When a user inserts a plastic bottle into the receiving slot, the IR sensor detects the bottle and sends the signal to the Raspberry Pi. The processor verifies the input and activates a servo motor to dispense a coin as a reward to the user. If no bottle is detected, the machine does not dispense any reward. The Raspberry Pi operates using a microSD card that stores the operating system and application software, ensuring reliable and efficient system performance.

This project promotes environmental sustainability by encouraging recycling and reducing plastic waste in public places. The automated reward mechanism increases public participation in recycling, helps minimize plastic pollution, and supports cleaner surroundings. The system is suitable for installation in schools, colleges, shopping malls, railway stations, airports, and other public locations to create awareness and improve plastic waste management.

Objectives:

• To develop a smart reverse vending machine for plastic bottle collection and recycling.
• To detect plastic bottles automatically using an IR sensor.
• To control the entire system using a Raspberry Pi Zero processor.
• To reward users by dispensing a coin for every valid plastic bottle deposited.
• To encourage people to recycle plastic waste through an incentive-based system.
• To reduce plastic pollution and promote environmental sustainability.
• To increase public awareness about proper plastic waste disposal and recycling.

Components used:

1. Power Supply.
2. Raspberry pi Zero.
3. SD card.
4. IR Sensor.
5. Servo motor.

Software’s used:

• Python language.
• Raspbian OS.

Block diagram of the project:

video:

In this project, a servo motor is interfaced with the NodeMCU to physically operate the MCB switch. Based on commands received from the web page, the NodeMCU controls the servo motor to turn ON or OFF the MCB. This enables real-time switching and automation without manual intervention.

The system can be further enhanced with sensors to detect abnormal conditions such as overcurrent, overvoltage, or short circuits. When such faults are detected, the controller automatically trips the MCB to prevent damage to electrical equipment and ensure user safety.

Overall, the Smart MCB system provides a reliable, cost-effective, and user-friendly solution for smart energy management, remote control, and electrical fault protection. It is highly suitable for modern smart homes, industries, and energy-efficient systems.

The main Objectives:

  To develop an IoT-based protection system: Design and implement a smart circuit breaker system using a NodeMCU for remote monitoring and control over the internet.

  To enable remote ON/OFF control of MCB: Allow users to operate the MCB from a web interface or mobile device without physical interaction.

  To automate fault detection and protection: Detect abnormal conditions like overcurrent, overvoltage, and short circuits, and automatically trip the MCB to prevent damage.

  To integrate servo motor-based switching mechanism: Use a servo motor to physically operate the MCB switch based on controller commands.

  To provide real-time monitoring of electrical parameters: Monitor system status and electrical conditions continuously through IoT connectivity.

  To improve electrical safety and reliability: Reduce risks of electrical hazards by ensuring quick and automatic response to faults.

  To design a cost-effective and user-friendly system: Develop an affordable solution that is easy to use for homes, industries, and commercial applications.

  To support smart home and industrial automation: Enable integration with modern automation systems for efficient energy management.

  To reduce manual intervention: Minimize human effort in controlling and maintaining electrical systems.

  To enhance energy management efficiency: Provide better control over power usage and system performance.

The major building blocks of this project are:

• Regulated power supply
• NodeMCU Microcontroller.
• Servo Motor.
• Realtime MCB.

Software’s used:

• Embedded C programming.
• Arduino IDE programmer for dumping code into Micro controller.
• Express SCH for Circuit design.

video:

The Pi Camera captures images of all faces of the Rubik’s Cube, and image processing algorithms running on the Raspberry Pi 4 identify the colors and arrangement of the cube blocks. Based on the detected pattern, the system computes the optimal solving sequence using a Rubik’s Cube solving algorithm. The generated commands are transmitted to the Arduino Nano, which controls the servo motors through the motor driver circuit. The rack and pinion mechanism ensures accurate gripping and smooth rotational movement of the cube faces, improving mechanical stability and solving efficiency.

The proposed system demonstrates the integration of robotics, embedded systems, computer vision, and automation techniques to achieve fast and reliable cube solving. This project reduces manual effort, enhances solving accuracy, and provides an effective platform for learning image processing and robotic manipulation concepts. The system can be further enhanced with advanced AI algorithms, wireless monitoring, and faster motor control for real-time industrial and educational robotic applications.

The main objectives of this project are:

  To design and develop an autonomous robotic system capable of solving a Rubik’s Cube automatically using image processing techniques.

  To use a Raspberry Pi 4 for capturing and processing cube images through the Pi Camera module.

