Quality Assessment of Research. Economics and Business Administration. Amsterdam, October 2005. Vrije Universiteit amsterdam. Faculty of Economics and Business Administration. (2018) designed two DCNN models to detect parking slots, namely DeepPS. One DCNN model is based on YoloV2 ( Redmon and Farhadi, 2016) for detecting marking points on around-view images. The other DCNN model is based on AlexNet ( Krizhevsky et al.

Aim of the Project

Automatic car parking indicator system

General application and Description of the project

Nowadays in many multiplex systems there is a severe problem for car parking systems. There are many lanes for car parking, so to park a car one has to look for the all lanes. Moreover there is a lot of men labor involved for this process for which there is lot of investment. So the need is to develop a system which indicates directly which parking slot is vacant in any lane. The project involves a system including infrared transmitter and receiver in every lane and a LED display outside the car parking gate. So the person entering parking area can view the LED display and can decide which lane to enter so as to park the car.

Conventionally, car parking systems does not have any intelligent monitoring system. Parking lots are monitored by human beings. All vehicles enter into the parking and waste time for searching for parking slot. Sometimes it creates blockage. Condition become worse when there are multiple parking lanes and each lane have multiple parking slots. Use of automated system for car parking monitoring will reduce the human efforts. Display unit is installed on entrance of parking lot which will show LEDs for all Parking slot and for all parking lanes. Empty slot is indicated by the respective glowing LED.

Working of the circuit and image of the model

IR Sensors are placed inside the parking slot to detect the presence of the vehicle in slot. If the slot is not vacant then a red led will glow under the specified slot number at the entrance of the parking area or else green led will glow. The Arduino takes the data from the IR sensors and compares the received value with the threshold value and accordingly supplies power to the desired led.

Geometric Features-based Parking Slot Detection Devices

Fig. 1: Cardboard Model of Advanced Parking System

Connection for the IR sensors

Fig. 2: Circuit Diagram of IR Sensor

Block Diagram

Fig. 3: Block Diagram of Advanced Parking System

Description of the Circuit

In circuit there are 3 IR sensors are used each at 3 parking slot. These IR sensors are connected to the pin A0, A1, A2 respectively. The led’s are connected at the Digital I/O pins i.e., pin 2 for RED1, pin 3 for GREEN1, pin 4 for RED2, pin 5 for GREEN2, pin6 for RED3 and pin 7 for GREEN3.

When the slot1 will be vacant then IR receiver will not receive any signal. Hence GREEN1 will glow. If any signal is received by the IR receiver then it will be compared to the threshold value and if it is more than the threshold value then RED1 will glow. This process will be similar to all other slots.

Components Required

Geometric Features-based Parking Slot Detection Tool

1.) ARDUINO UNO

Fig. 4: Typical Image of Arduino Uno

2.) IR SENSORS

Geometric Features-based Parking Slot Detection System

Fig. 5: Typical Image of IR Transmitters and Receivers

3.) LED RED AND GREEN

Fig. 6: Typical Image of Red LED

4.) Breadboard

Fig. 8: Typical Image of Breadboard

5.) Male-male wire

Geometric Features-based Parking Slot Detection Software

Fig. 9: Typical Image of Male-Male Wires

6.) Battery

Fig. 10: Typical Image of Battery

7.) Soldering Iron and Wire

Fig. 11: Typical Image of Soldering Iron and Wire

Project Source Code

Circuit Diagrams