Computer Engineering - Project Reports
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Item DSD soft(AIKTC, 2023-05) Ansari, Abdul Majid; Pangarkar, Rabiya (19CO05); Khan, Shoab (19CO33); Khot, Shehzad (19CO35); Qurishe, Mohd Ziyaulhaq (19CO37)Direct store delivery (DSD) software is a powerful solution that streamlines the delivery process for businesses that deliver products directly to stores or customers. This software system architecture includes components such as mobile devices, inventory management, route optimization, payment processing, and reporting and analytics. By integrating these components, DSD software provides businesses with real-time visibility into their delivery operations, enabling them to optimize routes, manage inventory, and improve overall efficiency. With the ability to automate tasks, eliminate manual processes, and increase accuracy, DSD software can help businesses reduce costs, improve customer satisfaction, and gain a competitive edge in the marketplace.Item Didactic solutions(AIKTC, 2023-05) Qureshi, Rehaal; Khan, Muskan (19CO02); Khan, Sana (19CO03); Shaikh, Zikra (19CO08); Khan, Aftab (19CO23)Didactic Solutions As technological advancements continue to reshape the corporate landscape, it is crucial to update training methodologies to improve work efficiency. E-Learning has emerged as a vital component of employee training and internal human resource development. In recent years, web-based training has gained immense popularity in the corporate world as a cheaper, faster, and more efficient way to train large numbers of employees and individuals worldwide. Blended learning, a combination of face-to-face and online modalities, has also taken on a more important role in corporate training program design and implementation, providing a more flexible learning modality. We developed a service-based project, the Didactic Solutions, designed to provide training to both students and employees. The Didactic Solutions offers free trials and low-cost courses, leveraging user-friendly web-based training. The project platform offers live online training, and students can access recorded videos of their sessions upon successful completion of their courses. The project chatbot feature enables students to ask their instructor any questions they may have. In this paper, we provide an in-depth analysis of the design and implementation of the Didactic Solutions, and highlight the benefits of web-based training for corporate training programs. The project research findings suggest that the Didactic Solution’s design and implementation offer an efficient and cost-effective way to deliver high-quality training programs to students and employees, resulting in improved work efficiency and productivity.Item Eyedesk(AIKTC, 2023-05) Ansari, Abdul Majid; Shaikh, Nadir (15CO38); Sayyed, Sohail (18CO48); Kadav, Rutuja (19CO01); Thube, Vaishali (19CO09)Improving efficiency and performance is an important topic in the world today.Our project Eyedesk includes registration of patients, storing their details into the system, and also booking their appointments with doctors.Our state-of-the-art facility is equipped with the latest technology, and our highly skilled and experienced team of ophthalmologists, optometrists, and support staff are dedicated to ensuring that you receive the best possible care.Our software has the facility to give a unique id for every patient and stores the details of every patient and the staff automatically. User can search availability of a doctor and the details of a patient using the id. Eyedesk can be entered using a username and password. It is accessible either by an administrator or receptionist. Only they can add data into the database. The data can be retrieved easily. The interface is very user-friendly. The data are well protected for personal use and makes the data processing very fast.It is having mainly two modules. One is at Administration Level and other one is of user I.e. of patients and doctors. The Application maintains authentication in order to access the application. Administrator task includes managing doctors information, patient’s information. To achieve this aim a database was designed one for the patient and other for the doctors which the admin can access. The complaints which are given by user will be referred by authorities. The Patient modules include checking appointments, prescription. User can also pay doctor’s Fee online.At our Eye Hospital, we understand that your vision is precious, and we are committed to helping you maintain it.Item Voice controlled e-commerce(AIKTC, 2023-05) Nusrat Jahan; Mapari, Simran (19CO04); Shaikh, Alfiya (19CO62); Aga, Fiza (20DCO01); Patil, Aditi (20DCO07)This project aims to develop a voice-controlled e-commerce platform that enables users to shop for products using voice commands. The project utilizes modern natural language processing and voice recognition technologies to enable seamless interaction between users and the platform. The platform is designed to enhance the shopping experience by making it more convenient and accessible. The report outlines the development process, including the technology stack used, the system architecture, and the user interface design. Additionally, the report evaluates the system’s performance and user experience, identifying key challenges and future directions for platform improvement. The project highlights the potential of voice-controlled e-commerce platforms in revolutionizing the way people shop online and demonstrates the importance of incorporating cutting-edge technologies in creating an efficient and user-friendly shopping experience. The main objective of this project is to develop a web application where a voice assistant is integrated using Alan AI to present a voice-controlled commodity purchase as per the user’s request.Item Product recommendation system using ML(AIKTC, 2023-05) Dange, Anas; Baig, Sahil (19CO49); Sirkazi, Ruzbihan (19CO48); Mohd., Aasif (19CO36); Ulde, Kais (19CO46)Product Recommendation System Using ML In today’s modern epoch of information technology, the idea of efficiently finding one’s favourite product in a large dataset of application database, becomes an essential issue to address for the online content providers in order to attract the masses as opposed to their competitors. Recommender systems or recommendation systems, as they are popularly known, are information filtering systems which are usually integrated with several consumer and com- mercial applications. Such systems act as a bridge between various content facilitators such as social media websites, e-commerce portals, streaming platforms, etc. and the users of these applications, by suggesting them items from the application database which conform to the user preferences and past activities. Such personalized systems play a vital role, especially when the user is unclear of the item to the searched for. These systems are infiltrating every aspect of our lives, in the form of ?Because you watched? header on Netflix, ?People you may know? section on Facebook, ?Customers who bought this also bought’ partition on Amazon.Item Disease prediction using machine learning and image processing(AIKTC, 2023-05) Dange, Anas; Haddadi, Amir (19CO19); Khan, Shahrukh (19CO51); Husen, Mohd Altaf (19CO41); Qureshi, Mohd Zaki (19CO40)Current machine learning models for healthcare analysis focus on one disease per analysis, such as diabetes, liver, malaria, pneumonia diseases. Our project aims to predict multiple diseases using machine learning algorithms, streamlit, Flask API, and Python pickling to save and load the model's behavior. By analyzing all parameters that cause diseases, our system can detect the maximum effects a disease will cause. A study using a large medical image dataset trained a deep learning model to predict diseases using transfer learning techniques. The proposed approach achieved high accuracy, outperforming other traditional methods, and has potential applications in clinical settings to reduce human error, improve diagnostic accuracy, and reduce the time required for diagnosis. This project can help people by monitoring their condition and taking necessary precautions to increase life expectancy. Overall, this study demonstrates the effectiveness of using machine learning and image processing for disease prediction and provides valuable insights into future research in this area.Item E-commerce Dapp(AIKTC, 2023-05) Mishra, Richa; Kadiri, Saud (19CO21); Khan, Anas (19CO24); Khan, Farhaan (19CO26); Shikalgar, Farhan (19CO56)Improving efficiency and performance is an important topic in the world today. As it is well-known, cooperative computing is an effective and traditional approach, and it is widely used in various fields. Inspired by this idea, take E- commerce for example, Security is one of its important indicators. In E-commerce, the security technology has become a major issue restricting the rapid development and popularization of E- commerce.With the advent of new technologies, Blockchain plays a major role in ecommerce sector.With the characteristics of decentralization, persistency, anonymity and auditability, blockchain technology is a new tool to solve the product traceability, information security and privacy, payment efficiency and cost reduction in cross- border e-business.Existing E-commerce models are trapped in a dilemma between the proof of ownership and privacy protection. To address this issue,We have made a platform Shoppingverse which is a blockchain based ecommerce.we design a privacy-preserving business protocol by employing private smart contracts in the negotiation phase. The protocol allows counterparties make deals without the disclosure of private information such as identities, addresses, and phone numbers. Moreover, we employ the zero- knowledge proof to guarantee the ownership.Item Stock analysis and prediction website(AIKTC, 2023-05) Mishra, Richa; Shaikh, Muhammad Huzaifa (18CO40); Bagdadi, Ameeruddin (19CO12); Khan, Raquib (19CO31); Qureshi, Mohammed Usman (19CO47)In this project we attempt to implement machine learning approach to predict stock prices. Machine learning is effectively implemented in forecasting stock prices. The objective is to predict the stock prices in order to make more informed and accurate investment decisions. We propose a stock price prediction system that integrates mathematical functions, machine learning, and other external factors for the purpose of achieving better stock prediction accuracy and issuing profitable trades. There are two types of stocks. You may know of intraday trading by the commonly used term ”day trading.” Interday traders hold securities positions from at least one day to the next and often for several days to weeks or months. LSTMs are very powerful in sequence prediction problems because they’re able to store past information. This is important in our case because the previous price of a stock is crucial in predicting its future price. While predicting the actual price of a stock is an uphill climb, we can build a model that will predict whether the price will go up or down. Apart from that, we have included a stock analysis feature, which helps users to understand the performance of a particular stock, also it guides users to invest in a stock whose price would eventually rise up in the coming future, leading to profit gains.Item Machine learning approach of price prediction(AIKTC, 2023-05) Jamkhandikar, Irfan; Mohammad Farhan, (19CO38); Shaikh, Afsar Ahmed (19CO52); Thokan, Naveed Naushad (19CO60)This paper presents a Laptop price prediction system by using the supervised machine learning technique. The research uses multiple linear regression as the machine learning prediction method which offered 85% prediction precision. Using multiple linear regression, there are multiple independent variables but one and only one dependent variable whose actual and predicted values are compared to find precision of results. This paper proposes a system where price is dependent variable which is predicted, and this price is derived from factors like Laptop’s model, RAM, ROM (HDD or SSD), GPU, CPU, IPS Display, and Touch Screen. Price prediction is a useful feature forconsumers as well as businesses. A price prediction tool motivates users to engage with a brand or evaluate offers in order to spend their money wisely. Price prediction enables businesses to set pricing in a manner that builds customer engagement and loyalty. With Machine Learning (ML) technology a price prediction problem is formulated as a regression analysis which is a statistical technique used to estimate the relationship between a dependent/target variable and single or multiple independent (interdependent) variables. In regression, the target variable is numeric. This project will focus on ML algorithm used for price prediction.Item Blockchain based e-voting system(AIKTC, 2023-05) Kazi, Samreen Banu; Ansari, Anas (20DCO02); Bhatkar, Zohaib (20DCO03); Khan, Absar (20DCO04); Shaikh, Anas (20DCO08)Electronic voting or e-voting has fundamental benefits over paper based systems such as increased efficiency and reduced errors. The electronic voting system tends to maximize user participation, by allowing them to vote from anywhere and from any device that has an internet connection. The blockchain is an emerging, decentralized, and distributed technology with strong cryptographic foundations that promises to improve different aspects of many industries. Expanding e-voting into blockchain technology could be the solution to alleviate the present concerns in e-voting. Here we propose a blockchain-based voting system that will limit the voting fraud and make the voting process simple, secure and efficient.Item Voice bot for mall(AIKTC, 2023-05) Dange, Anas; Gupta, Shailesh (18CO23); Khan, Mohd Zeeshan (18CO33); Khan, Mohd Usman (19CO29); Mohd Yusuf, Ashfaque (19CO39)A voice bot for a mall project can be a great addition to enhance the user experience and provide convenience to visitors. The voice bot can be designed to understand the user’s needs and assist them with finding locations within the mall. Our voice bot is designed to make your visit to our mall as seamless as possible. Whether you’re looking for a specific store, restaurant, or other service, our voice bot is here to help. Simply tell us what you’re looking for, and we’ll provide you with the location and directions to the particular shop to get there. With our voice bot, you’ll no longer have to navigate through confusing maps or ask for directions. Our voice bot is your personal guide to everything our mall has to offer. Our mall features is a wide variety of stores, restaurants, and entertainment options to suit your needs. Whether you are looking for the latest fashion trends, a delicious meal, or some family fun, we have something for everyone.Item Home Inventory with ML(AIKTC, 2023-05) Khan, Tabrez; Khan, Farhan (19CO27); Khan, Zaki (19CO34); Mulla, Saad (19CO43); Siddiqui, Ehtesham (19CO59)This paper describes the project on the topic of Home Inventory management system, it is a mobile application that is use for the track home inventory. It has a built-in intelligence system that make user work easy. In this advanced era of technology, we don't have any mobile application or site that can help user to manage their inventory, track their family nutrition, track their purchase record and suggest them recipe based on the item they have in inventory. In this project,our main aim is to save money, time, and save food from wastage. It also provide recipes and many more. It is a system designed to help individuals create an accurate and comprehensive inventory of their personal possessions. The system uses machine learning techniques to automatically identify and categorize items based on images and descriptions provided by the user. This is an Application which is responsive and can be accessed from any android or iOS device connected to the internet.Item Social media enabled gym management system(AIKTC, 2023-05) Kazi, Samreen Banu; Dolare, Daniyal (19CO15); Dawnak, Sufyan (19CO16); Baig, Hamza (19CO20); Kazi, Uzair (19CO22)Social Media is an innovative application dairy happened. In this study, we propose a social media-enabled gym management system. Through the system, the manager of a gym can easily track and trace the exercise status of members. For the purpose of the gym, one can apply an exercise prescription for each member when they come to the gym. The system not only can reduce the waste of human resources and enhance the efficiency of management levels, but also enhance the experience. The members, can post workout routines and diets and can share their experiences with other members. This can help members stay motivated and feel accountable to achieve their goals and level up in the world of fitness and can also increase member retention for the gym.Item Dementiacare; health monitoring and productivity(AIKTC, 2023-05) Nusrat Jahan; Rathod, Pooja (19CO06); Sayed, Zahra (19CO07); Ansari, Azad (19CO14); Khan, Haarish (19CO18)Dementia is a neurocognitive disease that affects millions of people worldwide, and the number of patients is expected to increase significantly in the coming years. In response to this growing problem, the DementiaCare application has been developed to help patients and caregivers manage the disease more effectively. The app includes features such as a personal diary, contact lists, reminders for medications and daily activities, and games to improve productivity. One of the key features of the app is the ability to track the live location of patients and provide emergency contact information for their family members. Early detection of dementia is also critical, and the app includes a system for detecting dementia at an early stage. Engaging in meaningful activities is an effective way to improve the quality of life for dementia patients, and the DementiaCare app is designed to identify and customize these activities for each individual patient.Item Fashion recommendation system(AIKTC, 2023-05) Khan, Tabrez; Nagori, Mohd Ali (17CO37); Khan, Mohd Saqibe (19CO30); Khan, Mohd Arham (20DCO05); Khan, Nemat Roshan (20DCO06)With an increase in the standard of living, peoples’ attention gradually moved towards fashion that is concerned to be a popular aesthetic expression. Humans are inevitably drawn towards something that is visually more attractive. This tendency of humans has led to the development of the fashion industry over the course of time. However, given too many op- tions of garments on the e-commerce websites, has presented new challenges to the customers in identifying their correct outfit. Thus, in this project, we proposed a personalized Fashion Recommender system that generates recommendations for the user based on an input given. Unlike the conventional systems that rely on the user’s previous purchases and history, this project aims at using an image of a product given as input by the user to generate recommen- dations since many-a-time people see something that they are interested in and tend to look for products that are similar to that. We use neural networks to process the images from Fashion Product Images Dataset and the Nearest neighbour backed recommender to generate the final recommendations.Item Arba-business listing portal(AIKTC, 2023-05) Abdul MajidThis paper describes the project on the topic of Arba-Business Listing Portal. It is business listing site which help the user to gain fund from investors and also let the expert business user to guide new business comers. Also investors can invest in business of their choice by analysing business profile and its idea. Currently in market there are few portal that allow the user and investor to communicate directly instead of involvement of 3rd parties.Item Face recognition attendance system(AIKTC, 2023-05) Shaikh, Salim; Mukadam, Ismail (19CO42); Shaikh, Fuzail (19CO53); Ansari, Mohd Sajjad (19CO61)The current attendance procedure is manual, which is time-consuming for both teachers and students. Manual attendance recording can lead to human errors, and students may have to wait for a long time to be marked present. Automating the attendance process can help increase learning time in the classroom. Facial recognition is a popular technology that can be used to automate attendance. For this project, we developed a facial recognition system that uses traditional facial recognition and recognition mechanisms. Facial recognition is essential for security and surveillance purposes, and it is crucial to have an effective and affordable system. The identification process involves three main steps: face recognition, feature extraction and classification, and real-time detection. Our system uses Python programming language and the OpenCV library for implementation.Item Snap illegal parking(AIKTC, 2023-05) Jamkhandikar, Irfan; Deshmukh, Awais (19CO17); Siddiqui, Altamash (19CO57); Shaikh, Navaid Ahmed (19CO55); Shaikh, Mohd Saif (19CO54)The report outlines the development and effectiveness of a Snap Illegal Parking application that enables citizens to report illegally parked vehicles to the government in exchange for reward points. The application aims to address the issue of traffic congestion caused by illegally parked vehicles on the road. The report describes the key features of the application, such as the reporting mechanism, reward system, and user interface. It also discusses the benefits and limitations of the application and provides recommendations for improving its effectiveness. The report concludes that the application has the potential to be a useful tool for improving traffic management and reducing illegal parking. Overall, the application can be proven to be a successful and innovative solution to promote citizen engagement and improve traffic management in the city.Item Mental health tracker app(AIKTC, 2023-05) Qureshi, Rehaal; Siddiqui, Arbaaz Gaffar (19CO58); Shaikh, Shahid Zakir Husen (17CO46); Siddiki, Jasmin Nizam (18CO13); Jamadar, Abdussamad (18CO25)Mental Health is a very important issue in today’s world . As in these days, a lot of people now working from home and even companies are preferring work from home, the mental health situation of the people has nose-dived to unbelievable levels. The main objective of the proposed project focuses on building an application that will try to collect the mental state of the user and provide close to accurate remedies – assigning tasks, connecting a doctor( or psychiatrist) etc. The application tries to find if an app user is suffering from any mental issue by asking a few psychological questions and then based on those answers, it suggests measures that the app users can believe to recover from their issue and all this happens based on how the user answers the questions. Based on the answers that the users provide, the application will suggest tasks to them. The application will also take timely updates from the user and will update the data to the dashboard Keywords: Anxiety, Depression, Android Application, Prediction, Sentiment Analysis, NLP, Machine Learning, Classification, Mental Health.Item Real time sign language translator for video conferencing platforms(AIKTC, 2023-05) Shaikh, Salim; Mullick, Touhid Islam (19CO45); Khan, Rehan (19CO32); Shaikh, Mohd Danish (19CO63); Sayyed, Md Ali (19CO50)Sign Language is the method of communication of mute people all over the world. There are about 70 Million sign language users around the world. But only a few percent of people who can hear and speak know sign language. This makes it difficult for mute people to communicate. Computer-based Sign Language Recognition is a breakthrough technology to overcome this problem. After pandemic businesses and organizations have started adapting online video conferencing platforms for carrying out meetings, workshops, interviews, collaborations, etc. The aim of this project is to provide a practical solution for sign language interpretation. Here we propose a lightweight real-time and integrable sign language detection application, that can be used in any video conferencing platform such as google meet, microsoft teams, zoom, discord, etc. Here we have used deep learning algorithms, image processing and the concept of virtual cameras to achieve our goal. We describe a desktop application to sign language detection in the browser in order to demonstrate its usage possibility in videoconferencing applications. We use the MediaPipe Holistic pipeline and LSTM for pose detection and to train and predict sign languages. It shows 91%-93% prediction accuracy while the latency is still under 4ms. Keywords: Sign Language Translation,American Sign Language, LSTM, Virtual Camera, Hand Gesture Recognition, OpenCV, video-conferencing, Sign Language Translator for Meeting Apps, Real Time Sign Language Translation, Google Meet, Microsoft Teams, Zoom.