  To identify and analyze the color pattern of the Rubik’s Cube using digital image processing algorithms.

  To implement a Rubik’s Cube solving algorithm for generating the shortest and most efficient solution sequence.

  To interface the Arduino Nano with servo motors for precise control of cube movements.

  To develop a rack and pinion mechanism for accurate gripping and smooth rotational movement of the cube faces.

  To synchronize image processing, motor control, and mechanical operations for fully automated cube solving.

  To reduce human effort and improve solving speed and accuracy through robotic automation.

  To demonstrate the practical application of embedded systems, robotics, and computer vision in automation projects.

  To create a scalable system that can be enhanced with AI-based optimization and wireless monitoring in future developments.

The major building blocks of this project are:

1. Adapter power supply.
2. Raspberry pi4.
3. SD card.
4. Pi camera.
5. Arduino nano.
6. Servo motor driver.
7. 8 servo motors.
8. WPVC wood.
9. Rack and Pinion Mechanism.

Software’s used:

• Raspbian OS.
• Express SCH for Circuit design.
• Image processing technology.

video:

When rainwater falls on the rain sensor, it detects the moisture and sends a signal to the microcontroller. The PIC microcontroller then activates the servo motor, which moves the wiper to clear the windshield. When there is no rain detected, the wiper remains in the OFF position. A crystal oscillator is used to provide a stable clock signal to the microcontroller for proper timing operations. The system is powered by a regulated power supply, and LED indicators are used to show the operational status of the system. A reset circuit is included to ensure reliable system startup.

This system eliminates the need for manual switching of the wiper during rainfall, thereby reducing driver distraction and improving road safety. The proposed design is simple, cost-effective, and suitable for basic automatic rain detection applications in automobiles.

Objectives:

• To detect rain using a rain sensor.
• To process the sensor signal using a PIC microcontroller.
• To automatically control the wiper using a servo motor.
• To reduce driver distraction during rainfall.
• To improve vehicle safety and visibility.

The main blocks of this project are:

1. Regulated Power Supply.
2. PIC Microcontroller.
3. Rain sensor.
4. Servo motor.
5. Reset Button.
6. Crystal oscillator.
7. LED Indicators.

Software’s used:

• PIC-C compiler for Embedded C programming.
• PIC kit 2 programmer for dumping code into Micro controller.
• Express SCH for Circuit design.

Block Diagram:

video:

The ESP32 processes the sensor data and uploads the real-time air quality information to the ThingSpeak cloud platform through Wi-Fi, enabling remote monitoring from anywhere. When the detected gas concentration exceeds a predefined threshold, the system activates a buzzer through a buzzer driver to provide an immediate audible warning. Simultaneously, a servo motor automatically opens a ventilation door or window to improve air circulation and reduce the concentration of harmful gases. The system operates using an adapter-based regulated power supply, ensuring reliable and continuous operation.

The proposed solution offers a low-cost, energy-efficient, and intelligent approach for indoor air quality monitoring in homes, laboratories, offices, hospitals, industries, and public buildings. By integrating IoT-based cloud monitoring with automatic ventilation control and real-time alerts, the system enhances safety, minimizes health risks caused by poor air quality, and supports smart building automation.

The features of the project are:

  Real-time Air Quality Monitoring using the MQ-135 gas sensor.

  ESP32-Based Smart Controller for fast data processing and Wi-Fi connectivity.

  IoT Cloud Monitoring with ThingSpeak for remote access to live air quality data.

  Automatic Buzzer Alert when harmful gas levels exceed the safety threshold.

  Automatic Ventilation Control using a servo motor to open a door/window for fresh air circulation.

  Continuous Air Pollution Detection for gases such as CO₂, NH₃, smoke, benzene, and VOCs.

  Wireless Data Transmission through built-in Wi-Fi without additional communication modules.

  Low Power Consumption suitable for continuous 24/7 operation.

  User-Friendly and Cost-Effective Design for homes, offices, industries, and laboratories.

  Scalable System that can be expanded with additional environmental sensors such as temperature, humidity, or particulate matter sensors.

  Real-Time Data Logging and Visualization through cloud-based graphs and historical records.

  Reliable and Automatic Operation with minimal human intervention, improving indoor environmental safety.

The main blocks of this project are:

• Power Supply.
• ESP32.
• MQ135 sensor.
• Buzzer.
• Servo Motor. 

Software’s used:

• Arduino IDE for Embedded C programming.
• Express SCH for Circuit design.
• IoT technology.

video:

This project presents an Obstacle-Avoiding Robot designed with built-in intelligence that navigates autonomously using an algorithm. The robot detects and avoids obstacles, allowing it to move efficiently in unknown environments without human intervention. This flexibility makes obstacle-avoiding robots ideal for dynamic settings, enhancing their overall efficiency.

The ultrasonic sensor is vital for this project. It transmits ultrasonic signal bursts at 40 kHz, which bounce back when an object is detected. The sensor generates high-frequency sound waves and analyzes the echo received to measure the distance to obstacles. By continuously calculating this distance, the ultrasonic sensor enables effective navigation for the Obstacle-Avoiding Robot, ensuring safe and efficient movement. DC motors and l293d motor driver is uses for robot movement with a battery power.

After an obstacle detection, the car changes its direction by making an autonomous decision. It can measure the distance between itself and surrounding objects in real time.

The main objectives of the project are:

1. Designing of a Robot.
2. Obstacle detection and avoiding system.
3. Automatic diversion mechanism.

The major building blocks of this project are:

1. Battery Power Supply.
2. Arduino uno Microcontroller.
3. Obstacle sensor (Ultrasonic sensor).
4. DC motors with driver.
5. Servo motor.

Software’s used:

• Embedded C programming.
• Arduino IDE for dumping code into Micro controller.
• Express SCH for Circuit design.

Block Diagram:

video:

In this system, RFID technology is used for user authentication and book issuing/return processes. Each user is provided with an RFID tag, enabling seamless and fast transactions. A Pi Camera connected to the Raspberry Pi scans QR codes placed on books for quick and accurate identification. All book and student details such as Roll Number, Book Name, Issue Time, Return Time, and Pending Status are stored and managed through a web-based application hosted on the Raspberry Pi. An LCD display provides real-time status updates such as successful issue, return confirmation, or pending alerts. The web portal allows users and administrators to browse books, reserve titles, monitor inventory, and track transaction history remotely.

To enhance security, an advanced theft detection mechanism is implemented at the library entrance. An ESP32-CAM is installed at the gate section to scan QR codes of books during exit. If a book’s details are not found in the central database or if it has not been officially issued, the system identifies it as unauthorized. The ESP32-CAM module communicates with the main Raspberry Pi system through a wired connection. Upon detecting an unissued book, the system activates a buzzer alert and LED indication, and the gate automatically closes using a servo motor mechanism to prevent unauthorized removal. Conversely, if the book is properly issued and verified in the database, the gate remains open, allowing the user to exit smoothly.

By integrating RFID authentication, QR code scanning, real-time web monitoring, automated gate control, and intelligent theft detection, the proposed system significantly reduces manual intervention, improves operational efficiency, ensures accurate record management, and enhances library security. This smart automation solution provides a reliable, scalable, and cost-effective approach for next-generation digital libraries.

Features:

  Centralized control using Raspberry Pi 3B+

  RFID-based user authentication for fast book issue and return

  QR code scanning using Pi Camera for quick book identification

  Web-based real-time database management

  Student account management (Roll No, Book Name, Issue Time, Return Time, Pending Status)

  LCD display for instant transaction feedback

  Online book browsing and reservation through web portal

  Real-time inventory tracking and monitoring

  Theft detection at entrance using ESP32-CAM

  Automatic buzzer alert and LED indication for unauthorized books

  Servo motor-based automatic gate control

  Gate remains open for properly issued books

  Reduced manual intervention and improved operational efficiency

  Enhanced security and accurate record maintenance.

The major building blocks of this project are:

1. Power Supply.
2. Raspberry pi3 B+.
3. Pi Camera.
4. RFID reader and TAGs.
5. LCD display.
6. SD card.
7. Esp32 cam.
8. Servo for Gate.
9. Buzzer.
10. LED indication.

Software’s used:

1. Python programming.
2. Raspbian OS.

video:

The system uses multiple sensors including four flame sensors positioned in four directions, a gas sensor, and a temperature sensor to continuously monitor the surrounding environment. These sensors send real-time data to the ESP32 microcontroller, which processes the information to detect the presence and location of fire. Once a fire is detected, the system automatically rotates a stepper motor controlled through a ULN2003 driver, enabling a 360-degree scanning and targeting mechanism to locate the fire source and a servo motor is used to adjust the direction of the water pump.

After identifying the direction of the fire, the ESP32 activates a relay-controlled DC water pump to spray water toward the affected area to extinguish the flames. Simultaneously, a buzzer alert is triggered to notify nearby people. The system also displays status information such as sensor readings and fire alerts on an LCD display for local monitoring.

In addition, the ESP32 sends real-time data such as temperature, Gas and fire detection status to the IoT cloud platform ThingSpeak, allowing users to remotely monitor the system through the internet. This enables quick response and continuous supervision from anywhere.

The proposed system provides automatic detection, precise fire localization, rapid extinguishing, and remote monitoring, making it a reliable and cost-effective solution for improving fire safety in homes, laboratories, industries, and warehouses.

Objectives:

• To detect fire using flame sensors, gas sensor, and temperature sensor.
• To identify the direction of fire using multiple sensors placed at different angles.
• To rotate the extinguisher mechanism using a stepper motor for 360° coverage.
• To automatically activate a water pump to extinguish fire.
• To provide audio alert using a buzzer during fire detection.
• To display system status on an LCD display.
• To send real-time data to ThingSpeak IoT cloud for remote monitoring.
• To adjust the direction of the water pump using servo motor.

The Major Building Blocks for This Project:

1. Regulated power supply.
2. ESP32 Microcontroller.
3. Stepper motor with ULN2003A.
4. Relay
5. DC Water motor.
6. Four Flame sensors.
7. GAS sensor.
8. Temperature sensor.
9. LCD display.’
10. Buzzer.
11. Servo motor.

Software’s used:

1. Embedded C programming.
2. Arduino IDE for dumping code into Micro controller.
3. Express SCH for Circuit design.
4. THINGSPEAK CLOUD.

Regulated Power Supply:

Block Diagram:

video:

To accommodate different bottle sizes, the water dispensing pipe can be adjusted manually before dispensing. After the user enters and confirms the desired quantity, the Arduino energizes a relay-controlled water pump/motor, initiating water flow. A flow meter sensor continuously measures the volume of water dispensed and provides real-time feedback to the controller. Once the selected quantity is delivered, the Arduino automatically stops the motor and activates the buzzer to notify the user that the dispensing process is complete.

The system also incorporates an ESP8266 Wi-Fi module to upload dispensing data, including water consumption details, to the ThingSpeak cloud platform for remote monitoring and record maintenance. An LCD display provides user instructions and system status, while Bluetooth connectivity enables communication with an Android mobile device. The proposed system offers a hygienic, accurate, secure, and IoT-enabled solution for smart water management in public places, offices, educational institutions, and commercial establishments.

Objectives of Intelli Flow: Smart Water Dispensing System

1. To provide secure access to the water dispensing system using RFID authentication, allowing only authorized users to dispense water.
2. To dispense a user-selected quantity of water accurately through a flow meter-based monitoring and control mechanism.
3. To automate the water dispensing process by controlling the water pump through an Arduino Uno and relay module.
4. To monitor and record water consumption data in real time and upload it to the ThingSpeak cloud platform using the ESP8266 Wi-Fi module.
5. To provide user-friendly operation and alerts through an LCD display, keypad input, and buzzer notifications for system status, completion, and unauthorized access.

Components Used:

• Regulated Power Supply.
• Arduino UNO Microcontroller.
• 4*4 KEYPAD.
• RFID reader and TAGs.
• DC motor for Water Dispenser.
• Flow Meter.
• ESP8266 WI-FI Module.
• Relay Control.
• Buzzer.
• Servo motor.
• I2C with LCD display.

Software’s used:

1. Embedded C programming.
2. Arduino IDE for dumping code into Micro controller.
3. Express SCH for Circuit design.

Regulated Power Supply:

Block Diagram:

video:

Objectives of Self-Balancing Stretcher System:

  To design a self-balancing stretcher that maintains a stable and level position during movement.

  To improve patient safety and comfort by minimizing tilting and sudden movements while transporting patients.

  To monitor the stretcher’s orientation using the ADXL345 accelerometer sensor.

  To automatically correct tilt angles using servo motors controlled by an Arduino Nano.

  To develop a compact and low-cost embedded healthcare solution for patient transportation.

  To monitor the patient’s body temperature continuously using a temperature sensor.

  To provide an audible warning through a buzzer when the patient’s temperature exceeds the preset limit.

  To ensure reliable portable operation using rechargeable lithium-ion batteries with a charging and voltage-boosting system.

  To enhance emergency and hospital transport systems through intelligent automation.

  To demonstrate the application of sensors, microcontrollers, and actuators in modern medical assistance devices.

The main objectives of the project:

1. ARDUINO NANO Microcontroller.
2. Battery power supply.
3. ADXL345 accelerometer.
4. Buzzer.
5. Servo motor.
6. Temperature sensor.

Software’s used:

1. Arduino ide studio compiler for dumping code into Microcontroller.
2. Embedded C language.

video: