Indian Startup Competition: A Tale of Innovation and Inspiration

STARTUP

In the heart of the bustling entrepreneurial landscape of India, an exciting event unfolded that would redefine my perspective on innovation and drive. The Indian Startup Competition, hosted by Mangalmay Institute of Engineering and Technology, became a transformative experience that took me on a rollercoaster ride of creativity, teamwork, and inspiration.

INVITATION

Amid the picturesque campus of Mangalmay Institute, the vibrant energy of budding entrepreneurs and innovators from across the country was palpable. The air was charged with anticipation as participants, each armed with a unique business idea, gathered to showcase their entrepreneurial prowess.

The Opening Ceremony: Igniting the Spark

The event kicked off with an electrifying opening ceremony, featuring inspiring speeches from industry leaders who shared their insights on the startup ecosystem in India. The collective aspiration to make a difference was infectious, and I felt an immediate connection to the community of like-minded individuals.

The Pitch: Nerves and Brilliance Collide

As I stepped onto the stage to present my startup idea, a wave of excitement and nervousness surged through me. The panel of esteemed judges, veterans of the startup world, awaited our pitches with discerning eyes. Each pitch was a testament to the innovation and creativity that thrives within our country.

Networking: Forging Connections Beyond Borders

Between rounds, I found myself engaged in conversations that transcended geographical boundaries. Entrepreneurs from different corners of India shared their experiences, challenges, and dreams. This exchange of ideas ignited a fire within me, reaffirming that entrepreneurship is a language spoken universally.

Workshops and Insights: Expanding Horizons

The competition wasn’t just about the pitches; it was also a learning platform. Engaging workshops on topics like business strategy, market analysis, and funding opportunities enriched our understanding of the startup landscape. These insights were invaluable, providing us with tools to turn our dreams into realities.

The Grand Finale: Celebrating Innovation

The crescendo of the event was the grand finale, where the top contenders showcased their refined pitches. The diversity of ideas, from tech solutions to social enterprises, was a testament to the power of innovation. The judges had a tough task at hand, as every pitch held the potential to change lives.

The Takeaways: More than a Competition

Looking back, the Indian Startup Competition wasn’t just about winning or losing. It was about the bonds formed, the lessons learned, and the dreams kindled. It reinforced that success is built on passion, perseverance, and the willingness to learn from both victories and setbacks.

Conclusion: A New Beginning

As the curtains drew to a close on the competition, I carried with me not just memories, but a renewed sense of purpose. The experience pushed me to push my boundaries, dream bigger, and believe that every idea, no matter how audacious, has the potential to shape the future.

The Indian Startup Competition at Mangalmay Institute was more than an event; it was a journey of self-discovery, camaraderie, and the celebration of innovation that India’s entrepreneurial spirit embodies. As I continue my journey, I’m grateful for the opportunity to be part of such an inspiring chapter in the entrepreneurial saga of our nation.

Machine Learning Based Air Quality Prediction:

Machine Learning

New Delhi Okhla Phase II Area Case Study

Sahil Negi

Computers can now learn without being explicitly programmed thanks to the discipline of machine learning.One of the most intriguing technologies ever is machine learning. As the name suggests, it gives computers what makes them more human: the ability to learn.

Air pollution has been one of the most important problems in human evolution over the last century because of its detrimental impact on the ecosystem of humans. The research presented in this article focused on using machine learning to predict behavior related to air quality.

Central Pollution Control Board: CPCB is a source from where data is collected to validate the model. In this paper, the Okhla Phase II area in New Delhi was selected as the study target, which suffers from severe air pollution. Based on CPCB data on major air pollutants from February 2018 to November 2022. The paper initially included monthly air quality assessments. The findings show that air quality in the Okhla Phase II region generally follows the same trend with respect to historical assessments during the study period. According to this study, a significant proportion of Okhla phase II air pollution is attributed to the pollutants PM2.5, PM10, NO2, and CO. Therefore, the study was conducted to determine air quality based on Particulate Matter 2.5, Particulate Matter 10, Nitrogen Dioxide, and Carbon Monoxide pollution concentrations in Okhla phase II. Air quality prediction used data based on CPCB from February 2018 to November 2022 for key air pollutants and machine learning techniques were used. These methods include linear regression, decision tree regressor, random forest regressor, support vector regressors, and the K Nearest Neighbour method for air quality prediction. The Study found that Random Forest Regressor was the most reliable algorithm for predicting air pollution, with a result of 99.3%.

Combined PM2.5, PM10, NO2, and CO

Check the Pairplot Graph.

Sources of pollution

We know that there are 5 key sources of pollution:

a. Vehicles – There is an increasing number of highly polluting vehicles such as trucks and diesel vehicles, and vehicles that negate the impact of clean fuel and emission technologies.

b. Combustion in power plants and industries using dirty fuels such as petroleum coke, FO (and its variants), coal,  biomass

c. Waste incineration, landfill, and other collection, and treatment.

d. Dust management on roads, construction sites, etc. causes fine dust pollution.

e. Farmers burn crop residues as they have no choice but to use straws.

The Air Quality Index

It Shows the Air Category wrt AQI Range

By CPCB

One of the biggest issues affecting individuals in metropolitan areas is air pollution. The issue is caused by a huge number of motor vehicles, industrial output emissions, and the combustion of petroleum products for power generation and transportation.

Over the past decades, two general approaches of have been used to predict air pollution: deterministic and probabilistic. One of the deterministic techniques created in diverse places to analyze and monitor air pollution is diffusion modeling. These models’ results are influenced by their input data, and their use requires access to data on the distribution and diffusion of pollutants in the atmosphere Therefore, it is sufficient to use these models. Since the data collecting necessary for diffusion models is challenging and impractical on a broad scale, researchers have moved to more effective techniques like statistical modeling. Statistical approaches have more uses for forecasting air pollution than deterministic methods do.

Download Research Paper

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Download Python Code

IoT Based Hand Gesture Project

Project

Problem Statement

It is difficult to make a presentation while standing behind podium and thinking that your audience is engaging with you and the presentation is going well . An interactive presentation includes stage covering and for that we need a helping hand who can handle our presentation . or if we own handle our ppt by going back to monitor again and again will reduce the audience retention

Features and Benefits

We can make Environment in which our hand will interact with the monitor and work like a mouse. Our technology is helping to make an Interactive and futuristic environment. Replacing human source need to handle our presentation such that to go to the next slide or to the previous slide we have to call him again and again. Which decreases the focus of the presentation. Our technology will help more audience retention. Instead of having a helping hand who will handle our presentation we can own now handle our presentation. Which Increases the focus of the presentation. Our technology will help with more audience retention.
Technology will help people to make their audience more. Engaging and helping to make presentations interactive. which we can use in business, schools, college, universities

Tech Preksha At Aravalli College

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Presentation

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Prototype

Project Development

Presentation

Eateo

Project

A Food Recommendation System is an artificial intelligence-driven platform that provides personalized food suggestions based on user preferences, dietary requirements, and nutritional goals. The system utilizes machine learning algorithms to provide accurate food recommendations from a large database of food choices. The system also takes into account user-specified preferences, dietary restrictions, and nutrition goals. The overall goal of the system is to help users make better food choices that are tailored to their individual needs.

Abstract

Eateo aims to explore the needs and preferences of customers who travel regularly for work, studies, or other purposes, and how to better meet their needs for food options. It will also consider how to optimize their experience with food choices and explore options that cater to their individual tastes and preferences

Eateo has great potential for development in India. The growth of the mobile app helping markets to grow. The food Recommendation system will become popular among people who search for relevant information about food. In this paper, the EATEO food recommendation application is studied in detail. Users could find food that matches their tastes in the shortest time. This app-based on AI Chatbot that can efficiently manage time and finances by making it easy for consumers to easily access the information they want anytime, anywhere. By analyzing the customer needs Eateo will work for the customer’s convenience. For the recommendation system, we put forward a recommendation algorithm based on the rank-centroid/analytic hierarchy process. In this paper, an artificial intelligence chatbot-based food recommendation app using personalized information is proposed. The recommendation service app utilizes personalized information such as gender, age, interests, occupation, favorite dish search records, visit records, wish lists, reviews, and real-time location information. Through the recent dishes that the user likes to have, transforming it to preferences of the user into the Eateo app and using this algorithm, we will establish a model, so that users can get recommendations for food that fit their mood through chatting AI chatbot. Furthermore, EATEO makes possible to check real-time information about restaurants famous dish and can write reviews. The proposed app uses a collaborative filtering recommendation system, through users dining out information using artificial intelligence chatbots. Through chatbots, users can receive customized taste food using personal information while minimizing time and space limitations.

Introduction

While India has always been a food-loving country with each region having its own special cuisine, Indians have never been very big on eating out. But all that is changing now. As everything is going to be digital now and consumer’s want everything at one click.

So EATEO is here which will understand the mood of consumer and recommend food that matches their tastes in the shortest time. This app-based on AI Chatbot that can efficiently manage time and finances by making it easy for consumers to easily access the information they want anytime, anywhere. By analyzing the consumer mood at particular time. As consumer may have different mood at different period of time. Such that at night consumer mood is diiferent comparing to day time and consumer wants something else in afternoon. This varies in mood, time, taste, places and people which is a very huge data and deep concept of understanding consumer needs.  it can take very long time to understand the customer. But EATEO systematic algorithm will understand the consumer preference by analyzing answers of different categories from user. To make it efficient for customer to take what they want.

The restaurant industry in India has been growing at a rapid pace over the last decade or so and the growth story is set to continue for the next foreseeable future. EATEO has a very vast scope in food app. As with EATEO sales can be increased by 25% as it covers main needs of customers. By food Recommendation system. There were nearly 22 lakh hotel and restaurant establishments in India in 2002. The food service or restaurant industry was worth a whopping Rs. 43,000 crores in 2010 and growing at a healthy rate of 15-20 percent annually. Solving customer’s need and fulfilling their demand is our first priority and Eateo will work for the customer’s convenience.

Literature survey

EATEO will be designed  to drive those customers attention who travel for work, job, studies on daily basis or who wants to take food according to his taste and preferences.


This research aims to develop a system that enables users to quickly and accurately identify food items that match their tastes in the shortest possible time. The system will explore various data sources to create a personalized food recommendation engine, which will utilize machine learning algorithms to analyze user preferences and provide tailored food suggestions. Additionally, the system will incorporate user feedback to continually refine and improve its food recommendation capabilities. The ultimate goal is to provide users with an efficient and customized food discovery experience.

EATEO focuses on the customers who are confused in choosing between different types of dishes.  According to our research there is no such or similar patent for this issue.
This research aims to develop a method for quickly and accurately identifying food choices that match a user’s individual tastes. The method will analyze individual user preferences and offer suggestions for food items that match the user’s taste. The goal is to provide users with a streamlined and efficient process for quickly finding food that is tailored to their personal taste.

Eateo

AWS Solution Architecture Virtual Internship

internship

Hi,
These Are the Solutions I have Proposed To One of AWS Client #aws
Send Me More Solutions Architecture for Client Problem
Hope You Like My Solutions
and Discuss With Me For The 2nd Solution of AWS Solutions Architecture

Best Regards,
Sahil Negi

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I’m happy to share that I’ve obtained a new certification: Solutions Architecture Virtual Experience Program from Amazon!
#amazon #architecture

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contact – Negisahil1960@gmail.com