How students help to improve campus parking

finding a parking spot on college campus

can be frustrating

not to mention it may lead to traffic

congestion

class delays and accidents

to alleviate this challenge a group of

computer engineering students

worked on equipping parking lots with

smart parking systems

at cal state san marino in this talk

i’ll present

our system that integrates iot sensors

and civilian cameras to count vehicle

at a parking structure

while various parking systems have been

deployed

the central problem is how to make the

trade-off

between cost accuracy and reliability

smart powering system can be divided

into three categories

the first one is sensor-based method

which use stationary sensors to detect a

vehicle’s presence

by sensing ultrasonic optical

magnetism or pressure changes

you might have noticed the black circles

and squares

on the road near intersections there are

so called

inductive loops when the vehicle passes

over

the car’s mental body reduce the

inductance of the wire loop

this change tells the sensor about the

presence of the vehicle

at intersections this information will

then be used

to adjust the signal timing the same

type of sensor

has been used to monitor parking lots

the second method for accounting vehicle

is by using cameras

this picture shows the license plate

radar from a nearby tow road

in camera based method computer

compromision techniques are used

to extract vehicles movement from the

camera footage

for plate raider it required a array of

specialized

high-speed cameras if it’s just for

counting vehicles

a consumer-grade camera can work

reasonably well

the last common method for parking

monitor is what it called

crowdsourcing in popular navigation apps

you’ve seen the popular time graph or

similar functions it relies on the users

voluntarily sharing their parting

location information

from their smartphone the the more

people that are using the app

the more accurate the estimation will be

each of these methods have some

limitations when it comes to tracking

the number of vehicles

coming in and going out of a parking lot

for sensor-based method it is hard to

distinguish

between two vehicles traveling closely

together

versus one slow moving vehicle

for camera-based method it’s challenging

to maintain a clear

line of sight at all times especially in

outdoor environment additionally

driving behavior such as the aggressive

and illegal ones in parking lots can

easily confuse

computer vision algorithm as to

crowdsourcing method

the performance heavily relies on the

adoption rate

of the smartphone app so crowdsourcing

are mainly used

for a rough estimation of the parking

lot occupancy

given these observations we built a

smart parking system

by integrating both sensor based

and camera based methods we installed

new iot sensors

at the entrances and utilized existing

civilian cameras

inside parking structure the pilot

the pilot side of the system is a

parking structure

with 745 parking spots

here’s a closer look at the sensor we

used it’s a

battery powered magneto resistive

sensing device

they are installed in holes cored in the

pavement

and are covered with epoxy this picture

was taken when we put them in

different from the traditional inductive

loops no wiring is required for this

sensor

vehicle detection data are wirelessly

transmitted using ieee

802.15.4 protocol

this picture on the left shows how we

install the access point

it is similar to the household wifi

antenna

the detection data is further related to

the id service room

inside the parking structure from there

the detection data is sent to our cloud

server

our system consists of three parts

wireless vehicle detector

civilian cameras and a web server

this floor plan shows the setup at one

of the entrances

there’s one camera pointing to the

entrance

the camera was installed by the campus

police to monitor security

before this project two sensors

were installed under each lane leading

towards the parking structure

now we’re looking from the civilian

camera’s perspective

our vehicle tracking algorithm process

the live

video footage the boundary box

shows the location of the vehicle

extracted from the background

by tracking the center of the boundary

box we can find if the vehicle is

entering or leaving the parking

structure

for the iot sensors they are triggered

when the vehicle are on top of them

integrating two sensing method it allows

us to achieve

good accuracy in our test

the vehicle counting accuracy is about

96 percent

our initial plan was to develop the

smart parking system

in two steps in the first year

we’ll conduct a pilot study at one

parking lot

then in the second year we’ll expand the

system to cover most of the campus

unfortunately the second step of the

project is currently on hold

due to the code 19 interruptions

so in the last few months we looked into

data collected by the pilot system

we’re interested in how to provide

parking prediction

and studied traffic patterns

the intuition behind parking prediction

is simple

we can estimate parking occupancy in the

next 15

or 30 minutes based on historical data

this figure were taken from our website

it shows the traffic pattern

is similar between two days in different

weeks

we can further improve our estimation by

looking at

daily and weekly traffic patterns

when we turn to data analysis we have

some interesting findings

our parking structure has two entrances

this figure shows

the hourly count of detected vehicles by

each line

from the two entrances each entrance has

two lines

one for enter and one for exit

it’s interesting to note the west

entrance

receives more traffic than the other

entrance

in this figure the count in blue is

significantly larger

than the counting gray this is

likely because the vast entrance is

closer

to other parking lots and major lecture

buildings

which makes students consider vast

entrance as the default entrance

to the park structure our study finds

it will be beneficial to add a parking

direction

at the east entrance this would help to

improve

traffic flow by balancing the use of

both entrances

and may reduce congestion during rush

hours

we also looked into weekly traffic

patterns

it may provide insight on long-term

traffic trends

well the last spring and the winter

quarters

are unconventional we can see

how wildfire induced power outage

and the kovale 19 pandemic affected the

university

generally speaking we can use the

traffic pattern

to study students movement behavior

this in turn can help to improve class

schedule

campus traffic management and plan for

emergency response

for future work there are a total of

7 300 parking spaces on campus

well the pilot system only covers 10

percent of them

we hope to expand the system to include

more parking lots

our ultimate goal is to provide parking

guidance

that is suggest parking location based

on parking lots occupancy information

so that we can direct the campus traffic

so far our students deployed the pilot

system

and designed a parking prediction

algorithm

all of this are student projects with

many support

from the university in the computer

science department

our objective has been providing

students

with hands-on experience solving

real world problems and to better

prepare them

with a data-driven mindset

and with that that’s how we define the

future

you