Engineering @Qube | Mentor @Scaler | Full Stack Developer

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This Application Aims to develop a foundation for a web-based and mobile-based application for a committee which can be helpful for the farmers in the market and buyers. Both farmers and buyers can
register and maintain their profiles. Farmers shall update their in-stock yield and expected yield along with the price. Buyers have to enter their needs and surf the profile of farmers and contact them for
price negotiation and fixing the Deal. This Application will enhance communication on both sides, which means not only buyers can communicate with the farmers but farmers can also communicate
efficiently with the buyers if they have any in-stock yield that matches the need of the buyer. It depends on the buyer and the farmer whether they want to involve the transportation service for the delivery.
The farmer can increase the good's price by making the delivery by himself. If the farmer and the buyer have a sophisticated smartphone, he can access the portal. In case one of them does not have a
smartphone, they can still update their data directly on the portal via SMS integration.

Portal for Farmers to Connect with Buyers 

In order to tackle the advent of futuristic technology and making it safe and secure, we introduce not just 1 but 2 new features on the Twitter platform.

TweeAR: Giving a whole new world to the tangible environment around us. You can use TweeAR literally anywhere and everywhere. May it be shopping malls, while reading a newspaper, finding your favourite music, finding your assignments, searching your favourite product, and whatnot. You name it and TweeAR gives you the augmented presence of your demand in front of you. Say you are reading a newspaper and wish to explore the recent tweets around the recent presidential elections, use TweeAR to scan your newspaper’s section and whoa! there you have a video of the presidential elections with which you also get to see all the tweets around the elections.

TweeShield : TweeShield gives the user an ability to secure his/her privacy.The user having a public account can make the tagging of their account private , in a sense, TweeShield detects all the tweets which have tagged a user and has abusive language in it. TweeShield gives the users 3 major options : Report and Block : Upon blocking the person who has tweeted, we ensure that the relevant tweet no more remains on the user’s wall. Along with which , the “Report” takes care of the ethicality of the tweet and let the Health department at Twitter take care for the same Untag Me: Say you wish to get untagged from the tweet while keeping the tweet on air, use the Untag me feature to let the tweet on air but of course, not your profile mentioned in it. Ignore: You find the person detected by TweeShield to be one of your friends and hence wish to take no action on the tweet, select Ignore to remove the person from the TweeShield and henceforth, the SmartBlock feature shall take care that upon “Ignoring” your friend multiple times, it doesn’t show him up!

TweeShield & TweeAR

Home Automation using ESP8266

Like many live code playgrounds, OCE is an online code editor for testing and displaying HTML, CSS, and JavaScript code snippets by users just like CodePen. It also supports Sass and SCSS (both with an optional Compass or Bourbon add-on).

It's core functionality is that it allows you to write code in the browser and view the results as you go. It's an open-source learning environment where developers may generate and test their code snippets. Since it has a web-based code editor, you can change your code and see the result immediately, which allows quicker debugging.

Users can also change the modes (Dark & Light). The project was built using ReactJS & Bootstrap Library. "Netlify" is used for the deployment of the project.

Online Code Editor

VR-for-Education

https://youtu.be/f_UO1vEVZBI 
Now a days technology made our life easy and made world compact. Day by day uses of technology increasing and people move there head toward smart technology. So this smart word it self define as augmented reality. So let’s take a step in future using augmented reality. Our project is based on smart studies with the help of AR.

AR - Step into the Future 

Project: Predict Future Product Prices Using Facebook Prophe

Cardiovascular disease is a major health burden worldwide in the 21st century. Human services consumptions are overpowering national and corporate spending plans because of asymptomatic infections including cardiovascular ailments. Consequently, there is an urgent requirement for early location and treatment of such ailments. The information which is gathered by data analysis of hospitals is utilizing by applying different blends of calculations and algorithms for the early-stage prediction of
Cardiovascular ailments. Machine Learning is one of the slanting innovations utilized in numerous circles far and wide including the medicinal services application for predicting illnesses. In this research, we compared the accuracy of machine learning algorithms that could be used for predictive analysis of heart diseases and predicting the overall risks. The proposed experiment is based on a combination of standard machine learning algorithms such as Logistic Regression, Random Forest, K-Nearest Neighbors (KNN), support vector machine (SVM), and Decision Tree. Most of the entities in this world are related in one way or another, at times finding a relationship between entities can help you make valuable decisions. Likewise, I will attempt to utilize this information as a model that predicts the patient whether they are having a Cardiovascular disease or on the other hand not. Moreover, the data analysis is carried out in Python using Jupyter Lab in order to validate the accuracy of all the Algorithm.



Deployed Ml model into website for CardioVascular Disease Pr

E-comerece Website for Smart India Hackthon

Augmented Reality Educational App - GirlScript India Hackath

Face recognition, as one of the most successful applications of image analysis, has recently gained significant attention, especially during the past several years. Our idea proposes an automatic face recognition attendance system for students using raspberry pi and mini cameras based on deep learning and narrowband Internet of things. The system automatically detects and identifies faces and mark present/absent of students with the help of face detection and it points out the technical challenges of building a face recognition system. The system will automatically update the student’s presence in the class to the student’s database and update all the data to the cloud as well as sends It will message to the guardians of absentees and also to the Head of the department. Face recognition processing, including major components such as face detection, tracking, alignment, and feature extraction, and it points out the technical challenges of building a face recognition system. We focus on the importance of the most successful solutions available so far. The final part of the chapter describes chosen face recognition methods and applications and their potential use in areas not related to face recognition.

Link to Github Repo: https://github.com/iyashjayesh/STUDENT-ATTENDENCE-USING-FACE-RECOGNITION 