The objectives of the project include:

• To interface R307 fingerprint module with Raspberry Pi.
• To store fingerprint templates with corresponding blood groups.
• To display blood group information on LCD using I2C.
• To generate buzzer alert for wrong fingerprint detection.
• To develop a web page for registration and database management.
• To enable Wi-Fi-based remote access.

The major building blocks of this project are:

• Regulated power supply.
• Raspberry pi zero 2w.
• Fingerprint module.
• LCD display.
• Buzzer.
• SD card.

Software’s used:

• Raspbian OS.
• WEB technology.
• Express SCH for Circuit design.

video:

This system is built around an ESP32 microcontroller that continuously collects and processes data from multiple onboard sensors. An MPU6050 gyroscope monitors ship tilt and orientation across the X, Y, and Z axes to ensure stability during operation. A load cell measures weight variations to detect imbalance or overload conditions, while an ultrasonic sensor (SR04) identifies nearby obstacles to prevent collisions and ensure safe navigation.

The ship’s propulsion is controlled using dual DC motors driven by an L298 motor driver, enabling directional movement via a web-based interface. Additionally, an oil spill collection mechanism is integrated using a belt-driven DC motor controlled through a MOSFET switching circuit. This allows remote activation of the oil collection belt to gather surface oil contaminants efficiently.

All critical parameters — including ship orientation, obstacle distance, load weight, propulsion movement, and oil belt status — are transmitted in real time to a web dashboard via ESP32 Wi-Fi connectivity. This enables remote monitoring and control of ship navigation and pollution management systems from any location.

Powered by a Li-ion battery system, the proposed design promotes sustainable marine operations by combining smart navigation safety with environmental cleanup functionality. The system provides a low-cost, scalable solution for future autonomous marine vessels focused on both operational safety and ecological preservation.

Objectives:

 To monitor ship stability in real-time:
Using the MPU6050 gyroscope to measure tilt and orientation along X, Y, and Z axes to prevent imbalance and ensure safe navigation.

 To detect obstacles and avoid collisions:
By integrating an ultrasonic sensor (SR04) to measure the distance of nearby objects in the ship’s path.

 To measure onboard load conditions:
Using a load cell to monitor weight distribution and detect overload or imbalance situations.

 To enable remote ship navigation:
Controlling propulsion motors through a web-based interface using ESP32 Wi-Fi connectivity.

 To integrate an automated oil spill collection system:
Operating a belt-driven oil collector using a MOSFET-controlled DC motor.

 To provide real-time web monitoring:
Displaying ship tilt (XYZ axis), obstacle distance, load weight, movement status, and oil belt operation on a live dashboard.

 To enhance marine safety:
By continuously monitoring ship movement and environmental conditions.

 To support environmental protection:
Through efficient detection and collection of oil spills from water surfaces.

 To develop a smart and energy-efficient system:
Powered by a Li-ion battery for sustainable marine operations.

 To create a low-cost IoT-based smart ship model:
That combines safety monitoring with pollution control.

The major building blocks of this project are:

• Li-ion Battery Power supply.
• ESP32.
• Ultrasonic sensor.
• Mpu6050 Gyro scope.
• Load cell.
• DC Motors with L298.
• DC motor for belt movement.

Software’s used:

• ARDUINO IDE.
• Embedded C language.
• WEB Technology.

Block Diagram:

video:

An Arduino Nano serves as the central control unit, monitoring system battery voltage using voltage sensor. The transmitted wireless power is received by a secondary coil in the receiving vehicle, converted from AC to DC, and regulated using a TP4056 charging module to safely charge a 3.7V Li-ion battery. Continuously monitor the battery voltage on LCD display, while a buzzer provides audible alerts for fault or threshold conditions.

This system eliminates the need for conventional charging cables, reduces wear and tear of connectors, and enhances safety and convenience. The proposed V2V wireless charging model demonstrates a practical solution for emergency charging, roadside assistance, and smart EV ecosystems, contributing toward sustainable and intelligent transportation systems.

The main objectives of the project are:

 To design a wireless charging system for electric vehicles.

  To enable vehicle-to-vehicle power transfer without using physical cables.

  To use inductive coupling for safe and efficient wireless energy transmission.

  To monitor battery voltage using sensor.

  To control and manage the system using an Arduino Nano.

  To display charging status and voltage on an LCD display.

  To provide alerts using a buzzer for abnormal conditions.

  To demonstrate a safe and portable charging solution for emergency situations.

The major building blocks of the project are:

• Regulated power supply.
• 12V Rechargeable Battery.
• Arduino NANO Microcontroller.
• Wireless Power Transmitting and Receiving Coil
• Voltage sensor.
• LCD display.
• Buzzer.
• Pulse generator.
• TP4056IC.
• 7V LI –ION Battery.

Software’s used:

1. Arduino IDE for compiling and dumping code into controller
2. Express SCH for Circuit design.

video:

The purpose of this project is to design and construct a solar tracker system that follows the sun direction for producing maximum out for solar powered applications at IOT based dual axis using DC motor and platform.

This project consists of few sun light sensors and a motorized mechanism for rotating the panel in the direction of sun. This system works continuously without any interruption. The main controlling device of the whole system is an Arduino nano Microcontroller. Solar panel along with voltage sensor, limit switches, loads, ESP8266 WI-FI and LDRs are interfaced to Microcontroller. The Microcontroller initially measures the voltage and WATTS from solar panel and will be send to the blynk mobile application through ESP8266 WI-FI Module. Microcontroller based control system takes care of sensing sunlight and controlling the motorized mechanism using DC motors. Limit switches are used to sense the tracking mechanism. Solar panel energy is obtained stored into the battery through charging circuit and this battery power is used to turn ON the loads will be controlled by the user from blynk mobile application. To perform this intelligent task, Microcontroller is loaded with an intelligent program written using embedded ‘C’ language.

The main objectives of the project are:

• Tracks sun direction automatically.
• Starts automatically in the morning (initial position).
• Solar panel moves using DC motor.
• Uses IoT technology.
• Monitors voltage & power in Blynk app.
• Controls loads remotely via mobile.

The major building blocks of this project are:

• Arduino Nano Microcontroller.
• Sun light Sensor to sense the sun direction.
• Motorized mechanism to control the position of solar panel.
• Limit switches.
• ESP8266 WI-FI module.
• Charging circuit.
• Rechargeable battery.
• 7805 voltage regulators.
• Two LEDs.

Software’s used:

• Arduino IDE compiler for Embedded C programming.
• Express SCH for Circuit design.
• Blynk mobile application.

Block Diagram:

video:

The robot section is controlled by a microcontroller interfaced with DC motors driven by an L298N motor driver for movement. An ESP32-CAM module provides real-time live video streaming, enabling remote visual monitoring through a mobile device. LoRa technology is used for long-range, low-power wireless communication between the robot unit and the remote-control section, where delivery status and alerts are displayed on an LCD.

To enhance security, a vibration sensor detects unauthorized handling or theft attempts or battery voltage goes low immediately triggering a buzzer alert and sending warning messages to the remote unit. An ultrasonic sensor detects obstacles, and upon detection, the microcontroller activates blue alert lights to ensure safe navigation. Battery voltage and current are continuously monitored to provide low-battery alerts.

At the destination, access to the parcel compartment is protected using a password-based locking system. A 4×4 keypad mounted on the robot allows the user to enter the password. If the correct password is entered, the solenoid lock opens for a predefined duration and closes automatically afterward. Multiple incorrect password attempts trigger an alert to prevent unauthorized access.

Overall, the proposed system provides a secure, intelligent, and remotely monitored delivery solution suitable for food delivery, courier services, and e-commerce applications, combining live streaming, theft detection, obstacle avoidance, and secure access control in a single robotic platform.

The objectives of the project include:

1. To design an RC-based delivery robot for food and e-commerce applications.
2. To enable long-range wireless control and alert communication using LoRa.
3. To provide live video monitoring using the ESP32-CAM.
4. To implement theft detection and security using sensors and alerts.
5. To ensure secure parcel delivery through a password-protected locking system.
6. To detect obstacles and provide alert indications for safe navigation.
7. To monitor battery status and display system information on an LCD.

The major building blocks of this project are:

• Rechargeable battery.
• ESP32 Camera.
• Arduino Nano.
• DC Motors with L293D driver.
• Blue light.
• Head light.
• Ultrasonic sensor.
• DC motor with l298 driver.
• Buzzer.
• Keypad.
• PIC Microcontroller.
• LCD display.
• Voltage &Current sensor.
• Solenoid Lock.
• Vibration sensor.
• Relay.
• LoRa Modules.

Software’s used:

1. Arduino IDE for compiling and dumping code into ESP32 Camera and Arduino NANO.
2. PIC-C compiler for Embedded C programming.
3. PIC kit 2 programmer for dumping code into PIC Micro controller.
4. Express SCH for Circuit design.

video:

The solar panel is connected to a charging circuit that charges a rechargeable battery for energy storage. Voltage and current sensors monitor the solar panel output, and a voltage sensor tracks battery voltage to ensure efficient power management. The system also measures environmental parameters such as temperature and humidity using a DHT11 sensor to analyze their effect on solar performance. In this system, LEDs are used as the primary load, which can be switched ON or OFF through the switch. Additionally, a water pump is integrated to pump the water on the solar panel surface to reduce temperature and remove dust, thereby improving panel efficiency which can be switched ON or OFF through the switch.

An ESP8266 Wi-Fi module enables real-time data transmission to the ThingSpeak cloud platform, allowing remote monitoring of solar voltage, current, battery voltage, temperature, and humidity. The floating design allows installation on water bodies, improving cooling efficiency and optimizing land utilization. Overall, the system provides an automated, intelligent, and remotely monitored solar tracking solution that improves solar power generation efficiency and supports sustainable energy management.

The main objectives of the project are:

  To design a dual-axis solar tracking mechanism.

  To maximize solar energy output using LDR-based tracking.

  To implement battery charging and energy storage.

  To monitor voltage, current, temperature, and humidity.

  To integrate IoT for real-time cloud monitoring.

  To implement a water cooling and cleaning mechanism.

  To develop a floating platform for improved cooling and land optimization.

The major building blocks of this project are:

1. Charging Circuit.
2. Rechargeable Battery.
3. Solar Panel.
4. PIC Microcontroller.
5. Sun light Sensor to sense the sun direction.(LDRs)
6. Motorized mechanism to control the position of solar panel(DC motors with L293D driver)
7. Limit switches.
8. Voltage sensors.
9. Current Sensor.
10. DHT11 sensor:
11. ESP8266 WI-FI Module.
12. LEDs as load.
13. Water pump.

Software’s used:

1. PIC-C compiler for Embedded C programming.
2. PIC kit 2 programmer for dumping code into Microcontroller.
3. Express SCH for Circuit design.
4. IOT thingspeak technology.

video:

The system uses Infrared (IR) sensors installed on both sides of the road to continuously monitor vehicle density. These sensors send real-time data to a PIC microcontroller, which processes the traffic conditions and determines which side of the road has higher congestion. Based on this analysis, the controller actuates servo motors that automatically shift the road divider toward the less congested side, thereby increasing lane space for the high-density traffic flow.

A regulated power supply ensures stable operation of the system, while a crystal oscillator maintains precise timing for accurate processing. The system also includes an LCD display to show traffic status and divider position, along with LED indicators for visual alerts. A reset button is provided for manual system restart if required.

This automated approach improves road space utilization, reduces traffic congestion, minimizes travel time, and enhances overall traffic management efficiency without requiring manual intervention. The proposed system is cost-effective, scalable, and suitable for implementation in high-traffic urban areas.

Objectives:

• To analyze traffic conditions using a PIC microcontroller
• To automatically adjust the road divider position
• To allocate more road space to high-density traffic
• To reduce traffic congestion
• To improve traffic flow efficiency
• To minimize travel delays
• To enable automatic traffic management
• To enhance road safety
• To develop a cost-effective smart traffic solution
• To monitor traffic density using IR sensors.

The major blocks of the project:

1. PIC microcontroller.
2. Regulated Power supply.
3. FOUR IR sensor
4. LCD display
5. Servo motor.
6. Crystal oscillator.
7. Reset Button.
8. LED indicator.

Software’s used:

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

video:

The sensor data is acquired and conditioned by an Arduino Nano and transmitted to a Raspberry Pi Zero 2W for advanced analysis. The Raspberry Pi processes the incoming data to calculate a stress score ranging from 0 to 100, representing the user’s current mental stress level. Based on this score, intelligent decision logic determines the system response.

When the stress level exceeds a predefined threshold, the Raspberry Pi automatically activates a relay to drive an integrated massage unit, providing immediate physical relaxation. In addition to automatic control, the system also offers a user-controlled massager through a web-based interface, allowing the user to manually turn the massager ON or OFF at any time without affecting EEG and GSR signal acquisition.

The Raspberry Pi Zero 2W generates alert messages and notifications during high-stress conditions and logs all sensor data and stress scores on an SD card for future analysis. A dedicated web page displays real-time stress levels, historical trends, and personalized AI-based recommendations such as relaxation exercises and breathing techniques.

Powered by a Li-ion battery, the proposed wearable head cap is compact, portable, and energy efficient. The system provides a comprehensive solution for mental fatigue monitoring, stress reduction, and user-centric control, making it suitable for healthcare monitoring, workplace wellness, and safety-critical applications.

The major Objectives of this project are:

• To acquire EEG and GSR signals related to mental stress
• To process sensor data and compute a stress score (0–100)
• To automatically activate a massage unit during high stress
• To provide a web-based interface for real-time monitoring and control
• To log stress data for future analysis and trends
• To generate AI-based stress relief recommendations

The major building blocks of this project are:

1. Li-ion Battery Power Supply.
2. Raspberry pi Zero 2W.
3. SD Card.
4. EEG amplifier bio amp EXG pill.
5. GSR.
6. Relay along with Massage.
7. Arduino nano.
8. CAP.

Software’s used:

• Python programming.
• Raspbian OS.

3. Express SCH for Circuit design.

• WEB technology.

video:

The important parameters for the quality and productivity of plant growth are soil and air temperature, humidity and soil moisture. The plant health and growth information have to be provided to the user continuously by monitoring and recording these garden parameters. All the sensors used in this project are interfaced with the NodeMCU. And this information about the plant can be directly monitored and controlled by the farmer through their smart phone using IoT.

The software’s used are Arduino IDE & Blynk IoT platform. Ardunio IDE is used for compiling and uploading the program to NodeMCU and Blynk IoT platform is used for monitoring the temperature, humidity, soil moisture, Water pump, and motion using sensors and update them into the blynk mobile Application through IOT and also displays the same values on LCD.

Here we are using DC motor instead of water pump. Here relay works as a switch to ON/OFF the water pump. By using blynk mobile application user will control the water pump and enable the motion sensor to detect the animals. NODEMCU will gives the feedback to the user about water pump status and motion detection on the blynk APP.

The major features of this project are:

• Wireless monitoring and controlling using IOT technology.
• Blynk up will tell us the feedback of plant monitoring system about sensors data and water pump on/off status and motion detection status.
• User can enable the motion sensor from blynk app when he required.
• User can turn ON/OFF the water pump through Button and Blynk APP.
• Continuous monitoring of temperature and humidity using DHT11 sensor.
• PIR based motion detection.
• Continuous monitoring of moisture using Soil moisture sensor.
• Live monitoring using LCD display.

The major building blocks of this project are:

• Power Supply.
• NodeMCU.
• Dht11(temperature, Humidity Sensor)
• Soil moisture sensor.
• PIR sensor.
• Button.
• Water Pump along with Relay.
• LCD display.

Software’s used:

1. Arduino IDE Compiler to write the program.
2. Embedded C language.
3. Blynk APP.
4. Express SCH for Circuit design.

video:

The robot is wirelessly controlled through a web browser interface, enabling live video streaming and remote navigation from any connected device. The night vision camera allows continuous monitoring in low-light or dark environments, making the system suitable for military, border security, and high-risk surveillance applications.

Image processing techniques are implemented on the Raspberry Pi to enhance autonomous intelligence. When the system detects metal objects using sensor, it automatically captures an image and sends an alert email along with the GPS-based location coordinates and also activate the buzzer for alerts. Similarly, face recognition algorithms are employed to identify unknown individuals. Upon detecting an unrecognized face, the robot captures the image and transmits an alert email containing both the image and real-time location data.

The integration of GPS ensures accurate location tracking, while web-based live streaming provides real-time situational awareness. This intelligent robotic surveillance system enhances security operations by combining remote control, night vision monitoring, object detection, face recognition, and automated alert mechanisms into a compact and cost-effective platform.

The main objectives of the project:

  To design and build a spy robot using the Raspberry Pi 3 Model B+.

  To provide live video streaming using a night vision camera for monitoring in dark areas.

  To control the robot wirelessly through a web browser.

  To track the robot’s real-time location using a GPS module.

  To detect metal objects using sensor techniques.

  To recognize unknown faces using face recognition technology.

  To automatically capture images and send alert emails with location details when a threat or metal is detected.

  To store captured data on an SD card.

  To ensure proper power supply using a rechargeable battery and voltage regulator.

  To develop a smart and cost-effective robotic system for security and surveillance applications.

The major building blocks of this project are:

1. Battery Power Supply.
2. Raspberry pi3 B+ processor.
3. SD card.
4. Night Vision Pi camera.
5. GPS.
6. LCD display.
7. L298 motor driver with DC motors.
8. LM2596 Buck converter.
9. Metal detector sensor.
10. Buzzer.

Software’s used in the project:

1. Raspbian OS.
2. WEB technology.
3. Express SCH for Circuit design.
4. Face recognition.

video: