The use of an intelligent conversational computer system (chatbot) is gaining acceptability among many industries to provide virtual assistance to customers. Advancements in large language models (LLM) have enabled the development of chatbots like ChatGPT (by OpenAI) and LaMDA (by Google). This project aims to utilize an existing LLM-based chatbot to develop a conversational AI to engage with farmers in a near-human context and convert the conversation into aids for farm decision-making. In this project, one student will work with a Ph.D. student to help with the tasks identified below:

Student Task List:

1. Survey current literature and write a critical synthesis
2. Utilize publicly available APIs/datasets comprising a multitude of media: images, text, videos, and numerical data
3. Design and develop an interactive interface using Optical Character Recognition (OCR)
4. Present weekly progress in the form of PowerPoint presentations
5. Prepare a final report in the form of a research paper

IoT for Precision Agriculture, Mobile Computing

• Agricultural Engineering,
• Agricultural Systems Management
• Computer and Information Technology
• Computer Science
• Computer Engineering
• Electrical Engineering
• Agronomy (multiple concentrations)

Relevant coursework in Python programming and introductory machine learning, equivalent courses from online platforms, or relevant work experience. Motivation for higher studies and an ability to work independently are desirable.

Agricultural and Biological Engineering

Dharmendra Saraswat

Infectious diseases are a leading cause of economic burden on food production from animals. For example, African Swine Fever is the deadliest animal pandemic and led to loss of half the swine herds in China in 2019. Detection of such diseases can be challenging because the clinical signs can be similar to other diseases.
Our research project focuses on developing a low-cost user-friendly biosensor based on paper that can detect which pathogen is causing the disease quickly and provide recommendations on appropriate next steps. Such a biosensor would provide a rapid readout to the farmer or the veterinary physician and guide surveillance efforts.
Lab members working in the team have three objectives: i) design, test, and optimize primers for detecting pathogens and genes associated with African Swine Fever, ii) build and field-test a paper-based device for conducting loop-mediated isothermal amplification, and iii) build and field-test a heating/imaging device for conducting the paper-based assay in the field.
The SURF student will work on one of the objectives depending on their background and experience.

Biological Simulation and Technology, IoT for Precision Agriculture

• Biological Engineering - multiple concentrations
• Biochemistry
• Agricultural Engineering
• Biomedical Engineering
• Mechanical Engineering
• Electrical Engineering

Relevant skills for the project: • Wet lab skills and experience with molecular biology • Autodesk Fusion 360 for 3D Modeling/Printing and Laser Cutting • Python Programming Language for image processing and graphical user-interface using Raspberry Pi (or any other single board computer) To be successful at this position, you should have a GPA>3.5, prior experience working in a lab, and the ability to work in a team.

Agricultural and Biological Engineering

Mohit Verma