Online Face Recognition System Using Gaussian Naive Bayes Machine Learning Algorithm Based On Drone Technology.
Since faces are a part of inherent identities of people, or most probably there can be a difficulty of searching people or finding people in areas that are too difficult and dangerous for human being to reach...Face Recognition Drone is the solution to the problem, which will be used for detecting a
2025-06-28 16:34:20 - Adil Khan
Online Face Recognition System Using Gaussian Naive Bayes Machine Learning Algorithm Based On Drone Technology.
Project Area of Specialization Internet of ThingsProject SummarySince faces are a part of inherent identities of people, or most probably there can be a difficulty of searching people or finding people in areas that are too difficult and dangerous for human being to reach...Face Recognition Drone is the solution to the problem, which will be used for detecting and tracking targets with treats. It will take a picture of person and search and identify the people on the ground with a surveillance camera and remote monitoring. Face recognition capability is a key for drone to detect or identify the individuals within a crowd. It will be a pre-programmed drone, we will use our own algorithm to identify the person in image and tag the identified person by transmitting the location to the concerned authorities.
Project Objectives- To develop RC based Drone
- To detect faces in an image capture by camera mounted on Drone.
- To design an algorithm to identify person in image.
- To synchronize a Drone with the designed algorithm (Autonomous).
- Tag the identified person by transmitting the location to the concerned authorities.
- The image processing software used in this project is OpenCV.
- The first goal is to have a program recognize a face and put a box around it.
- The face detection software can spot many faces in the same image, but this would only confuse the drone So, the best way to do that was to have the drone try and keep the center of the face in the center of the screen.
- We used the dimensions of the box around a face to determine a center point.
- By having the autopilot, it easy to check the width of the box around the face.
- The width of the boxed face equaled 100 pixels
- The drone use a combination of tilting and turning to correct horizontal errors.
- All of the movement options are adjusted to produce the best tracking possible.
- We create a database of 25 pictures of each group member.
- The LBPH Recognizer is the most robust of the three options and performs the best when there is no guarantee for consistency in the quality and lighting of a picture.
- The main purpose of making face recognition drone is to improve our security system.
- As we know that, the current security situations of the city is not good and the street criminals become the biggest threat for the citizens.
- This drone can helps police and other security agencies to identity the criminal by using the raspberry pie camera.
- It can prove most beneficial to improve the security system.
In this project we are going to using quad copter, raspberry pie, raspberry pie camera, gyro sensors, ultrasonic sensors and GPS.
Final Deliverable of the Project HW/SW integrated systemType of Industry Telecommunication Technologies Internet of Things (IoT), Robotics, OthersSustainable Development Goals Quality Education, Industry, Innovation and Infrastructure, Sustainable Cities and CommunitiesRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 51900 | |||
| Quad Copter | Equipment | 1 | 35000 | 35000 |
| Raspberry Pie | Equipment | 1 | 6500 | 6500 |
| Raspberry pie Camera | Equipment | 1 | 5500 | 5500 |
| Gyro Sensors | Equipment | 1 | 400 | 400 |
| Ultrasonic Sensors | Equipment | 4 | 500 | 2000 |
| GPS | Equipment | 1 | 2500 | 2500 |