Department of Computer Science

Permanent URI for this communityhttps://repository.cuilahore.edu.pk/handle/123456789/16

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Author: search.filters.author.Dr Usama Ijaz BajwaSubject: search.filters.subject.FA16

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    AQI Predictor
    (Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-11-20) Waqas Ahmad; FA16-BCS-047; Dr Usama Ijaz Bajwa; LHR TP 6129
    Our project, AQI Predictor, is an application to predict the quality of Air aka Air Quality Index (AQI) Level using images. The user can input the images by capturing directly from the smartphone’s camera or already captured ones from the gallery. The app uses a trained model that’s hosted on local server at the backend. The trained model is a Convolutional Neural Network that uses machine learning techniques to help us in predicting the Air Quality level (AQL) correctly. The model is trained on a relevant dataset in order to achieve the accuracy. Along with the app, a website will be created that will be synchronized with the app and the data will be collected. The data then will be used to generate a map of the areas the Air quality level has been calculated for. This will help people in deciding which areas have what kind of air quality. The quality of air will be predicted by the application providing us Air Quality Level which will further tell us more details such as if the air is harmful or good and how necessary precautions can be taken. These factors and results will help us and the authorities including the Government and relevant governmental and other bodies decide certain measures to make the air quality better.
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    Charades
    (Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-11-20) Ramsha Rasheed; FA16-BCS-127; Dr Usama Ijaz Bajwa; LHR TP 6118
    As stated by World Health Organization(WHO), it is estimated that over 466 million people around the globe that are suffering from hearing loss that is disabling. [1]. In those 466 million people some are completely deaf that basically have little or no functional sense of hearing at all and the other are called “hard of hearing” who have mild-to-moderate hearing loss. Deaf people practice sign language to communicate whereas the hard of hearing can use sign language and spoken language with aid too. Deaf communicate in sign language as their first language. Abled people perhaps have little or no knowledge of sign language at all. Deaf people have difficulty in correspondence on a daily basis. A sign language interpreter may be used. But a sign language interpreter is expensive to have accessible all the time, and it becomes inconvenient too. A solution to this problem is needed, that is economical and easy to use. Hence, our final year project proposes a solution to this problem that is easy to use and have too. The solution wished-for being an android application works both ways. First as a listener i.e. it detects the signs performed by the deaf person using Smart phone/tablets camera or a device such as Kinect and translate them to native spoken language in form of text on an android tablet/Smart Phones screen. Secondly as a speaker i.e. it takes the text in natively spoken language typed by the abled person through the keyboard and converts it into a series of signs which are implemented on a 3D avatar on the screen of the Smart phone/ tablet.