UNMANNED AIR VEHICLE VIA FACIAL RECOGNITION AND GESTURE CONTROL
UAVs remain a popular talking point for many folks out there and the fact remains that they do serve various purposes across a number of verticals. UAVs perform tasks which we humans are unable to perform. (UAVs) have been around for centuries and were solely used for military purpose but now as inc
2025-06-28 16:36:31 - Adil Khan
UNMANNED AIR VEHICLE VIA FACIAL RECOGNITION AND GESTURE CONTROL
Project Area of Specialization RoboticsProject SummaryUAVs remain a popular talking point for many folks out there and the fact remains that they do serve various purposes across a number of verticals. UAVs perform tasks which we humans are unable to perform. (UAVs) have been around for centuries and were solely used for military purpose but now as increase in demand and multiple purpose use of these vehicles motivated us to make unmanned air vehicle with identification technology. This technology gave us a way to shape our task. Subsequently, we molded our principle thought, which is to limit the labor and cost that it requires for the utilization of air vehicles. The cost is reduced by removing the use of remote control which is usually of huge amount and enabled a new feature of security by making it face detected, so only an authorized person can control it by his/her respective gestures. Basically, a UAV equipped with an automatic face recognition system that can detect a person irrespective of his-her attire, face orientation, posture or background and follow him/her and second part is to make it able to recognize a few hand gestures and respond to it according to the gesture it recognizes.
Project Objectives1. A UAV equipped with an automatic face recognition system that can detect a person irrespective of his/her attire, face orientation, posture and/or background and follow him/her
2. A UAV able to recognize a few hand gestures and respond to it according to the gestures it recognizes.
The objectives of the project are:
MAIN IDEA : to minimize the man power and cost that it requires.
Object Detection: Identifying and discovering objects using HAAR Cascade.
Image Processing: to identify various objects in digital images.
Hand Gestures: Gesture detection via gesture detection device.
Project Implementation MethodThis Project is comprises of two parts
1. Facial Recognition:
The algorithm used for facial recognition is Viola-Jones algorithm that was originated by Viola and Jones.
Haar cascade classifier is the core segment of this particular algorithm.
In order to achieve fast and accurate detections, the three main components are:
- Integral Image
- Adaboost
- AL cascade
The equipments which are used in facial recognition are
- Raspberry Pi 3E
- Pi camera module
2. Gesture Control:
Following components are used in project for gesture control:
- Accelerometer – ADXL 335
- RF module – Xbee
- Encoder/Decoder – HT12E/HT120
- Arduino Nano and Mega
- it reduces the cost of UAV
- It increases the security from theft.
- Increases Productivity
- It can be used for the different purposes like surveillance, media reporting, agriculture, courier transportation and a lot more
- it has also wide range of applications in defence missions and rescue operations.
- its an attractive business idea.
The prototype integrated UAV system will be delivered along with its technical detailed reports
There are two main steps which portray the working for detection and recognition
of gesture and face:
a) TRANSMITTER END:
At the transmitter side is the accelerometer, Arduino Nano, encoder module, and RF transmitter. The signal information streams from accelerometer to the Arduino to be prepared to choose the development of the UAV. The information for movement is exchanged to the encoder module. The encoder module at that point encodes the information and transmits into the air interface with the assistance of RF transmitter.
b) RECEIVER END:
The RF receiver gets the information from the air interface and offers it to the decoder module. The decoder module interprets the got information and gives it to raspberry pi. Raspberry pi at that point gives the directions to the motors to be driven by the signal information.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 74046 | |||
| Raspberry pi | Equipment | 1 | 6000 | 6000 |
| Pi camera module. | Equipment | 1 | 2000 | 2000 |
| Arduino Mega | Equipment | 1 | 1400 | 1400 |
| Arduino Nano | Equipment | 1 | 600 | 600 |
| Xbee Module | Equipment | 1 | 9000 | 9000 |
| Xbee sheild | Equipment | 1 | 1000 | 1000 |
| Drone body | Equipment | 1 | 8000 | 8000 |
| Propellors | Equipment | 4 | 100 | 400 |
| Motor | Equipment | 4 | 2000 | 8000 |
| Battery | Equipment | 1 | 8500 | 8500 |
| Cables(VGA,HDMI) | Equipment | 1 | 2000 | 2000 |
| Monitor | Equipment | 1 | 5000 | 5000 |
| keyboard | Equipment | 1 | 700 | 700 |
| Mouse | Equipment | 1 | 300 | 300 |
| Flex sensor 2.2 | Equipment | 1 | 1700 | 1700 |
| Apm 2.8 Flight controller | Equipment | 1 | 6000 | 6000 |
| Power Regulator module | Equipment | 2 | 500 | 1000 |
| Accelerometer | Equipment | 1 | 1500 | 1500 |
| Battery 12v | Equipment | 1 | 950 | 950 |
| Miscellaneous | Miscellaneous | 1 | 9996 | 9996 |