http://repository.iiitd.edu.in/xmlui/handle/123456789/140 ECE 2026-04-13T09:40:39Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1869 Foreign Object Debris (FOD) detection using mmWave FMCW radar for runway surveillance Pandey, Satyam; Ram, Shobha Sundar (Advisor) Foreign Object Debris (FOD) on airport runways is a serious threat to aviation safety, causing damage to aircraft during take off and landing. This report suggests a method of detecting FOD by utilizing a millimeter-wave (mmWave) Frequency Modulated Continuous Wave (FMCW) radar system for runway inspection. The method utilizes fundamental radar principles of transmission of the signal, reflection analysis, and beat frequency range estimation to detect small objects in the presence of environmental noise and clutter. Following the initial guidance of the project advisor, the system describes radar configuration, signal processing for range and angle detection, and simple noise filtering techniques. 2025-07-18T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1868 Computational gastronomy: web development Trivedi, Saumya; Bagler, Ganesh (Advisor) This report presents a comprehensive study that combines large-scale Exploratory Data Analysis (EDA) with the development of a modern web application, collectively forming the foundation for RecipeDB — an intelligent and interactive recipe discovery platform. The dataset under consideration comprises 584,572 diverse recipe records, each annotated with 21 attributes includ- ing ingredients, preparation time, cooking instructions, nutrition facts, categories, and cuisine types. The EDA component focused on identifying patterns in ingredient usage, evaluating the dis- tribution of preparation and cooking times, detecting data inconsistencies, and constructing a robust dietary tagging framework encompassing classifications such as Jain, Vegetarian, Egg- based, and Non-Vegetarian. This process also involved significant data cleaning, normalization, and the detection of duplicate or semantically similar entries, ensuring high data quality and consistency for downstream applications. The insights gained from the analysis were used to inform the design of a web-based interface, which allows users to search, filter, and explore recipes using a wide variety of parameters includ- ing ingredients, nutrients, utensils, and dietary preferences. The frontend of the application was developed using React (Vite) and Tailwind CSS, while the backend was built using Node.js with Express and connected to a MySQL database. Key features include a responsive and visually engaging UI, real-time search suggestions, nutrient-based sliders, and dark/light mode toggling for enhanced usability. The project demonstrates the integration of data science and software engineering practices to build a scalable and user-centric platform. It not only showcases how rich insights can be derived from raw recipe data but also how these insights can be operationalized through a well-designed application to improve user interaction and food information accessibility. 2025-07-26T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1866 Development of large language models and tools to study patents and develop insights Soam, Satyam Singh; Grover, Anuj (Advisor) The project titled "Development of Large Language Models and Tools to Study Patents and Develop Insights" aims to use advanced AI to help analyze and understand patent information better. With more patents being filed each year, there is an increasing need for tools that can handle lots of information and find useful insights. This project focuses on creating and using large language models (LLMs) designed to read, analyze, and summarize patent documents. The main functionality of this project is to provide detailed information about patents, like titles, summaries, claims, inventors, filing dates, and legal status. By making use of advanced natural language processing (NLP) techniques, this project will automatically extract and organize this information, making it easy to find and search. The project will also include tools to spot trends, perform smart searches, and create insights from patent data, helping researchers, inventors, and legal professionals. The successful completion of this project will create a strong platform that makes it easier to get and analyze patent information and offers advanced features for deeper insights into patents, technology, and innovation trends. This will save time and effort in patent analysis, help make better decisions, and give a better understanding of global innovation. The platform will also support comparing studies and competitive intelligence, giving users an advantage in their fields. 2024-11-29T00:00:00Z http://repository.iiitd.edu.in/xmlui/handle/123456789/1865 Development of a haptic device for surgical training in mixed reality Sharma, Nootan; Kumar, Nitin; Shankhwar, Kalpana (Advisor) This project focuses on designing a haptic device integrated into a virtual reality (VR) environment to enhance surgical training. Combining force feedback, sensor integration, and 3D modeling, the device offers a realistic simulation of surgical procedures. Using Unity for simula- tion, Blender for 3D modeling, and precise sensors for feedback, the system aims to bridge the gap between theoretical learning and practical expertise. The innovation lies in its immersive, interactive design and its potential for reducing errors in surgical training. 2024-11-27T00:00:00Z