Fire Detector Using Computer Vision and IoT
In this project, the fire will be detected based on Internet of Things (IoT) and deep learning. A deep learning model will be trained based on the real dataset. The data will be collected by using the camera and sensors. The trained model will be used to predict the fire in the real time. The
Project Title
Fire Detector Using Computer Vision and IoT
Project Area of Specialization
Project Summary
In this project, the fire will be detected based on Internet of Things (IoT) and deep learning. A deep learning model will be trained based on the real dataset. The data will be collected by using the camera and sensors. The trained model will be used to predict the fire in the real time.
The main purpose of this work to detect the fire in real time with more accuracy. The system will be feasible for the outdoor environment where sensors are difficulty to install. In this case, the real time video will be monitored in the real time.
The use of video surveillance systems is common practice when safety is to be ensured. These systems generate a high volume of video data that needs to be parsed continuously by human operators. To ease such a tedious and error-prone task in the context of fire detection, the proposed system will be an automatic system with low cost and high accuracy.
Project Objectives
The main objectives of the proposed system are:
1. To detect fire in the real time with more accuracy.
2. To develop a low-cost fire detection system in the real time.
3. When fire is detected, notification will be sent on the gadgets and alarm sound will be generated.
Project Implementation Method
The proposed work is based on Computer Vision and IoT. The proposed solution will be consisting of four main components:
A. Deployment of Sensors
The sensors will be deployed in the system for the collection of data about the temperature, shade, smoke. Every sensor board consists of two different types of sensors, the temperature sensor, smoke sensor. Project will be implemented using Internet of Things and image recognition/processing. Sensors collect data and send it to the trained deep learning model. If there is any alarming situation the expert system will send the notification to the rescue services and turn on the alarm system.
B. Transfer of information
The information gained by the sensors will be communicated to the cloud with the help of Wi-Fi shield associated with Raspberry pi.
C. Analysis/Comparison
The cloud receives data through the internet. This data will be compared with given dataset to find either there is fire or not.
D. Inform to Authorities
Finally, after detecting the fire a message will be sent to authorities for saving lives of peoples and property to further destruction.
Benefits of the Project
This project will provide several advantages including cost effective fire detection, accurate and fast results. The system will be handy for the clients, as the system will be providing the user-friendly environment with real time access. Furthermore, the system will be more beneficial, as:
- Quick fire detection can save lives of people and protect the assets.
- Immediate response to emergency team in case of great accident might happens.
- Notify everyone in the multi-storeys building, like in the education institute and hospitals.
Technical Details of Final Deliverable
The proposed system will require camera, raspberry pi, and sensors (i-e temperature sensor TMP36, Smoke Sensor SCO7CN ). These sensors will sense certain data including , smoke, temperature and moisture.. The information gathered will be sent to cloud using wifi shield associated with Arduino board. Then this data will be tested at the recommender part of the system. Finally it will generate the results either their is fire or not and will notify the authorities.
Final Deliverable of the Project
Core Industry
Other Industries
Core Technology
Other Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| 1.Raspberry Pi 4 Model B 4GB | Equipment | 1 | 25000 | 25000 |
| 2.Alarm Motion Detector | Equipment | 1 | 10000 | 10000 |
| 3.TMP36 (temperature sensor | Equipment | 1 | 1200 | 1200 |
| 4.OV2640 (camera) | Equipment | 1 | 12000 | 12000 |
| 5.Video Graphics Card | Equipment | 1 | 13000 | 13000 |
| 6.SCO7CN (smoke sensor) | Equipment | 1 | 8500 | 8500 |
| 7.FYP Documentation (Stationary, Printing, Binding) | Miscellaneous | 1 | 10000 | 10000 |
| Total in (Rs) | 79700 |
If you need this project, please contact me on contact@adikhanofficial.com
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