The controlling device of the whole system is a raspberry pi zero W processor. LCD display, Pi-camera, servo Motor, Bluetooth module, PIR, Buzzer, keypad, GSM and relay along with bulb and transistor with fan is interfaced to the raspberry pi processor. After the system detects the motion using PIR, when the person does not enter the PIN within a certain time, Raspberry pi will send an alert SMS through GSM and also sending alert MAIL along with photo to the predefine stored email. When the person enters the PIN with in the time, it will send the OTP to the user. So, user need to send the OTP through keypad with in the time. When the raspberry pi detects a wrong OTP or PIN, Raspberry pi will capture the person image and mails it. If the entered OTP matches the generated OTP, then the system accesses the door and lets the person in. This device consists of Bluetooth technology for controlling the devices through voice from android mobile application. Based on the received commands, raspberry pi will turn ON/OFF the devices accordingly. The main controlling device of the project is Raspberry Pi. We program it using Python Language and the OS used here is Linux.

The major features of this project are:

• Buzzer, mail and SMS alert for unknown persons.
• PIR sensor-based motion detection.
• Using Pi camera to capture the image.
• GSM based SMS and OTP sending system.
• Servo motor-based door lock/unlock.
• Using raspberry pi ZERO W to achieve this task.
• Voice Based Home automation using Bluetooth technology.
• To achieve this task using RASPBERRY pi zero W processor.

The major building blocks of this project are:

• Power Supply.
• Raspberry pi ZERO W.
• SD card.
• Pi camera.
• Buzzer.
• LCD display.
• Servo motor.
• GSM.
• HC-05 Bluetooth module.
• Keypad.
• PIR sensor.
• Relay with bulb.
• Transistor with fan.

Software’s used:

• Python programming.
• Raspbian OS.
• Express SCH for Circuit design.

video:

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Objectives of the project:

• Design a multiple application surveillance boat.
• Controlling boat, buzzer and laser light form web browser.
• Using web technology.
• It can shoot the enemies through laser.

The major building blocks of the project are:

• Battery power supply.
• RASPBERRY PI ZERO W.
• Pi camera module.
• DC motors with L293d.
• Buzzer.
• Laser light.
• Robot chassis.

Software’s used:

• Raspbian OS.
• python programming language.
• Express SCH for Circuit design.
• WEB technology.

Block diagram:

video:

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This project demonstrates the design and implementation of a various sensors for greenhouse environment monitoring and controlling. This greenhouse control system is powered BY RASPBERRY PI ZERO W it consists of DHT11; it can detect both Humidity& temperature sensor, soil moisture sensor; it can detect moisture content in soil, Rain sensor to detects the rain sensor, LCD display module, DC fan and water pump. Based on the moisture content in soil, Raspberry Pi will turn ON/OFF the water motor through relay. Here relay works as a switch to ON/OFF the water motor. If the system detects high humidity, it will turn ON the DC motor to control the humidity. Raspberry Pi will continuously read the data from sensors and will be display on LCD as well as it will upload the same data into the thingspeak cloud over IOT. By this way it will become easy to monitor and control the system. To achieve this task raspberry pi loaded program written in python language

• Design a Raspberry pi based greenhouse monitoring system.
• DHT11 sensor-based temperature and humidity detection.
• Soil moisture based automatic water pump.
• Humidity -based DC motor control system.
• Monitoring sensor data on LCD display.
• Wireless monitoring of sensor data into the thingspeak cloud.

The major building blocks of this project are:

• Adapter power supply.
• Raspberry pi zero W.
• DHT11(Humidity & Temperature) Sensor.
• SOIL Moisture.
• Rain sensor.
• Relay With water motor.
• LCD display.
• DC motor.
• SD card.

Software’s used:

• Python programming.
• Raspbian OS.
• Express SCH for Circuit design.

video:

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These sensors provide real-time data that is logged and analyzed in the Thing Speak cloud platform. All sensor data is logged and analyzed in the Thing Speak cloud platform, offering real-time insights for informed decision-making and enhancing overall agricultural productivity and sustainability.

The main objective of this project is:

1. Developing a smart agriculture IoT network for efficient monitoring and management of agricultural conditions.
2. Integrate sensors such as the DHT22 sensor, soil moisture sensor, and fire sensor to collect real-time data on environmental conditions and potential hazards.
3. Implement automated irrigation using an AC motor controlled by a relay based on soil moisture levels.
4. Provide alert notifications through a buzzer for critical events such as fire detection or extreme environmental conditions.
5. Focusing on low power solutions to ensure energy efficiency and sustainability in agricultural operations.

The major building blocks of this project are:

• Regulated power supply
• Raspberry Pi zero w
• Fire sensor
• Buzzer
• Ac motor
• Soil Moisture Sensor
• Thing speak cloud
• DHT22
• LCD display

Software’s used:

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

video:

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• Enable real-time video surveillance of human activity in remote or hazardous environments using the Pi Camera and web interface.
• Allow remote control of the robot’s movements and actions via the web interface, enhancing its utility in military reconnaissance and surveillance operations.
• Implementing autonomous behavior for the robot to enhance its capability to operate in complex environments without human intervention.
• Developing a user-friendly web interface for controlling the robot and accessing surveillance footage, making it accessible to operators with minimal technical expertise.

The major building blocks of this project are:

• Regulated power supply.
• Raspberry Pi zero w.
• Pi camera.
• Sd card.
• 12v battery.
• LM256.
• L293D Motor driver.
• Dc motors.

Software’s used:

1. Python programming language.
2. Raspbian os.
3. Express SCH for Circuit design.

video:

The main objective of this project is:

• The primary objective of the “Fire Detection Using Raspberry Pi” project is to enhance fire safety by developing a cost-effective and efficient system capable of detecting fire incidents in real-time and alerting relevant stakeholders promptly via SMS.

The major building blocks of this project are:

• Regulated power supply.
• Raspberry Pi zero w.
• Pi camera.
• Sd card.
• Buzzer.
• GSM.

Software’s Used:

1. Python language.
2. Linux Operating System.

Block diagram:

video:

The Raspberry Pi acts as the central processing unit, interfacing with these components to provide a robust and intelligent security solution. The system operates in two primary modes: lock/unlock mode based on authenticated access through the keypad and alert mode triggered by unauthorized access attempts detected by the Pi camera and motion sensors.

Key functionalities include real-time monitoring of the door via the Pi camera and the ability to remotely control access to the door through secure authentication mechanisms. The integration of these components ensures a reliable and efficient security system suitable for both residential and commercial applications.

This project demonstrates the effective use of Raspberry Pi in conjunction with various sensors and communication modules to create a sophisticated yet user-friendly door locking and intruder alert system.

The major features of this project are:

• Buzzer, mail and alert for unknown persons.
• Using Pi camera to capture the image.
• Servo motor-based door lock/unlock.
• Using raspberry pi ZERO W to achieve this task.
• To achieve this task using RASPBERRY pi zero W processor.

The major building blocks of this project are:

• Power Supply.
• Raspberry pi ZERO W.
• SD card.
• Pi camera.
• Buzzer.
• LCD display.
• Servo motor.
• Keypad.

Software’s used:

• Python programming.
• Raspbian OS.
• Express SCH for Circuit design.

To control the wheel chair by hand movement using joystick. Joystick is a simple device with four direction movement. Wheel chair movement can be controlled in Forward, Reverse, Left, Right and stop direction using JOYSTICK by using wireless RF technology. To control the wheel chair by hand movement using joystick. Joystick is a simple device with four direction movement.

Wheel chair consist of MEMS sensor to detect the fault. IR receiver at wheel chair and IR transmitter at person is used for human following. Lidar is used for autonomous navigation and obstacle avoidance. Raspberry pi zero W has inbuilt wi-fi, if the user selects the location from WEB page, it goes to that location avoiding obstacles. GPS is used for location tracking. SOC is used for emergency intimation. If the user presses the SOC button, wheel chair stops automatically and emergency call goes to the predefine mobile number through GSM and simultaneously the buzzer beeps automatically. As per user request raspberry pi can control the wheel chair using DC motors by using Battery power. In this project we are using PIC microcontroller to read the joystick data and sending this data to the raspberry pi using RF technology. To achieve this task Raspberry pi loaded program written in python language.

Features:

• Design a hand gesture control prototype wheel chair.
• Autonomous navigation and obstacle avoidance using LIDAR.
• Wireless controlling of wheel chair using JOYSTICK technology.
• Automatic fall detection using MEMS technology.
• Automatic intimation using GSM technology.
• GPS based location tracking system.
• IR based human following wheel chair.
• Audible alerts using BUZZER.
• Wheel chair stops Automatically if the person presses the SOC switch.
• To achieve this task Raspberry pi and PIC Microcontroller.

