Browsing by Author "Jamkhandikar, Irfan"

Now showing 1 - 8 of 8
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    Courio delivery service
    (AIKTC, 2021-05) Jamkhandikar, Irfan; Mohammed Sohail, Siddiqui (16CO59); Mansoor, Ali Malik Basha (16CO35); Khan, Gulam Haider (16CO26); Mulla, Ismail Mehmood (16DCO63)
    The global same day delivery market size was valued at USD 4.6 billion in 2019 and is expected to grow at a compound annual growth rate (CAGR) of 20.3 from 2020 to 2027. The market is driven by increasing urbanization, rapid e-commerce adoption, and changing customer expectations towards delivery services. Moreover, the ongoing substitution of stationary retail sales by online sales through e-commerce platforms has led to a significant increase in B2C shipments. Thus, the market is expected to witness substantial growth over the forecast period due to the rise in shipments, coupled with consumer demand for faster delivery service. Long delivery time is one of the significant reasons owing to which customers shop in brick and mortar stores than on online platforms. However, same day delivery services offer products in less than 24 hours i.e., preferably within the same day of the order placement. Thus, it integrates the convenience of online retail shopping with the immediacy of physical retail stores. Moreover, ease of ordering through online platforms, coupled with reduced shipping time, is creating growth opportunities for the market. Additionally, the availability of same day delivery services is further expected to support e-commerce adoption among consumers. Thus, online retailers are expected to be benefit ted from the adoption of same day services as reduced delivery time of the product and higher convenience improves their position versus stationary retailers. Moreover, same day delivery services combine the convenience of online shopping with the immediate product availability of retail. The aforementioned benefits, coupled with the rising adoption of same day delivery services among e-commerce platforms, are anticipated to bolster the market growth over the forecast period. Keywords: B2C, e-commerce
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    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.
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    Medication adherence monitoring with tracking automation and emergency assistance
    (AIKTC, 2020-05) Jamkhandikar, Irfan; Shaikh, Shadab Ali Murad Ali (17DCO74); Kazi, Obaid Abdul Aziz (17DCO69); Ansari, Mohd Adnan Azimuddin (17DCO63); Shaikh, Romaan Usman (16DCO77)
    In today‘s busy world, people are not able to track/monitor the medication events of their dear ones who are suffering from diseases appropriately. There are times when a patient “forgets” to have or “doesn‘t take” the prescribed medicine at a given schedule. Such scenarios in medical term is known as Medication Non-adherence (MNA). The MNA to prescribed treatment is thought to cause at least 100,000 preventable deaths and $100 billion in preventable medical costs per year. The reason for Nonadherence shows 63% for forgetfulness.[5] A study kempegowda institute of medical sciences & research center, Bangalore, India depicts over 21% of MNA problem in hypertensive patients.[9] The technology that could help in improving the MNA related problem is over 28% combining phone call (10%), live chat (3%), SMS (9%), Mobile applications (5-8%).[11] Despite, The medical profession largely ignores MNA or sees it as a patient problem and not a physician or health system problem.[5] This is a great loss to society considering the health effects and causes being generated from this issue. This report highlights various mechanisms that can be thought to integrate in order to improve the adherence of a patient.[1] Unlike already existing applications, Our Application (MAMTE) will guide a patient through automated calls, maintenance & tracking of log of events, & will use state of the art technologies such as Google Cloud Vision A.I and Deep learning neural networks for text and handwriting detection-recognition and extracting medication events through images. Keywords: Medication Non-Adherence, handwriting recognition, google cloud vision A.I, deep learning neural networks, medication events tracker.
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    Music Generation with A.I.
    (AIKTC, 2021-05) Jamkhandikar, Irfan; Prajapati, Deepak (17CO22); Sonde, Ashraf (17CO51); Shaha, Sufyan (17CO52)
    Today in the world of growing technology the domain of artificial intelligence is the pioneer. There are majority of the advancements and applications of Artificial Intelligence that we hear about refer to a category of algorithms known as Machine Learning. Self-learning algorithms use statistics to draw models from huge amounts of data. Machine learning is able to make very precise assumptions about what we do, about the next activity we might want to do. Alongside visual art and creative writing, musical composition is another core act of creativity that we consider to be uniquely human. We will create a model that will generate completely new music.
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    Principles of dimesnsional modeling
    (AIKTC, 2018) Jamkhandikar, Irfan
    Sem - VIII; Computer Engineering
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    Requistion process automation
    (AIKTC, 2017-05) Ansari, Mukhtar; Jamkhandikar, Irfan; Muqri, Sheefa (13CO10); Khatib, Ateeque (11CO54); Mansuri, Misba (13CO09)
    This project is aimed at developing a requisition process automated system that is of importance to either an organisation or an institute.This system can be used to automate the work flow of requisition and their approvals. Normally in any organisation or institute the request for the stationary is tracked via an e-mail or via excels sheets or registers and this leads to tremendous wastage of resources and it involves a lot of manual work. To reduced this wastage of resources and time we are working on creating an automated system which would shorten the requisition process cycle and administrative overhead. There are features like requesting for stationery, automatic approval for request, cancellation of request, notification to store if product is not available when requested, other notifications, record of requisition etc in this automated system.
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    Smart class: An extension to smart lecture delivery system
    (AIKTC, 2017-05) Khan, Mubashir; Jamkhandikar, Irfan; Shaikh, Yusuf (13CO54); Gharade, Abdul Mueed (13CO28); Choudhary, Haider (13CO23); Ansari, Ziauddin (13CO18)
    This Project illustrates extension to the Smart Lecture Delivery System. For this project, we have used a credit card sized, mini board computer called Raspberry Pi. A general working about the project, a camera module of RPi is used for recording video feed, a wired microphone is used for taking sound input. Recorded video are processed in Raspberry Pi and uploaded on a local server. Video recording is handled by the faculty through an VNC client application. After completion, the video is uploaded automatically on the server. All videos are uploaded through FTP protocol into a local Server and entry is added to the database. Student can access these video lectures according to his/her convenience from an android application or a website. With some modifications, it can also be used to monitor the behaviour of the student in the class and used to control any misconduct happening in the class.
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    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.