Research
Opportunities
Team

Agriculture Automation and Information Systems

Information extraction (AI/ML)
Management (Databases)
Presentation (User Interface/Actuators)

Agriculture Automation and Information Systems (AAIS) vertical emphasises on sustainable data collection with affordable sensing infrastructure, data analysis with state of the art AI/ML methods, and distribution of the information with an adaptive human-computer interface for decision support and task automation.


Research

Decoupled Crop Surveillance

Receiving information is the key to a cyber-physical system, and particularly important for crop surveillance and monitoring systems. The sensors capture environmental, crop, and activities taking place on the farm. The goal of this project is to decouple the sensing infrastructure from farms and provide surveillance as a service using modern sensors such as UAV, Satellite, Robots, etc.
Contact coordinators to for more information and click here to apply.

Big Data Analytics with AI/ML

Due to the enormous spatial size of the farmland and regular interval of data-sensing makes the big data analytics challenging and costly. The overall cost includes the cost of storage, transmission, and computing resources. The goal of this project is to build affordable AI/ML solutions to help farmers in agriculture automation, decision support, precision agriculture, and market analysis.
Contact coordinators to for more information and click here to apply.

Web platform and HCI

Farmers are not technology savvy. Most of the farmers find it difficult to use technological devices. In developing countries, farmers may even not be familiar with the English language. The aim of this project it to build human-computer-interface (HCI) that are farmer-friendly. Particularly we intend to consider the local culture in choosing the interface modality and structure.
Contact coordinators to for more information and click here to apply.

Sustainable Hardware

Due to the vast fields, replacing batteries in sensors, wireless devices, and micro-controllers is a challenging task. Therefore, it is beneficial that battery requirements are minimized in computational and sensor devices deployed on the field. However, the state of the art of AI/ML algorithms have a huge computational requirement. Therefore, we aim to build custom electronic hardware solutions that are cheap efficient, specifically for precision agriculture and monitoring tasks.
Contact coordinators to for more information and click here to apply.


Opportunities

CHANAKYA-GI (Graduate Internship)

This is 10 month internship for graduate students. The students would work on project developmental work of the technical solutions.
Click here for more information.

CHANAKYA-PGF (Post-Graduation Fellowship)

This is 24 month fellowship for the students admitted to PG programmes in CPS or related areas and having a valid GATE, at AICTE approved engineering institutions.
Click here for more information.

CHANAKYA-DF(Doctoral Fellowships)

This fellowship supports doctoral candidates for 48 months to do an in-depth R & D in CPS by applying independent methodologies of scientific research and creating new scientific knowledge/ technology solutions in CPS.
Click here for more information.

CHANAKYA-PDF (Post-Doctoral Fellowships)

This fellowship supports motivated young researchers with doctorate degree in the area of CPS to groom them as an independent researcher. The fellows are required to work under a faculty/scientist at TIH - AWaDH..
Click here for more information.


Team


Domain Coordinators

Dr. Mukesh Saini

Multimedia Processing, AI/ML

319, SRB, Main Campus, IIT Ropar
mukesh@iitrpr.ac.in
Homepage, Google Scholar

Dr. Neeraj Goel

Custom Hardware for AI/ML

218, SRB, Main Campus, IIT Ropar
neeraj@iitrpr.ac.in
Homepage, Google Scholar

Members