TANTROTSAV

Pic-to-toon: Cartoonify your memories

Description: In today’s digital world, image transformation plays a crucial role in various applications, including entertainment, social media, and AI-driven enhancements. However, converting real images into cartoon-style visuals requires advanced techniques that balance artistic creativity with computational efficiency. Traditional methods often struggle to maintain key image details while simplifying colors and textures. This project aims to develop an automated cartoonization system that effectively transforms images while preserving essential features, making it suitable for creative and analytical purposes.

Tech Stack: Python, TensorFlow, Cuda

GitHub: View Code

Analyzing startup growth and investment trends

Description: The Startup Growth and Trend Analysis System is a real-time platform developed using python and Streamlit that provides an overall analysis of startups in india through interactive data visualizations using libraries like Matplotlib,seaborn,and plotly.users can explore different startups,compare their growth over time,and analyze key aspects such as top 5 funded startups top funding cities,and popular funding types.The system also includes role-based access for secure data viewing by investors and executives.overall,it helps stakeholders make informed decisions by offering a clear visual understanding of startup trends and funding patterns.by examining historical funding data,the tool provides interactive charts,graphs to highlight industry-wise investments,active investors,funding rounds and regional distribution .it enables entrepreneurs,investors and policymakers to explore key trends,identify opportunities,and make informed decisions.with clear and engaging visualizations,the application simplifies complex data fostering deeper insight into the dynamics of startup growth and funding in india.

Tech Stack: Python, TensorFlow, Flask

Color Detection using OpenCV

Description: In today’s digital age, the ability to analyze and visualize data efficiently has become a critical skill. One of the most intriguing areas of data analysis is color detection and visual ization, which has wide-ranging applications from digital art to web design and marketing. Addressing this need, our Color Detection application, developed using the powerful Flask web framework, offers a seamless solution for detecting and analyzing colors from user uploaded images. The application allows users to upload images, which are then processed to identify the most prominent colors within the image. By using Python’s versatile libraries like Pillow for image processing and Chart.js for data visualization, this project provides an interactive experience that not only detects color distribution but also displays it through visually appealing charts and graphs. The application leverages powerful Python libraries such as PIL and NumPy to accurately analyze the pixel data of the image and identify the most dominant colors. This ensures reliable and meaningful results, which are then displayed in real-time to the user. The proposed Color Detection project aims to offer a comprehensive and intuitive solu tion for identifying and visualizing the most common colors in images. Focusing on the analysis of color distribution, the system allows users to easily upload images, detect the most prominent colors, and visualize this data through dynamic charts. By incorporating both command-line and graphical user interfaces, the project accommodates a wide range of user preferences and technical skills. In addition to basic color detection, the project includes data visualization, enabling users to gain insights into the distribution of colors through interactive bar and pie charts. This visualization allows users to quickly grasp the prevalence of specific colors within an image, making it an ideal tool for designers, artists, and anyone working with visual content.

Tech Stack: Python

Student Performance Analysis

Description: The Student Performance Analysis System is a comprehensive and user-friendly platform designed to track, analyze, and visualize student academic performance. It replaces traditional manual methods with a structured, automated approach, ensuring improved transparency, accuracy, and efficiency. The system allows students to view their academic records—including semester marks, unit test scores, attendance rates, and technical skills (Java, Python, Web Technology, SQL)—through personalized dashboards. Teachers have secure access to update marks only for their respective subjects. Data visualization plays a central role, using bar charts, pie charts, and line graphs to clearly represent academic trends and performance metrics. Students can identify strengths and areas for improvement, while teachers can make data-informed decisions to support learning outcomes. Additional features include automated report generation, performance range analysis (score brackets such as 40-50, 30-40, etc.), and highlighting top scorers in unit tests. The system promotes secure access control and real-time data updates, ensuring data integrity. Overall, it supports structured academic monitoring and lays the foundation for future integration of predictive analytics and AI-driven insights.

Tech Stack: Python, Matplotlib, Numpy, Pandas

GitHub: View Code

Automated Toll Gate

Description: The Automatic Tollgate System is an advanced toll collection mechanism designed to im prove efficiency, reduce congestion, and minimize manual intervention. The system utilizes an IR sensor to detect the arrival of a vehicle and an I2C module with an LCD display to notify the user. Payments are processed using an RFID-based system, ensuring a quick and seamless transaction. If the user has insufficient balance, the system provides an option to recharge the account using a 4×4 keypad, making it more convenient for travelers. By automating toll collection, this system enhances traffic flow, reduces delays, and improves the overall toll management process. The integration of these technologies results in a cost-effective, scalable, and efficient solution for modern toll plazas.

Hardware Components

• Arduino Uno
• 16x2 LCD Display with I2C
• RFID tage
• 4x4 keypad
• Breadboad & Jumper Wires

Software Requirements

• Arduino IDE
• C++ Programming Language

Smart Obstacle Avoiding Vehicle

Description: An Obstacle Avoiding Vehicle is an autonomous robot designed to navigate through an environment while detecting and avoiding obstacles. This system uses an Arduino UNO as the central controller, which processes inputs from an Ultrasonic Sensor to measure the distance between the vehicle and nearby objects. When an obstacle is detected within a specified range, the vehicle automatically takes action, such as stopping, moving backward, or turning left or right to avoid collisions. The Servo motor is used to rotate the ultrasonic sensor, enabling the vehicle to scan the surroundings in different directions. The L298N H-Bridge motor driver controls the movement of the vehicle's motors, which drive the wheels. This setup allows the vehicle to move forward, backward, or turn based on the information gathered by the sensor. The overall design ensures that the vehicle can autonomously navigate through its environment by continuously adjusting its path to avoid obstacles.

Hardware Components

• Arduino Uno
• Ultrasonic Sensor
• Servo Motor
• DC Motors x 2
• Motor Driver
• Breadboad & Jumper Wires
• 9v Battery
• Switches

Software Requirements

• Arduino IDE
• C++ Programming Language

GitHub: View Code

Smart Parking

Description: The Smart Parking System is an IoT-based solution designed to automate and streamline the vehicle parking process using Arduino Uno, IR sensors, a servo motor, and an LCD display. This system detects the entry and exit of vehicles using two infrared sensors placed at the entrance and exit of the parking area. When a vehicle is detected at the entrance, the system checks the availability of parking slots. If space is available, the servo motor automatically opens the gate, and the available slot count is updated and displayed on the LCD screen. Similarly, when a vehicle exits, the system detects it and updates the slot count accordingly. The aim of this project is to reduce manual intervention, prevent parking space misuse, and provide real-time updates on slot availability. By automating the parking process, the system enhances efficiency, reduces congestion, and improves user experience in crowded parking areas. This prototype can be implemented in malls, offices, and public parking areas, and further expanded with cloud connectivity and mobile app integration for remote monitoring. The entire system is developed using the Arduino platform and is easy to set up, cost-effective, and scalable for larger implementations.

Hardware Components

• Arduino Uno
• Infrared Sensor x 2
• Servo Motor
• 16x2 LCD Display with I2C
• Breadboad & Jumper Wires
• 5V Power Supply

Software Requirements

• Arduino IDE
• C++ Programming Language

GitHub: View Code

Smart Fish Feeder

Description: This project presents the design and implementation of a smart fish feeder using IoT and embedded system technology. Aimed at automating the feeding process in home aquariums, the system addresses the common problem of irregular fish feeding due to the busy lifestyles of pet owners. The core of the project revolves around an Arduino Uno microcontroller, which controls a servo motor to dispense fish food at preset intervals. The feeding schedule can be programmed and customized through serial communication, allowing flexibility based on the needs of different fish species. To enhance usability, an LED indicator provides visual confirmation during each feeding cycle, while a manual ON/OFF switch ensures safe operation and prevents overfeeding or malfunction. The entire setup is powered by an external power supply and battery, ensuring portability and uninterrupted operation even during power outages. The system has been tested for reliability, power efficiency, and feeding accuracy, proving to be an effective and user-friendly solution. By combining automation with real-time feedback and manual control, this project contributes to smart pet care and promotes sustainable fish-keeping practices. In the future it can be modified so that even pets like cats and dogs are fed.

Hardware Components

• Arduino Uno
• D C Motor
• Servo Motor
• Motor Driver
• Breadboad & Jumper Wires
• 9V Battery

Software Requirements

• Arduino IDE
• C++ Programming Language

Smart Juice Dispenser

Description: A Smart Dispenser is an advanced, automated device designed to dispense materials such as liquids, powders, or small solid items in a controlled and efficient manner. It uses sensors, microcontrollers, and often IoT connectivity to detect user presence and accurately deliver a predefined quantity of the substance without the need for physical contact. Commonly used in settings like healthcare, hospitality, and home environments, smart dispensers help promote hygiene, reduce waste, and enhance convenience.

Hardware Components

• Arduino Uno
• D C Motor
• Ultrasonic Sensor
• Pipe
• Breadboad & Jumper Wires
• Switches

Software Requirements

• Arduino IDE
• C++ Programming Language

Rain Detection Alarm

Description: The Internet of Things has revolutionized weather monitoring and automation, enabling smart solutions for everyday challenges. One such innovation is the rain detection alarm with automatic shelter closing, designed to provide protection against unexpected rainfall. This system is especially useful in open spaces such as balconies, parking lots, stadiums, and agricultural fields, where sudden rain can cause inconvenience or damage. This IoT-based system functions using a rain sensor, microcontroller such as Arduino, motorized shelter mechanism, and an alert system. When rain is detected, the sensor trans mits a signal to the microcontroller, which then activates the motorized mechanism to close the shelter. At the same time, an alarm or notification is triggered to inform the user of the weather condition. This automation ensures quick and efficient protection without re quiring manual intervention. The system offers multiple benefits, including automation, real-time monitoring, and remote access via mobile applications or cloud-based platforms. Users can monitor and control the system from anywhere, making it highly effective for smart homes, industries, and agricultural applications. By preventing rain-related damage, this technology also helps protect valuable assets and equipment. Future advancements in IoT can further enhance this system by integrating weather prediction data and AI-based decision-making. This would improve efficiency by enabling the system to take preventive actions based on upcoming weather forecasts. As technology continues to evolve, such smart solutions will play a crucial role in creating a safer, more convenient, and automated lifestyle.

Hardware Components

• Arduino Uno
• Rain Sensor
• DC Motors x 2
• Buzzer
• Motor Driver
• Breadboad & Jumper Wires

Software Requirements

• Arduino IDE
• C++ Programming Language

GitHub: View Code

Smart Door System

Description: The Smart Door Lock System using a Password Pattern is a modern, IoT-based security solution designed to enhance safety and convenience by replacing traditional keys with a programmable access system. At the heart of this project is the Arduino UNO, which acts as the main controller. It interfaces with a 4×4 matrix keypad for password input, an LCD display with an I2C module for real-time feedback, and a servo motor that controls the physical locking and unlocking of the door. When a user inputs a password via the keypad, the Arduino compares it with a predefined password. If the password is correct, the system displays “Access Granted” on the LCD and activates the servo motor to unlock the door. If incorrect, access is denied and an appropriate message is shown. All components are connected using jumper wires, ensuring a clean and efficient hardware setup. This project presents a low-cost and scalable alternative to conventional door locking systems. It is ideal for homes, offices, and restricted areas. Future enhancements may include features like fingerprint scanning, Bluetooth or Wi-Fi control, and integration with smart home ecosystems, making the system more versatile and secure. This project effectively showcases how IoT can be applied in everyday life to improve security systems.

Hardware Components

• Arduino Uno
• 4x4 keypad
• Servo Motor
• Breadboad & Jumper Wires

Software Requirements

• Arduino IDE
• C++ Programming Language

Smart Dustbin

Description: Maintaining cleanliness and hygiene has become a crucial concern, especially in indoor environments like homes, offices, schools, and hospitals. One of the most common sources of contamination is the traditional dustbin, which requires manual handling for disposing of waste. To address this problem, we have developed an IoT-based smart dustbin that provides a touch-free waste disposal solution using basic electronic components. This project uses an Arduino Uno microcontroller as the core of the system, along with an ultrasonic sensor, servo motor, and battery power supply to operate efficiently in an indoor setting. The working principle of the smart dustbin is simple yet effective. The ultrasonic sensor continuously monitors for any object (like a user's hand or a waste item) within a certain range. Once it detects an object, it sends a signal to the Arduino, which in turn activates the servo motor to open the lid of the dustbin. After a short delay, which gives the user enough time to throw in the waste, the lid closes automatically. This smart mechanism ensures that the user does not need to touch the dustbin at any point, thereby reducing the chances of spreading germs or viruses through physical contact. The main objective of this project is to encourage safe and hygienic waste disposal, particularly in closed and frequently used spaces. While the model is simple and cost-effective, it showcases the potential of using IoT and automation to improve everyday tasks. This smart dustbin not only helps in reducing the risk of contamination but also promotes cleanliness and ease of use for all age groups. Its design is compact, power-efficient, and easy to install in various indoor settings. In conclusion, this project demonstrates how basic IoT integration can lead to practical and health-focused innovations for a cleaner living environment.

Hardware Components

• Arduino Uno
• Ultrasonic Sensor
• Servo Motor
• Breadboad & Jumper Wires

Software Requirements

• Arduino IDE
• C++ Programming Language

Real Time Object Detection with Description

Description: Ensuring workplace safety in hazardous environments like construction sites and factories is a significant challenge for employers and safety managers. Despite strict regulations, incidents of workers neglecting Personal Protective Equipment (PPE) continue to pose serious risks, leading to accidents and legal consequences. Traditional monitoring methods are often manual, inefficient, and prone to human error, making it difficult to ensure consistent compliance with safety standards. To address this critical issue, we propose a Real-Time Safety Detection System Using IoT. Utilizing components like Arduino Uno and ESP32 Camera, the system continuously captures real-time images from the workplace. Advanced image processing algorithms analyze the images to detect whether workers are wearing essential PPE, such as helmets, gloves, and vests. If any safety violation is identified, the system immediately triggers an alert message, notifying supervisors and relevant personnel. This automated approach ensures proactive safety management by providing instant notifications, enabling swift corrective actions. The system promotes a safer work environment, minimizes the risk of accidents, and enhances compliance with safety regulations. By leveraging IoT technology, our solution offers a cost-effective and reliable means of improving workplace safety, fostering accountability, and protecting workers’ well-being.

Hardware Components

• Arduino Uno
• ESP32 Camera
• Jumper Wires

Software Requirements

• Arduino IDE
• C++ Programming Language

Voice Assistant Smart Switch

Description: This project aims to develop a cost-effective, scalable, and energy-efficient smart home automation system using IoT technologies. The system enhances home accessibility, comfort, and energy savings by integrating voice, web, and manual controls. It utilizes a NodeMCU ESP8266 Wi-Fi module for remote access, a Bluetooth module for local control, and a relay module to operate household appliances. Voice commands are enabled through the Arduino Bluetooth Controller app, allowing users to control devices effortlessly. The NodeMCU offers Wi-Fi-based web interface access, while manual switches ensure continued functionality in case of connectivity issues. The relay module acts as a bridge between control inputs and appliances, executing instructions reliably. Designed with user-friendliness in mind, this system is ideal for modern households seeking smart solutions with minimal power consumption. It provides seamless operation, making smart living more accessible and practical.

Hardware Components

• NodeMCU ESP8266 Wi-Fi Module
• Bluetooth Module
• Relay Module
• Bulb & Switches

Software Requirements

• Arduino IDE
• C++ Programming Language

GitHub: View Code

Smart Weather Forecasting

Description: Weather forecasting is a critical aspect of modern life, impacting sectors such as agriculture, transportation, disaster management, and urban planning. Accurate weather predictions help in preparing for extreme conditions, optimizing resource utilization, and enhancing safety measures. Traditional weather monitoring systems rely on large-scale infrastructure, satellite data, and meteorological models, which may not always provide localized and realtime weather insights. To address these limitations, the integration of the Internet of Things (IoT) has emerged as a transformative solution for weather forecasting. This project presents an IoT-based weather monitoring system that utilizes rain and temperature sensors to measure environmental parameters in real-time. The system is designed to collect, process, and transmit weather-related data to a central server, where it can be stored and analyzed. By leveraging IoT technology, the system provides continuous and remote monitoring capabilities, enabling users to access weather updates from anywhere via cloud-based platforms. The collected data can be used for predictive analytics, helping users anticipate weather patterns and make informed decisions.

Hardware Components

• NodeMCU ESP8266 Wi-Fi Module
• Temperature & Humidity Sensor
• Rain Sensor
• 16x2 LCD Display with I2C
• Breadboad & Jumper Wires

Software Requirements

• Arduino IDE
• C++ Programming Language

Food Waste Management System

Description: A Food Donation System is an online platform designed to connect food donors with those in need, helping to reduce food waste and fight hunger. This system allows individuals, restaurants, hotels, supermarkets, and other food providers to donate excess or unused food easily. Registered donors can upload details about the food, including its type, quantity, and expiry time. On the other hand, NGOs, charity organizations, or needy individuals can view available donations and request food as per their requirements. The system ensures safe and timely distribution of food, promoting social responsibility and community support. It can also include features like real-time tracking, notifications, and location-based searches to make the donation process quick and efficient. The admin manages users, monitors donations, and ensures fair distribution. By using a Food Donation System, both food donors and receivers benefit while contributing to a greater cause — minimizing food wastage and supporting people suffering from hunger. This system not only helps the environment but also encourages kindness and unity in society.

Tech Stack: HTML5, CSS3, JavaScript, SQL, PHP

GitHub: View Code

SafeWalk: Ensuring Women Saftey in Public Spaces

Description: The safety of women in public spaces remains a critical global issue, significantly affecting their freedom, participation, and overall well-being. Alarming statistics indicate that one in three women worldwide may experience physical or sexual violence in their lifetime, underscoring the urgent need for effective intervention. Persistent threats such as verbal and physical harassment, assault, and the constant fear of violence restrict women's mobility and public engagement, depriving them of their sense of security and independence. This initiative introduces a comprehensive, technology-driven approach to enhance women's safety in public areas by integrating advanced solutions, community involvement, and strategic partnerships. The primary objective is to develop an all-in-one system that ensures both psychological and physical security for women navigating public spaces. Key features include a user-friendly mobile app built using React Native for seamless communication, Next.js powers the implementation of real-time safety insights through community-based reporting, incident reporting and SOS emergency alert button for instant assistance. Additionally, the system integrates Firebase for secure user and admin authentication, ensuring a reliable and protected access system. Also, the system includes identification of safety zones for the users. By implementing these essential features, the project empowers women with a renewed sense of confidence and security, enabling them to reclaim public spaces without fear. Beyond being a technological solution, this initiative represents a broader societal commitment to safeguarding women's rights and dignity. Through strategic planning, innovation, and collaboration, the project aims to establish a new benchmark for public safety and diversity.

Tech Stack: Typescript, Next.js, CSS

GitHub: View Code

KSRTC Bus Notification System

Description: The KSRTC Rural Bus Notification System is a web-based application that sends real-time updates and messages to passengers on bus availability, routes, and delays. The system is made up of two main modules: Admin and User. The Admin module enables authorized workers to control bus routes using CRUD (Create, Read, Update, Delete) operations and to send notifications of delays or route cancellations. The User module allows passengers to view bus schedules, check route availability, find nearby stations, and receive email notifications about cancellations and delays. There is also map integration that helps users locate all nearby bus stations within a 5 km range. This system increases the efficiency of public transportation by keeping passengers informed, minimizing uncertainty, and improving their overall trip experience. It is intended to be user-friendly, with seamless access to information for both administrators and passengers. This system acts as a connection between passengers and the Karnataka State Road Transport Corporation, promoting a more transparent and dependable public transportation system

Tech Stack: Java

GitHub: View Code