Final Year Projects (FYPs) - Undergraduates
Permanent URI for this collectionhttps://repository.cuilahore.edu.pk/handle/123456789/37
This collection archives the complete set of theses produced by students of the COMSATS University Islamabad, Lahore Campus.
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Item Vision Based Rehabilitation and Information System for Patients(Library Information Services, COMSATS University, Lahore Campus, 2019-06-19) Syyam Noor, Muhammad Hasham; FA15-BCS-127 , FA15-BCS-058; Dr. Allah Bux Sargano; LHR TP 5898The system is an action verification system for rehabilitation of patients with limited mobility. In this regard, a Kinect depth sensor is used to capture the image-sequences of patients for identification of different actions in real time during rehabilitation exercisers at home. The system is trained to make decisions whether the person is performing the rehabilitation exercises correctly or not, each exercise contain some passing parameters, and this is to ensure that all the exercises are done in a complete and perfect manner. A desktop based application is designed for user’s interaction. This application contains a list of exercises available, the user will have an option to choose any of them according to the need. Physiotherapists using this system at their clinics will be hugely benefitted with this, it will act as their personal application based assistant for mobility exercises. Especially, the report generation feature will help them in tracking the patient’s progress. The report can be generated at any given time while doing an exercise that will brief the user about the angles and distances between the joints and what is the ideal one. The main ambition behind making this rehabilitation system is to recover pre-injury stages in all phases of physical fitness. The equipment required by the system are economical ones to help those patients who genuinely need this system which everyone can set up at their own places. This would allow patients to perform the rehabilitation exercises in sitting position at their relaxing place while preventing patients from falling down during training. The proposed system is 100% real-time (gives results on run time), effective to vision-based action identification, and demands low-cost system requirement (hardware and software), which is affordable for almost everyone.Item Voice Assistant for WEGO(Library Information Services, CUI Lahore, 2023) Muhammad Shafay Abid Shafayan; sp 19-BCS-040; Dr. Allah Bux SarganoThis project has been developed as a part of an industrial FYP with WEGO. WEGO is a travel assistant application that allows the user to search for and book flights and hotels. We were assigned the task of automating the process of searching the flight through WEGO with the help of a voice assistant. This project will improve the user experience of searching for a flight through WEGO and make the user less prone to errors. The voice assistant for the project has been trained using Google’s Dialogflow and the application has been developed using Kotlin and Jetpack Compose. This is a standalone Android application and has not been integrated into the existing WEGO application. Moreover, the application provides a complete chatbot experience where the user can communicate with the voice assistant regarding the flight they want to search. Once the user has communicated all of the required information with the voice assistant, they will be shown their search results on a WebView page from WEGO within the application. Since the majority of WEGO’s user base lies in the middle east, we have added Arabic and Urdu language support to the application as well. Further functionalities of our application include user accounts and user history. If the user is registered with the application, their history will be saved and they can visit their old search results from the history. User accounts are maintained using Firebase authentication and history is maintained using Firebase Realtime Database. We have succeeded at solving the problem that we set out to solve with this application. The application is working as it should and showing the relevant results. As far as the accuracy of the search results is concerned it is 100% when it comes to taking input in the English language. However, the accuracy is slightly compromised when it comes to Urdu and Arabic. We have used Google’s on-device translation models for adding Urdu and Arabic languages which compromises the accuracy of the search results shown. However, the search results are still respectable.Item Augmented Reality App for Basic Human Organs(Library Information Services, COMSATS University Islamabad, Lahore Campus., 2019-11-20) Fatima Zulfiqar; CIIT/FA15-BCS-030/LHR; Dr. Allah Bux Sargano; LHR TP 5810The proposed system targets a mobile phone android application using Augmented Reality (AR) as means of user interface. AR is a concept of integrating virtual 3-dimensional objects on 2-dimensioanl user screen creating an illusion of a 3-dimensional, real time user experience of an inherently simulated object in the real environment. The system will serve as a medium for extensive class of students focusing on assisting them to build better semantics for biological concepts through E-learning. The application focuses on four main human organs (heart, brain, stomach and lungs). The user will be able to view the 3D model of the four mentioned organs augmented on their books, saving not only learning time but also to provide a unique perspective to the curious nature of the human mind to understand the inherited complexity of its constituent anatomy. The proposed system achieves this by providing unique interfaces for the user to understand the working functionalities of human anatomy by simulating the 3D models. Converging to the recursively natural approach in machine learning we choose, state of the art, pre-trained convolutional neural network (CNN) as system’s classifier to recognize particular human organs such as Brain, Heart Lungs and Stomach from input camera frames. Once recognized, the particular target model is loaded from the model repository and simulated on user screen for interaction. To ensure maximal student access, the system is deployed as an android application, fine tuned with respect to the execution parameters such as CNN and anatomy model’s storage size kept to the minimum. For modelling and animation of organs, 3D modelling software like Blender, Cinema 4D and Autodesk Maya is used respectively. Unity platform is used for integration of different components and to develop Augmented Reality based mobile application.Item Smart Home Surveillance System(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2021) Muhammad Ibrahim Arif; SP19 BCS 033; Dr. Allah Bux SarganoThe Smart Home Surveillance System is an advanced intelligent security system that makes our residence safe and secure. The system aims to transform the regular CCTVs into intelligent cameras that will have some additional features like Suspicious Activity Detection, Smart Video Recording, Object Detection, and Notification alerts. The system is built not only for residential security but also for commercial areas. In fact, it can be installed in any environment either working or residential to track and minimize the occurrence of criminal activities. It detects the activities like Robbery, Assault, Stealing, Burglary, and Wall Climbing. The system's mobile application uses a trained deep learning model (CNN) that classifies the activities as suspicious or non-suspicious. The model has trained on the UCF crime dataset as well as our custom-made dataset, based on which the binary classification is being done. If the activity is classified as 'Suspicious', the user will get notified immediately on the app through the snapshot of the scene. Yolov5 has been used for object detection. Further, there's a smart recording option that can be enabled through the mobile application. By enabling the smart recording option, the system will start recording only on the detection of objects in the frame. There's an admin portal of the system, which is a web app that would be used by the administrators. The user will be assigned the login credentials through this portal, and it is also responsible for monitoring the whole system. There is also a web portal on the user side that shows the live streaming once the user logged into the portal through the provided credentials. Thus, the whole system facilitates the users by providing a secure and intelligent security system. To evaluate the model, the confusion matrix has been used. The confusion matrix is being created using a test set which is obtained from the UCF crime dataset and some custom recorded videos. The model has an accuracy of 89% with the best confusion matrix obtained so far.