360 degree video streaming is a new form of video streaming where video is captured using a 360 degree video camera, and users may select which perspectives are of interest to them. Using traditional approaches to video streaming can result in 5X-6X bandwidth overhead. It is desirable to only show a user the portion of the video relevant to her, but user motion can lead to stalls, or degraded experience. We are developing new algorithms and solutions for 360 degree streaming with smooth user experience while achieving significant bandwidth savings.

In the summer project, we are looking to build a complete end to end prototype, where users can engage in 360 streaming from mobile devices and Oculus headsets. We would like to work with real content producers (e.g., Purdue commencement) to perform field trials of our 360 video streaming system. Doing so can also allow for A/B testing of different algorithms and provide data on how users engage with such content.

Human Factors, Mobile Computing, Other

• Computer Engineering

The main skillsets are: (i) strong Computer Engineering skills, especially in systems and software building; and (ii) an interest and passion in building working real-world research prototypes and evaluations among real users. Strong background in C++ is preferred, and an ability to develop code for mobile devices, and devices such as Oculus headsets will be required. Desired course work include: Operating Systems, and Computer Networking. Other requirements include C++/Java (ECE 30862/39595) and Data Structures (ECE 368).

Electrical and Computer Engineering

Sanjay Rao

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