This innovative system utilizes a Raspberry Pi-based central hub, which connects to an array of sensors distributed across the aircraft. These sensors continuously gather real-time data on pressure, temperature, gas levels, and humidity. The collected data is securely encrypted using the AES algorithm before being transmitted to a cloud-based platform. The cloud platform not only stores the encrypted data but also provides real-time analysis and alerts for irregularities in flight parameters.

By implementing AES encryption, the system safeguards the confidentiality and integrity of flight data, preventing unauthorized access and tampering. This encryption ensures that only authorized personnel can access and decipher the critical flight parameter information stored in the cloud.

The “Flight Parameter Monitoring and Alerting System by IoT” enhances aviation safety by not only providing real-time insights but also by prioritizing the security of sensitive flight data. This system represents a significant step forward in aviation technology, ensuring both the safety and confidentiality of flight parameter monitoring, which is essential in the modern era of aviation.

Features:

1. Real-time Parameter Monitoring: Continuously monitors critical flight parameters including pressure, temperature, gas levels, and humidity, providing real-time data insights.

2. Advanced AES Encryption: Utilizes the robust Advanced Encryption Standard (AES) algorithm to protect flight data, ensuring secure transmission and storage in the cloud.

3. Cloud-based Analysis and Alerts: Employs a cloud-based platform for data storage and analysis, generating instant alerts for any irregularities in flight parameters.

4. Enhanced Aviation Safety: Integrates IoT technology to enhance aviation safety and confidentiality, offering a comprehensive solution for monitoring and securing vital flight parameter data.

The major building blocks of this project are:

• R P S
• Raspberry Pi3 Processor.
• SD Card.
• Pressure sensor Bmp180
• LED indicators.
• DHT11
• Gas sensor
• LCD
• Buzzer
• Wi-Fi.

Software’s used:

1. Python Language.
2. Raspbian OS.

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Features:

• Real-time GPS location tracking.
• Emergency push-button activation.
• Automatic latitude and longitude detection.
• SMS alert through GSM module.
• Sends location to a predefined mobile number.
• LED indication during emergency.
• Arduino Nano-based control system.
• Simple and compact hardware design.
• Fast emergency location communication.
• Useful for personal safety and emergency situations.

The major building blocks of this project are:

• Battery Power supply.
• Arduino nano.
• GSM modem.
• GPS Receiver.
• Buttons.
• LED indicator.

Software’s used:

• ARDUINO IDE.
• Embedded C language.

Block Diagram:

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Since there is no vaccine yet available in the market, the only way to be safe is by taking precautions. It is suggested to sanitize surroundings that help in slowing down the spread of infection as the virus mainly gets transmitted with the aerosols which come out of an infected person’s nose or mouth while coughing or sneezing. To solve these problems, we have designed a microcontroller-based sanitization robot along with UV lamp.

The project mainly designs a robot that can be operated using Android mobile phone. The controlling of the Robot is done wirelessly through Android smart phone using the Bluetooth feature present in it. This system also uses, sanitizer, UV lamp along with relay driver and two DC motor along with l293d motor driver with Robot chassis to build this Robotic car setup. The system also controls the sanitizer and UV lamp using android mobile. Here relay likes as a switch to on and off the sanitizer and UV lamp.

The controlling device of the whole system is a Microcontroller. Bluetooth module, DC motors are interfaced to the Microcontroller. The data received by the Bluetooth module from Android smart phone is fed as input to the controller. The controller acts accordingly on the DC motors of the Robot. In achieving the task, the controller is loaded with a program written using Embedded ‘C’ language.

The objectives of the project include:

1. To design and develop a wireless sanitizing robot controlled through a mobile phone.
2. To use an Android smartphone with a touch screen for robot control.
3. To establish Bluetooth wireless communication between the mobile phone and robot.
4. To develop a robot that can sanitize surrounding areas.
5. To use a UV lamp for reducing microorganisms and viruses on exposed surfaces.

The major building blocks of this project are:

• Battery Power Supply.
• Microcontroller.
• Android smart phone.
• Bluetooth module.
• Crystal oscillator.
• Reset.
• LED indicators.
• UV lamp.
• Sanitizer.
• DC Motors with L293D driver.
• Relays.

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:

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In accordance with the program of Indonesian Army Force (TNI) commander who will always perform modernization and rejuvenation of the main tools of Indonesian defense system, both of Army, Navy and Air Force. From the few examples of defense equipment bought by Indonesia from abroad, such as tanks, warships, military aircraft and so forth, researchers and students are encouraged to make research on technology major appliance defense system especially its gun turret used on military vehicles, the military vehicle itself composed of military ground vehicles, military vehicles sea and air military vehicle that has its own characteristics so the gun turret itself has flexibility because it can be placed on all military vehicles on land, sea or air .It is used for defense and security interests that can be placed in tanks, armored vehicles, warships, and military aircraft. It has camera to track the target.

The Target Detection and Tracking with Gun Triggering System is an automated vision-based system designed to detect, track, and continuously point toward a moving target. The system uses a Raspberry Pi with a Pi Camera to capture and process the target position, while an Arduino UNO receives information from the ultrasonic and gyro sensors for distance measurement and stabilization. Two servo motors are used for platform stabilization, and another servo motor is used to control the trigger-point mechanism. Based on the detected target position, the Raspberry Pi controls a stepper motor through a ULN2803 driver to provide controlled angular movement, while a laser light indicates the tracked target position. The Arduino and Raspberry Pi work together to maintain stable and accurate target tracking. The prototype can be used as a platform for studying computer vision, object tracking, stabilization, and automated pointing mechanisms in controlled environments.

Objectives:

1. To design and develop a vision-based target detection and tracking system using Raspberry Pi and Pi Camera.
2. To detect and continuously track the position of a moving target using image processing techniques.
3. To use ultrasonic and gyro sensors for distance measurement and platform stabilization.
4. To control servo and stepper motors for accurate angular movement and pointing toward the detected target.
5. To develop a trigger-point indication mechanism using a servo motor and laser light for controlled target-pointing demonstrations.

The major building blocks of this project are:

• Raspberry pi.
• Servo motors.
• Stepper motor.
• Gyro sensor.
• Ultrasonic sensor.
• Laser light.
• Pi camera.
• Power supply.

Software’s used:

• Python language.
• Linux OS.

Block Diagram:

video:

In accordance with the program of Indonesian Army Force (TNI) commander who will always perform modernization and rejuvenation of the main tools of Indonesian defense system, both of Army, Navy and Air Force. From the few examples of defense equipment bought by Indonesia from abroad, such as tanks, warships, military aircraft and so forth, researchers and students are encouraged to make research on technology major appliance defense system especially its gun turret used on military vehicles, the military vehicle itself composed of military ground vehicles, military vehicles sea and air military vehicle that has its own characteristics so the gun turret itself has flexibility because it can be placed on all military vehicles on land, sea or air .It is used for defense and security interests that can be placed in tanks, armored vehicles, warships, and military aircraft.

The project aims in designing a gun turret that is able to find the direction of the target and also based on the target direction the gun turret will move using Arduino and GY511digital compass. The ARDUINO Microcontrollers used in the project are programmed using Embedded C language.

The major building blocks of this project are:

• Arduino Micro Controller.
• Servo motors
• Laptop
• GY511 sensor.

Software’s used:

1. Embedded C language.
2. Arduino IDE studio compiler.
3. Express SCH for Circuit design.

Block Diagram:

video:

The Microcontroller is loaded with a program written in embedded ‘C’ language to perform the task. To perform this task microcontroller is loaded with an intelligent program written using embedded ‘C’ language.

The features of the project are:

1. IR sensor-based vehicle detection.
2. IOT based vacant slot monitoring system.
3. RFID based vehicle accessing and billing system.
4. Using Blynk mobile application to know the vacant slots.

The major building blocks of this project are:

1. Regulated Power Supply
2. PIC Micro Controller.
3. IR sensors.
4. RFID reader and TAGS.
5. ESP8266 Wi-Fi module.
6. Crystal oscillator.
7. Reset.
8. 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.

Block Diagram:

video:

Objectives:

The main objectives of the Smart Shopping Cart System are:

1. To design and develop an intelligent shopping cart using Raspberry Pi and Pi Camera.
2. To reduce customer waiting time and long queues at supermarket billing counters.
3. To automatically identify products using image processing technology.
4. To provide options for adding and removing products from the shopping cart.
5. To display product details such as product name, weight, and price on the LCD.
6. To automatically calculate and update the total bill amount in real time.
7. To provide audio indication using a buzzer during product addition or removal.
8. To minimize manual billing operations and human effort.
9. To provide a fast, accurate, and user-friendly shopping experience.
10. To develop a low-cost automated billing system suitable for supermarkets and shopping centers.

The major building blocks of the project are:

1. Power supply.
2. Raspberry Pi processor.
3. Pi Camera
4. LED Indicator.
5. LCD display with driver
6. Buzzer
7. Selection switch.

Software’s used:

1. Embedded Linux programming.
2. Express SCH for Circuit design.

Block Diagram:

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This technology, when combined with IoT, is able to provide intimation to the user about food products. It’s just like a food inspection technology. More precisely, our system consists of gas, temperature and humidity sensors, which provide the essential information needed for evaluating the quality of the packed product. This information is transmitted wirelessly through Wi-Fi to a computer system providing an interface where the user can observe the evolution of the product quality over time. To perform this intelligent task, using arduino is loaded with a program written in embedded ‘C’ language.

The main objectives of the project are:

1. By using this project, we can identify the quality of the packed product.
2. Sending intimation to the user using IOT.

The main building blocks of the project are:

• Power Supply.
• Arduino UNO.
• Methane gas sensor.
• DHT11
• ESP8266WI-FI module.

Software’s used:

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

Block diagram of the project:

video:

When a person approaches the entrance, the MLX90614 measures the body temperature. At the same time, the Pi Camera captures the person’s face, and OpenCV-based image processing is used to detect whether a mask is properly worn. If the temperature is within the safe limit and the person is wearing a mask, the Raspberry Pi activates the DC motor to open the door. If the temperature is high or a mask is not detected, the door remains locked and a buzzer provides an alert. An LCD displays the system status, while LEDs indicate the operating condition. The proposed system provides a simple, contactless, and automated safety solution for indoor entrances.

Objectives:

• To develop a Raspberry Pi 3 based automatic safety screening system.
• To measure body temperature using the MLX90614 contactless temperature sensor.
• To detect face masks using Pi Camera and OpenCV.
• To automatically control the entrance door using a DC motor.
• To prevent entry when high temperature or no-mask condition is detected.
• To provide an audio alert using a buzzer during unsafe conditions.
• To display temperature and system status on an LCD.
• To indicate system operation using LEDs.
• To provide a contactless and automatic safety system for indoor areas.

The main building blocks of the project are:

• Power Supply.
• Raspberry pi3.
• Pi camera module.
• Buzzer.
• MLX90614.
• LCD display.
• DC motor with L293D driver.
• SD card.
• LED indicators.

Software’s used:

• Python language.
• Linux OS.
• Express SCH for Circuit design.

Block diagram of the project:

video:

The major features of this project are:

  Autonomous lane following using Pi Camera.

  Lane detection and tracking using OpenCV.

  Obstacle detection using an ultrasonic sensor.

  Automatic emergency braking when an obstacle is detected.

  Raspberry Pi 3 as the main controller.

  Python-based control and image processing.

  Real-time camera-based monitoring.

  Automatic motor control according to lane position.

  Collision avoidance for improved safety.

  Suitable for autonomous vehicle and robotic applications.

The major building blocks of this project:

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

Software’s used in the project:

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

Block Diagram:

video: