Early Fire Detection Using Image Processing
Fire outbreak is a common issue in Malays and causes tremendous damages toward nature and human interest. To reduce loss of life and property from fire, an early warning is an imperative. Fire detection is the primary goal of this project other than surveillance. The objective of the project is earl
2025-06-28 16:32:17 - Adil Khan
Early Fire Detection Using Image Processing
Project Area of Specialization Artificial IntelligenceProject SummaryFire outbreak is a common issue in Malays and causes tremendous damages toward nature and human interest. To reduce loss of life and property from fire, an early warning is an imperative. Fire detection is the primary goal of this project other than surveillance. The objective of the project is early detection of fire separated from preventive measures to reduce the losses because of risky fire. The proposed system is mainly based on image processing and arduino serial communication. In this project, at the client end, the fire pictures will be feeded as video frames. The proposed framework utilizes RGB, YCbCr and HSV color space. The benefit of utilizing YCbCr color space is that it can isolate the luminance from the chrominance more successfully than RGB color space. Along with this smoke, motion, area detection is additionally performed utilizing its color attributes. . Fire growth is analyzed and calculated based on frame differences. Flame plays a more and more important role in the fire recognition. The proposed framework comprise of equipment, for example, arduino, GSM to send message in case of fire detection. There is a camera for the observation. This camera will give an ongoing video yield to the client on the PC or PC by means of a little GUI. Thus the fire will be detected utilizing this model. This project can likewise be served for security and observation applications.
Project ObjectivesThe objective of the project is early detection of fire separated from preventive measures to reduce the losses because of risky fire. The proposed system is mainly based on image processing and arduino serial communication. In this project, at the client end, the fire pictures will be feeded as video frames. The proposed framework utilizes RGB, YCbCr and HSV color space. The benefit of utilizing YCbCr color space is that it can isolate the luminance from the chrominance more successfully than RGB color space. Along with this smoke, motion, area detection is additionally performed utilizing its color attributes. . Fire growth is analyzed and calculated based on frame differences. Flame plays a more and more important role in the fire recognition. The proposed framework comprise of equipment, for example, arduino, GSM to send message in case of fire detection. There is a camera for the observation. This camera will give an ongoing video yield to the client on the PC or PC by means of a little GUI. Thus the fire will be detected utilizing this model. This project can likewise be served for security and observation applications.
Project Implementation MethodAs visual color pictures of fire have high values in the red component of the RGB coordinates. This property permits simple threshold-based criteria on the red component of the color images to segment fire images in natural scenarios. However, not just fire gives high values in the red component. Another characteristic of fire is the proportion between the red part and the blue and green segments. An image is stacked into color detection system. Color detection system applies the particular property of RGB pixels and gives the output result as a picture with a selected area of color detection. For that, color space RGB and YCbCr is picked. For grouping of a pixel to be fire we have defined seven rules. If a pixel fulfills these seven rules, we state that pixel have a place to fire class. Color alone isn't sufficient to distinguish fire. There are numerous things that share the same tone as things that are not fire, for example, a desert, sun, red leaves and different items. The key to recognize the fire and the fire shaded items is the nature of their motion. Motion detection is used to detect any occurrence of movement in a video. It is done by investigating distinction in pictures of video frames. There are three principle parts in moving pixel detection: frame/background subtraction, background registration, and moving pixel detection Similar to the fire detection. We are likewise demonstrating smoke pixels. The smoke pixels do not show chrominance attributes like fire pixels. Toward the start, when the temperature of the smoke is low, it is normal that the smoke will show color from the range of white- bluish to white. Close to the beginning of the fire, the smoke's temperature increments and it gets shading from the scope of dark grayish to black. Utilizing this thought, HSV color spaces is used. The output is noisy, thus the motion property of the smoke can be utilized to eliminate such noisy parts. The proposed system will activate alarm and send a message to the management in case whether fire or smoke or both are detected.
Benefits of the Project- The technique has many advantages such as early fire detection, high accuracy, flexible system installation, and the capability to effectively detect fires in large spaces and complex building structures. It processes image data from a camera by algorithms to determine the presence of a fire or fire risk in images. Therefore, the detection algorithm is the core of this technology, directly determining the performance of the image fire detector.
- Cost of using this type of detection is cheaper.
- This type of system is greatly simpler.
- The response time of fire detection system is faster.
- A single camera can monitor large area.
- The fire source can be saved in the form of images or video.
- Fire confirmation without visiting the location.
The final system will be able to detect fire within two seconds and try to extinguish the fire. As we are detecting fire by using image processing the system will continuously monitor frames after two seconds and inform the management through text and activate alarm in case of fire detection. The proposed system will cover a large area as compared to sensors and can be used in an open environment. The ultimate system will be more efficient, faster and less costly.
Final Deliverable of the Project Hardware SystemCore Industry ITOther Industries Others Core Technology Artificial Intelligence(AI)Other Technologies OthersSustainable Development Goals Affordable and Clean Energy, Industry, Innovation and InfrastructureRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 60995 | |||
| Arduino Uno R3(Just for communication) | Equipment | 2 | 3500 | 7000 |
| LCD 16*2 | Equipment | 2 | 1800 | 3600 |
| 12c Module for LCD | Equipment | 2 | 1800 | 3600 |
| Camera | Equipment | 3 | 5000 | 15000 |
| Power supply for Arduino | Equipment | 2 | 2000 | 4000 |
| Step down power supply | Equipment | 2 | 1200 | 2400 |
| Bridge rectifier | Equipment | 1 | 500 | 500 |
| Capacitors | Equipment | 6 | 200 | 1200 |
| Diodes | Equipment | 12 | 260 | 3120 |
| Relays | Equipment | 4 | 500 | 2000 |
| Buzzer | Equipment | 1 | 1000 | 1000 |
| Resistors | Equipment | 15 | 200 | 3000 |
| Bc547 transistor | Equipment | 2 | 300 | 600 |
| GSM Module | Equipment | 1 | 1500 | 1500 |
| Water sprinklers | Equipment | 5 | 720 | 3600 |
| Arduino connecting cable for laptop | Equipment | 2 | 400 | 800 |
| Vero board | Equipment | 5 | 530 | 2650 |
| Lm7805 voltage regulator | Equipment | 2 | 600 | 1200 |
| Connecting wires | Equipment | 10 | 105 | 1050 |
| Silicon glue | Miscellaneous | 6 | 250 | 1500 |
| soldering Iron | Miscellaneous | 1 | 820 | 820 |
| Soldering paste | Miscellaneous | 1 | 700 | 700 |
| Glue gun | Miscellaneous | 1 | 155 | 155 |