Automation is the most frequently spelled term in the field of electronics. The hunger for automation brought many revolutions in the existing technologies. This project makes use of an onboard computer, which is commonly termed as Raspberry Pi processor. It acts as heart of the project. This onboard computer can efficiently communicate with the output and input modules which are being used. The Raspberry Pi is a credit-card-sized single-board computer developed in the UK by the Raspberry Pi Foundation. The Raspberry Pi has a Broadcom BCM2835 system on a chip (SoC), which includes an ARM1176JZF-S 700 MHz processor, Video Core IV GPU, and was originally shipped with 256 megabytes of RAM, later upgraded to 512 MB. It does not include a built-in hard disk or solid-state drive, but uses an SD card for booting and long-term storage. In order to further maintain peace and provide security to people now a day, Closed-circuit television (CCTV) surveillance system is being utilized. This study focused on the design and implementation of a low-cost smart security camera using Raspberry Pi (RPI) and OpenCV. The system was designed to be used inside a warehouse facility. It has human detection, fire detection and gas detection capability that can provide precaution to potential crimes and potential fire. The credit card size Raspberry Pi (RPI) with Open-Source Computer Vision (OpenCV) software handles the image processing for the alarms and sends captured pictures to user’s email via Wi-Fi. The device which is able to perform the task is a Raspberry Pi processor. Whenever pi camera detects any motion then camera capture that image and sending to the respective mail via Wi-Fi. When the GAS sensor detects the gas, then the system gives buzzer alerts. When the flame sensor detects the flame, then raspberry pi switch ON the water sprinkler through DC water motor. To perform this task, Raspberry Pi processor is programmed using embedded ‘Linux’.

 

The objectives of the project are:

1. Capturing of Person images using pi camera.
2. Captured image is sent through email.
3. It sprinkler the water when fire is detected.
4. It activates the buzzer when the gas is detected.
5. Motion detection using image processing.

The project provides learning’s on the following advancements:

1. Learn about Image processing and IOT Technology.
2. Raspberry pi working and programming.
3. Learn about Relay.
4. Learn about Gas and fire sensor.

The major building blocks of this project are:

• Power supply.
• Raspberry pi3.
• SD card.
• Pi camera.
• GAS Sensor.
• Fire sensor.
• Buzzer.
• Relay with DC water motor.

Software’s used:

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

   

   

Block Diagram:      

 

Video: