IoT Based Semi Autonomous Vehicle using Computer Vision
The goal of the project is to design and fabricate a semi autonomous vehicle that will be capable of driving itself and learning the traffic signs and controlling the drive.The car will be controlled using computer vision. The parameters of the car will be monitored over IoT. Features include are se
2025-06-28 16:33:39 - Adil Khan
IoT Based Semi Autonomous Vehicle using Computer Vision
Project Area of Specialization Artificial IntelligenceProject SummaryThe goal of the project is to design and fabricate a semi autonomous vehicle that will be capable of driving itself and learning the traffic signs and controlling the drive.The car will be controlled using computer vision. The parameters of the car will be monitored over IoT. Features include are self driving, traffic light, sensing zebra or pedestrian crossing and lane detection.
Project ObjectivesA semi autonomous vehicle will help people with physical limitations travel easier. The marketing behind them will be to increase safety by using artifical intelligence instead of human intelligence to detect objects in the road that should be avoided. Instead of relying on human instincts built up over millions of years that ensure self preservation, a computer will be safer. As all of us know that the number of road accidents are constantly increasing due to several aspects such as conjested roads as a result of rise in population , human errors and so on. We are in need of a more safer way of travelling , so the semi autonomous vehicle play a major role.
Project Implementation MethodIn our fyp project , there is one main controller that is Raspberry pi and the other one sub-main controller that is Arduino. We took two ways input from environment one was from rpi camera and other was from sensor. With the help of Rpi camera we continously captured images from real time environment and send back it to the cloud server. We used ultrasonic sensor for object detection. If rpi camera captured traffic light signal , this input was uploaded on to the cloud , then google cloud sent instruction to the raspberry pi that is main controller that there is red light. After this, main controller sent this output to the sub controller that is arduino to controll the motors of the vehicle to stop the vehicle. For object detection we took input from sensor as well as from RPI camera, there was a object or obstacle infront of vehicle the car was be stopped. Through IoT we mointored our vehicle.
Benefits of the Project- Reductionn of Traffic accidents
- Increased road capacity
- Increased safety
- Lower furl consumption
- Reduced crime
1- Traffic Light Detection:
By image processing we trained our model to detect light signal.
2- Object Detection:
By ultrasonic sensor and with the help of rpi camera we detected object. Raspberry pi sense the object with the help of pi camera and sensor. Raspberry pi instructed the arduino to stop the vehicle.
3- Lane Detection:
With the help of rpi camera we trained our model that followed the lane where was less traffic.
Final Deliverable of the Project Hardware SystemType of Industry Manufacturing , Transportation Technologies Artificial Intelligence(AI), Internet of Things (IoT), Robotics, Cloud InfrastructureSustainable Development Goals Industry, Innovation and InfrastructureRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 52568 | |||
| Lipo Battery | Equipment | 1 | 1700 | 1700 |
| Lipo Battery Charger | Equipment | 1 | 1000 | 1000 |
| Push Button | Equipment | 20 | 10 | 200 |
| PCB | Equipment | 2 | 200 | 400 |
| PCB fiber board | Equipment | 8 | 500 | 4000 |
| DC power supply 12v | Equipment | 2 | 300 | 600 |
| 2N2907 | Equipment | 32 | 5 | 160 |
| 2N222 | Equipment | 32 | 5 | 160 |
| IN5819 | Equipment | 32 | 8 | 256 |
| Resistor (1K) | Equipment | 32 | 1 | 16 |
| Motor Connector | Equipment | 6 | 6 | 36 |
| LM7805 | Equipment | 3 | 30 | 90 |
| L293D | Equipment | 1 | 100 | 100 |
| mini drill machine | Equipment | 1 | 900 | 900 |
| iron stand | Equipment | 1 | 120 | 120 |
| drill bits | Equipment | 1 | 10 | 10 |
| LM 7812 | Equipment | 2 | 15 | 30 |
| LM 7905 ,7912 | Equipment | 4 | 20 | 80 |
| PCB SHEET paper | Miscellaneous | 3 | 30 | 90 |
| 2N3904 | Equipment | 4 | 5 | 20 |
| 2N3906 | Equipment | 4 | 5 | 20 |
| PCB | Equipment | 2 | 250 | 500 |
| RESISTOR 330OHM | Equipment | 8 | 2 | 16 |
| RES 2.2K OHM | Equipment | 8 | 2 | 16 |
| IRF740 | Equipment | 4 | 45 | 180 |
| IRF9540NL | Equipment | 4 | 60 | 240 |
| PC817C | Equipment | 8 | 15 | 120 |
| MOTOR CONNECTOR WIRE | Equipment | 1 | 10 | 10 |
| 3 WHEEL BASE | Equipment | 2 | 700 | 1400 |
| ULTRASONIC SENSOR | Equipment | 4 | 150 | 600 |
| MALE TO MALE MPER BUNDLE | Equipment | 1 | 100 | 100 |
| PI CAMERA | Equipment | 2 | 3500 | 7000 |
| ESP MODULE 8266 | Equipment | 1 | 700 | 700 |
| ETHERNET CABLE | Equipment | 1 | 150 | 150 |
| L293 | Equipment | 4 | 100 | 400 |
| IC BEDS | Equipment | 4 | 15 | 60 |
| MODULE L298 | Equipment | 2 | 300 | 600 |
| 9V BATERRY | Equipment | 1 | 50 | 50 |
| CONNECTOR HEADER | Equipment | 4 | 10 | 40 |
| VERROW BOARD | Equipment | 2 | 30 | 60 |
| MEGA 2560 | Equipment | 2 | 1180 | 2360 |
| FERRIC CHLORIDE | Miscellaneous | 1 | 70 | 70 |
| IN4007 | Equipment | 10 | 15 | 150 |
| RES 1K | Equipment | 4 | 2 | 8 |
| RED LED | Equipment | 2 | 5 | 10 |
| CAP 0.1UF | Equipment | 8 | 5 | 40 |
| CAP 220UF | Equipment | 2 | 10 | 20 |
| CAP 10 UF | Equipment | 6 | 7 | 40 |
| 7805 | Equipment | 4 | 15 | 60 |
| 7812 | Equipment | 4 | 15 | 60 |
| 7905 | Equipment | 4 | 15 | 60 |
| 7912 | Equipment | 4 | 15 | 60 |
| RASPBERRY PI | Equipment | 3 | 6000 | 18000 |
| RASPBERRY PI COVER | Miscellaneous | 1 | 1000 | 1000 |
| MEMORY CARD | Equipment | 1 | 800 | 800 |
| BLUETOOTH MODULE | Equipment | 1 | 700 | 700 |
| JUMPER WIRES | Equipment | 4 | 100 | 400 |
| JUMPER WIRES | Equipment | 2 | 150 | 300 |
| 4 WHEEL BASE | Equipment | 1 | 1200 | 1200 |
| ARENA | Miscellaneous | 1 | 5000 | 5000 |