The major building blocks of this project are:

1. Battery power supply.
2. Raspberry pi zero W.
3. SD card.
4. IR sensor.
5. Lidar.
6. GPS.
7. GSM.
8. Buzzer.
9. PIC Microcontroller.
10. DC motors with driver.
11. Joystick.
12. MEMS.
13. RF transmitter and receiver.
14. SOC switch.

Software’s used:

1. PIC C compiler for dumping code into PIC Microcontroller.
2. Raspbian OS.
3. Python language.
4. Express SCH for Circuit design.

Block diagram of the project:

video:

To control the wheel chair by hand movement using MEMS. MEMS is a Micro Electro Mechanical Sensor which is a highly sensitive sensor and capable of detecting the tilt. This sensor finds the tilt in X and Y directions and these measured values are sent to the microcontroller. Microcontroller converts these raw values into a human readable value. Wheel chair movement can be controlled in Forward, Reverse, Left, Right and stop direction using MEMS by using wireless RF technology.

Wheel chair consist of MEMS sensor to detect the fault. IR receiver at wheel chair and IR transmitter at person is used for human following. Lidar is used for autonomous navigation and obstacle avoidance. Raspberry pi zero W has inbuilt wi-fi, if the user selects the location from WEB page, it goes to that location avoiding obstacles. GPS is used for location tracking. SOC is used for emergency intimation. If the user presses the SOC button, wheel chair stops automatically and emergency call goes to the predefine mobile number through GSM and simultaneously the buzzer beeps automatically. As per user request raspberry pi can control the wheel chair using DC motors by using Battery power. In this project we are using PIC microcontroller to read the joystick data and sending this data to the raspberry pi using RF technology. To achieve this task Raspberry pi loaded program written in python language.

Features:

• Design a hand gesture control prototype wheel chair.
• Autonomous navigation and obstacle avoidance using LIDAR.
• Wireless controlling of wheel chair using MEMS technology.
• Automatic fall detection using MEMS technology.
• Automatic intimation using GSM technology.
• GPS based location tracking system.
• IR based human following wheel chair.
• Audible alerts using BUZZER.
• Wheel chair stops Automatically if the person presses the SOC switch.
• To achieve this task Raspberry pi and ARDUINO NANO Microcontroller.

The major building blocks of this project are:

1. Battery power supply.
2. Raspberry pi zero W.
3. SD card.
4. IR sensor.
5. Lidar.
6. GSM.
7. GPS.
8. Buzzer.
9. Arduino nano Microcontroller.
10. DC motors with driver.
11. MEMS for fall detection.
12. MEMS for hand gesture.
13. RF transmitter and receiver.
14. SOC switch.

Software’s used:

1. Arduino IDE for dumping code into ARDUINO Nano Microcontroller.
2. Raspbian OS.
3. Python language.
4. Express SCH for Circuit design.

Block diagram of the project:

video:

Heartbeat sensor is uses to detect the heartrate of the person, DS18B20 temperature sensor is uses to detect the body temperature. AD8232 ECG is uses to measure the electrical signals of the heartbeat. This system consists of GSM module for sending the alert message if the sensor data crosses the set limit. This system consists of panic button to send the alert SMS in panic situations.

The main controlling device of the project is Raspberry Pi Zero W processor. DS18B20 Temperature sensors, GSM, LCD display, ECG and panic button is interfaced to the raspberry pi processor. Raspberry will continuously monitor the health condition through sensors will be displays on LCD. If the sensor data crosses the set limit raspberry pi will sending the alert SMS to the predefine mobile number though GSM. If the person presses the panic button it can send the alert SMS to the predefine mobile number through GSM. There are no ADC pins in raspberry pi so, we are using Arduino nano as an ADC converter. To achieve this task raspberry pi loaded program written in python language.

The main objectives of the project are:

1. The health status is known wirelessly using IOT technology.
2. Indicating health status using different sensors like temperature, heartbeat, ECG.
3. GSM based alerting system.
4. AD8232 based ECG monitoring system.
5. Visual alerts using LCD.
6. Remote monitoring of sensor data using blynk APP.

The project provides exposure to following technologies:

1. Interfacing GSM to the raspberry pi.
2. Interfacing LCD to the raspberry pi.
3. Interfacing of different sensors to the raspberry pi.

The major building blocks of the project are:

1. Power Supply.
2. Raspberry pi zero w.
3. Arduino Nano.
4. DS18B20 Temperature sensor.
5. ECG sensor.
6. GSM module.
7. Heartbeat sensor.
8. LCD display.
9. Panic button.

Software’s used:

1. Python programming.
2. Express SCH for Circuit design.
3. Raspbian OS.

Block diagram:

video: