham-Diamand

Research Focus

  • Portable soil nitrogen and phosphorus monitoring.
  • Real-time agricultural soil assessment.
  • Sensor-driven precision agriculture.
  • Sustainable nutrient management.
05

AdapTree

Data-driven plant stress assessment framework combining artificial intelligence with sensor-based measurements for plant health monitoring.

Research Paper
Authors:
Divisha Garg, Harpreet Singh, Yosi Shacham-Diamand

Research Focus

  • Data-driven plant stress assessment.
  • AI and sensor integration for plant monitoring.
  • Plant health and stress detection.
  • Data-driven approaches for precision agriculture.
06

IoT-Based Automated Irrigation & Soil Management System

An IoT-enabled agricultural system focused on automated irrigation and intelligent soil management. The technology has also been protected through an Indian patent.

Inventors:
Harpreet Singh, Rasmeet Singh, Jatin Chauhan

Key Features

  • IoT-based agricultural monitoring.
  • Automated irrigation management.
  • Soil-condition monitoring.
  • Technology-driven water management for agriculture.

Patent

Indian Patent Application No. 201811021657. The patent is listed as granted in 2024.