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:

The project aims in designing an IOT based food delivery robot which is operated wirelessly through smart phone using IOT technology.

This is the internet of things (IOT) based project, where we are particularly uses the Esp32 camera, head light and two DC motor along with l293d motor driver.

The ESP32 cam will capture live data with regards to its surroundings and then send it to a particular IP address through internet. User can access this device using mobile phone and while seeing the video user will control the robotic vehicle along with headlight and door lock from webpage.

This robot consist of ultrasonic sensor which uses to detect the obstacles in its path and switches ON the blue lights for alerts. This robot consist of one more feature is uses to detect the theft and alerts through buzzer.

After reaches the destination robot will ask the password .Use need to enter the correct password though keypad .If it is correct the door will open to collect the food after some time the door will close automatically. The status of the project will display on LCD.

The main controlling device of the project is PIC microcontroller which loaded program written in embedded C language.

The objectives of the project include:

• IOT based food delivery robot.
• Controlling robot, head light and door lock from web browser
• ESP32 camera based surveillance system.
• Keypad based password entering system.
• Obstacle detection and switching ON the blue lights.
• Theft detection and Alerting through Buzzer.
• Visible alerts using LCD display.
• To achieve this task using PIC Microcontroller.

The major building blocks of this project are:

• Rechargeable battery.
• ESP32 Camera.
• DC Motor with L293D driver.
• Blue light.
• Head light.
• Ultrasonic sensor.
• DC motor with l298 driver.
• Buzzer.
• Keypad.
• PIC Microcontroller.
• LCD display.

Software’s used:

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

video:

The robot’s mobility is controlled via DC motors driven by an L298 motor driver, with an additional motor managing the door’s opening and closing based on rain sensor input. A speaker provides voice alerts to enhance interaction and safety. The robot is powered by a rechargeable battery regulated by an LM2596 voltage regulator and supported by a charging circuit.

while moving forward, when the robot detects obstacles or rain, it sends SMS alerts with the current GPS location through a GSM module, ensuring real-time updates to the user. The system features a web interface that allows users to start the robot, initiate QR code scanning, view live streams, and monitor order count and serial numbers dynamically as the robot scans items during delivery.

This design highlights the integration of Raspberry Pi with sensors, communication modules, and web interfaces to develop a low-cost, efficient, and socially interactive delivery robot suitable for indoor and controlled environments.

Objectives:

• Integrate Raspberry Pi 3 with sensors such as ultrasonic, IR, rain sensor, and GPS for navigation and environment sensing.
• Implement a Pi Camera for live streaming and QR code scanning to identify delivery items.
• Control DC motors for robot movement and door operation using an L298 motor driver.
• Develop a communication system using GSM to send SMS alerts with location in case of obstacles or rain detection.
• Create a web interface for remote control, live monitoring, QR code scanning activation, and order management.
• Ensure power management with a rechargeable battery and charging circuit.

The major building blocks of this project are:

• Battery.
• Raspberry Pi.
• Pi Camera.
• IR Sensor.
• Ultrasonic Sensor.
• GSM
• GPS
• Speaker.
• Rain Sensor.
• L298 With DC Motors.
• Door
• SD Card.
• Charging Circuit.
• LM2596

Software’s used:

• Raspbian OS.
• TinyML and deep learning techniques

Software’s used:

1. Express SCH for Circuit design.
2. Raspbian OS, Python language.
3. Web technology.

video:

The project aims in designing an IOT based food delivery robot which is operated wirelessly through smart phone using IOT technology.

This is the internet of things (IOT) based project, where we are particularly uses the Esp32 camera, head light and two DC motor along with l293d motor driver.

The ESP32 cam will capture live data with regards to its surroundings and then send it to a particular IP address through internet. User can access this device using mobile phone and while seeing the video user will control the robotic vehicle along with headlight and door lock from webpage.

This robot consists of ultrasonic sensor which uses to detect the obstacles in its path and switches ON the blue lights for alerts. This robot consists of one more feature is used to detect the theft and alerts through buzzer.

After reaches the destination robot will ask the password. Use need to enter the correct password though keypad. If it is correct the door will open to collect the food after some time the door will close automatically. The status of the project will display on LCD.

The main controlling device of the project is PIC microcontroller which loaded program written in embedded C language.

The objectives of the project include:

• IOT based food delivery robot.
• Controlling robot, head light and door lock from web browser
• ESP32 camera-based surveillance system.
• Keypad based password entering system.
• Obstacle detection and switching ON the blue lights.
• Theft detection and Alerting through Buzzer.
• Visible alerts using LCD display.
• To achieve this task using PIC Microcontroller.

The major building blocks of this project are:

• Rechargeable battery.
• ESP32 Camera.
• DC Motor with L293D driver.
• Blue light.
• Head light.
• Ultrasonic sensor.
• DC motor with l298 driver.
• Buzzer.
• Keypad.
• PIC Microcontroller.
• LCD display.

Software’s used:

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

video:

This project proposes a smart BMS for electric vehicles using an Arduino UNO microcontroller to monitor key battery parameters such as voltage, current, and temperature. The system integrates multiple sensors along with safety features like fire detection and accident detection using a MEMS sensor. In case of an accident, the GPS and GSM modules are used to track the vehicle location and send alert messages to predefined contacts.

Additionally, the system enables real-time monitoring by displaying parameters on an LCD and uploading data (voltage, current, temperature, location, and time) to the ThingSpeak cloud via an ESP8266 Wi-Fi module. An ultrasonic sensor is used for obstacle detection, and alerts are provided through a buzzer and display.

Overall, the proposed system ensures safe battery operation, real-time monitoring, and enhanced vehicle safety through IoT and embedded technologies, making it suitable for advanced electric vehicle applications.

The main objectives of this project are:

• To design a smart IoT-based system for automatic vehicle accident detection.
• To develop a rescue alert mechanism that sends location and emergency messages using GPS and GSM.
• To implement a Battery Management System (BMS) for monitoring EV battery parameters like voltage, current, and temperature.
• To ensure safe battery operation by preventing overcharging, overheating, and overcurrent conditions.
• To integrate real-time data monitoring using IoT (ESP8266 with ThingSpeak).
• To design a charger monitoring system for efficient battery charging control.
• To display system parameters and alerts using an LCD and buzzer.
• To detect vehicle accidents using MEMS sensor and trigger immediate response.
• To enhance vehicle safety with additional sensors like fire and obstacle detection.
• To develop a low-cost, reliable, and user-friendly system for smart electric vehicles.

The major building blocks of this project are:

• Li-ION Battery.
• LM2596.
• ARDUINO UNO Microcontroller.
• Temperature sensor.
• Voltage sensor.
• Current sensor.
• Charging Circuit.
• LCD display.
• MEMS sensor.
• Fire sensor.
• Ultrasonic sensor.
• Buzzer.
• GSM.
• GPS.
• ESP8266 WI-FI module.
• DC motor (vehicle).

Software’s used:

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

video:

In day-to-day life road accidents goes on increasing due to varies reasons. Some road accidents may cause due to chasing between two vehicles. We avoid these kinds of accidents by providing some precautionary methods using ultrasonic sensors.  Ultrasonic sensors generate high frequency sound waves and evaluate the echo which is received back by the sensor. These sensors calculate the time intervals between sending the signal and receiving the echo to determine the distance to an object. If the distance of the vehicle is too small then this vehicle is automatically control the speed of the vehicle which avoids the potential risk of the accident.

The main controlling device of the system is a Microcontroller. Ultrasonic sensor, buzzer and DC motors along with l293d motor driver are interfaced to Microcontroller. The microcontroller gives an alarm if distance is less than predefined limit from obstacle. If the sensor detect obstacle this data is fed as input to the micro control and microcontroller stop the vehicle ignition automatically. Here relay works as a switch to on/off the ignition. To perform the intelligent task, Microcontroller is programmed using embedded ‘C’ language.

Features:

1. Automatic braking system.
2. Object identification through ultrasonic sensor
3. Buzzer based alarming system

The project makes us learn about:

1. Ultrasonic sensor characteristics.
2. DC motor working principle and need for a motor driver.
3. Embedded C programming.
4. PCB designing.

The Major Building blocks of this project are:

• Battery Power Supply.
• PIC Microcontroller.
• Ultrasonic sensor.
• DC motor with relay driver.
• LED Indicators.
• Buzzer with driver.
• Crystal Oscillator.
• Reset Button.
• 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.

Regulated Power Supply:

 BLOCK DIAGRAM:

video:

This project makes a use of ultrasonic and IR sensors to detect the human. DC motors along with l293d driver is used to moves the robot. Batteries are uses to provide the power supply of the Arduino and DC motor.

The main controlling device of the project is Arduino UNO. IR sensors, Ultrasonic sensor and DC motors along with L293d motor driver is interfaced to the Arduino UNO. When the sensor detects the human Arduino will moves the robot towards the human. To achieve this task arduino UNO loaded program written in embedded C language.

  The Major building blocks of this project are:

• Arduino UNO.
• DC motor with L293D motor driver.
• TWO IR sensors.
• Ultrasonic sensor.
• Batteries

Software’s used:

1. Arduino IDE Studio for Embedded C programming.
2. Express SCH for Circuit design.

Block Diagram:

video:

The project aims in designing a train accident avoiding system using Arduino. The proposed system is an enhanced technique for monitoring the object which uses Arduino microcontroller, ultrasonic sensor, and radar module. The radar will get the distance from the object and ultrasonic sensor will ensure to avoid the accidents that may occur by the clash between the train and objects.

The controlling device of the whole system is a Microcontroller. Ultrasonic sensor, servo motor long with barrier gates are interfaced to the Microcontroller. When the ultrasonic sensor detects the train, microcontroller will close the barrier gates to let the person in. To achieving the task, the controller is loaded with a program written using Embedded ‘C’ language.

The main objectives of the project are:

1. Automatic train arrival/despatcher detection using ultrasonic sensor.
2. Automatic barrier gates open/close.

The major building blocks of the project are:

1. Regulated Power Supply.
2. PIC Microcontroller.
3. Ultrasonic sensor.
4. Servo motor through barrier gates.
5. Crystal oscillator.
6. Reset.
7. LED indicators.

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.

Regulated Power Supply:

Block diagram:

video:

This system uses Ultrasonic sensor which is used to detect the human presents near by the table and based on that Arduino switches on/off the light, fan through relay. Here relay works as a switch to on/off the devices.

The Arduino Uno is a microcontroller board based on the ATmega328. It has 14 digital input/output pins (of which 6 can be used as PWM outputs), 6 analog inputs, a 16 MHz ceramic resonator, a USB connection, a power jack, an ICSP header, and a reset button. It contains everything needed to support the microcontroller; simply connect it to a computer with a USB cable or power it with an AC-to-DC adapter or battery to get started.

The main controlling device of the project is Arduino UNO microcontroller. Ultrasonic sensor, keypad, relay through light, fan and LCD display is interfaced to the Arduino. Arduino continuously read the data from sensor, keypad .Based on that Arduino take the appropriate action up on the system and process this data to the NodeMCU microcontroller it has inbuilt Wi-Fi to send the notification into the blynk app.

The features of the project are:

• Designed a E-Restaurant and menu ordering system using IOT.
• Using KEYPAD to select the food items.
• Using ultrasonic sensor to detects the person near by the table.
• Automatic device switching based on human presents.
• Using NodeMCU module to send the data into the blynkapp.
• Automatic intimation to the responder about table number, items quantity,customer order.
• Visible alerts using LCD display.
• Using Arduino, NodeMCU modules to achieve this task.

Software’s used:

• Arduino IDE for compiling and dumping code into Microcontrollers.
• Express SCH for Circuit design.

The main blocks of this project are:

• Power Supply.
• Arduino UNO.
• NodeMCU
• Ultrasonic sensor.
• Keypad
• Relay
• LCD display.
• Lights
• Fan
• Blynkapp

Block diagram of the project:

video:

This system to detect the object using machine learning algorithm which is written in embedded Linux platform. All images like table, chair, bottle…..we will prepared dataset and stored into the raspberry pi and trained for preprocessing. This system uses Ultrasonic sensor to detect the nearest obstacle and announce the voice through speaker.

OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. It mainly focuses on image processing; video capture and analysis including features like face detection and object detection.

In this project we are using python language to write the program. Python is an interpreter, object-oriented, high-level programming language with dynamic semantics. Python’s simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse.

The controlling device of the whole unit is a Raspberrypi3 processor to which input and output modules are interfaced. Raspberrypi3 has Broadcom BCM2837B0, Cortex-A53 (ARMv8) 1GB LPDDR2 SDRAM 1.4GHz 64-bit quad-core processor, dual-band wireless LAN, Bluetooth 4.2/BLE, faster Ethernet, and Power-over-Ethernet support (with separate PoE HAT).

The processor is programmed in PYTHON language which intelligently performs the specific task. Here, the processor gets input from the sensor and pi camera attached to the raspberry pi. This input is processed by processor and announce the voice appropriately.

The major features of this project are:

• 1. Automatic obstacle sensing.
  2. Automatic object detection and classification.
  3. Using Raspberrypi3 processor to achieve this task.
  4. Using pi camera and openCV machine learning to detect the objects
  5. Using Ultrasonic sensor to detect the obstacle.
  6. Voice alerts for obstacle detection.
  7. Voice announce for object detection.

The major building blocks of this project:

• Battery power supply.
• Raspberry Pi3 Processor.
• SD Card.
• Ultrasonic sensor.
• Pi camera.
• LED indicators.

Software’s used in the project:

1. Python Programming.
2. OpenCV MACHINE LEARNING Image processing.
3. Embedded Linux operating system.
4. Express SCH for Circuit design.

Block Diagram:

video: