WIRELESS REMOTE MONITORING SYSTEM WITH

FLEXIBLY CONFIGURABLE MULTIVISION

Shinichi Masuda, Tetsuo Hattori

Graduate School of Enginieering, Kagawa University, Takamatsu City, Kagawa, 761-0396 Japan

Keywords: Wireless remote monitoring, Multivision, Wireless sensor with ID, Event driven, Infrared camera

Abstract: Novel remote monitoring system for all day outdoor observation using wireless communication is

proposed. It consists of three parts: a host station that is PC, remote station (camera and CPU) attached by

solar cell and battery for power supply, and wireless sensor with ID (identification) signal. The remote

station usually performs based on the event driven method by the sensor signal. It also can control the

camera according to the sensor’s ID. So the multivision monitoring system is flexibly configurable. This

paper describes the details of the system and evaluates the maximum number of connectable remote

stations. Since the systems are now really running at many places in Japan, we consider that the fact shows

its effectiveness in a practical sense.

1 INTRODUCTION

Recently, the necessity of monitoring camera system

has increased in a wide variety of fields. And the

image processing research for such monitoring

system has been done in many ways (

K.Yamada, et al.,

2000), (T.Sogo, et al., 2000), (H.Mori, et al., 2001),

(H.Nagahara, et al., 2001).

The purpose of this kind of

vision system is not only for security against crime

and disaster in the social and individual life, but also

for investigation and control such as of vehicle

traffic. In some of those monitoring camera systems,

especially in outdoor system, the capability of all day

and all weather monitoring with self-feeding of

electric power is required. Moreover, the flexibility

of configuration and installation of multiple cameras

(multivision system) is also required, depending on

the place to be observed.

In this paper, we present a compact wireless

remote monitoring system that we have developed in

order to meet the demands in outdoor monitoring

system. The system is composed of three parts: host

computer (PC) that we call base station, CPU built-

in monitoring camera and the peripherals that we call

remote station, and wireless sensors that are

independent of the monitoring camera. The system

has the following features.

The remote station is made as a self-feeding

system, mainly using solar battery for power supply.

By the wireless communication of portable handy

phone, etc., acquired images at the remote station are

transmitted to the base station.

With all weather and darkness, the camera in

the remote station can acquire images using the

functions of auto focus, auto iris, lens zooming, and

night vision. The camera automatically changes into

an infrared one, depending on the lightness.

Usually based on the wireless sensor’s signal,

the remote station is driven to work. That is, as soon

as one of the wireless sensors detects some object

such as human body, it sends a radio signal to the

remote station, then the station inputs image and

transmits it to the base station.

Because each wireless sensor sends the

discrimination radio signal (or radio ID signal) to the

remote station, the station can control the viewpoint

of camera according to the signal. Then, using those

wireless sensors, it is expected that multi remote

stations are easily composed as a multivision system

with arbitrary configuration for various purposes

such as cooperative tracking.

484

Masuda S. and Hattori T. (2004).

WIRELESS REMOTE MONITORING SYSTEM WITH FLEXIBLY CONFIGURABLE MULTIVISION.

In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics, pages 484-487

DOI: 10.5220/0001147804840487

 SciTePress

2 SYSTEM

2.1 Outline

The monitoring system is composed of base station,

remote station, and wireless sensors, as shown in

Figure 1. The remote station usually takes rest state

and it runs according to the wireless sensor’s signal,

that is, it drives and makes the camera acquire

images, and then it transmits the compressed image

data to the base station. After this series of

operations, the remote station automatically takes a

rest state again. The remote station also supplies the

power to the infrared light when it runs at night. It is

possible to force the remote station to run or to rest

by a command signal from the base station.

Figure 1: Conceptual image of the system.

The remote station can continuously keep running

for 5 days using built-in battery, even if there is no

power supply from the solar cell. The wireless sensor

has also a built-in battery, and it keeps working for 2

years. One base station can control a maximum

number of 256 remote stations. And one remote

station can distinguish a maximum number of 16

wireless sensor signals. The wireless sensor’s signal

is effective within approximately 200 meters far

from the remote station. Each wireless sensor can

send the radio ID signal, so the remote station can

operate depending on the ID signal. Then, the

multiple remote stations can work cooperatively. For

example, they can also acquire images of one object

from many directions at the same time.

2.2 Remote Station

Since the multiple remote stations can take images in

many different ways such as synchronous or

asynchronous acquisition, according to the

configurations in the area to be monitored, we can

flexibly construct various multivision monitoring

system. The block diagram of the remote station is

shown in Figure 2.

The remote station is excellent in portability

and is easily installed. After the remote station is put

at some place, the base station can tune up the

precise viewpoint of camera and lens zooming, etc.,

because the base station can easily control the remote

station by wireless communication.

Figure 2: Block diagram of the remote station.

2.3 Performance of Remote Station

As aforementioned, the Built-in microprocessor

(CPU) in the remote station recognizes the wireless

sensor’s ID signal, and take a series of actions:

image acquisition, image data compression, image

transmission, etc. The storage battery in the station

stores electric power by solar energy and supplies it

when necessary.

The specification of the remote station is as

follows.

・Battery:

12V, 15Ah.

・Solar cell:

16.3V, 1.65A/24W.

・Continuous working period without sunlight:

5 days guaranteed.

・Unit box:

Dust and water proof.

Size [mm]: W270×H310×D200×2.

Weight [kg]: Approximately 13kg×2.

As for the image data, the specification is as

follows.

Remote Station

Observation

Area

Invader

Wireless

Sensors

Base Station

CPU

CAMERA

CONTROLLER

BATTERY

POWER

CIRCUIT

SOLAR

PANEL

IMAGE

ENCODER

IMAGE

COMPRESSION

FRAME

MEMORY

GENERAL

I/O

SENSOR

RECEIVER

HANDY

PHONE

SERIAL

I/F

GENERAL

MEMORY

EVENT

VIDEO

WIRELESS SENSORS

CLOCK

WIRELESS REMOTE MONITORING SYSTEM WITH FLEXIBLY CONFIGURABLE MULTIVISION

485

・Image to be transmitted:

Still image, JPEG formatted.

・ Size of one original image data (RGB color

image):

640x480 [pixels] x 3[Byte/pixel] = 921.6 kByte.

・Compressed image file size:

Attached header etc.: 2kByte.

Compressed image: 40 kByte (Average).

・Frame memory (RGB color image):

640x480 [pixels] x 3[Byte/pixel] x 10.

・Image transmission rate [sec/frame] :

Cellular phone: 60.

Handy Phone: 30 (Approximately).

As for the transmission time of compressed

image file, the average value is as follows.

・Dialling time: Approximately 10 seconds.

・Transmission time including the above dialling

time:

Cellular phone line: Approximately 55 seconds.

Handy phone line: Approximately 30 seconds.

Figure 3 shows the appearance of the remote station

that is divided into two units for the weight balance.

The installation example is shown in Figure 4.

2.4 Base Station

The station is composed of an IBM compatible PC

(personal computer) and the interface for wireless

communication (Figure 5).

The base station can control the remote station

freely. When it receives an image from the remote, it

tells the fact to an operator (or supervisor) by a voice

message. If the operator is absent, the base station

automatically transfers the voice message to a

designated telephone. The station can also store the

transmitted image for at maximum 1,000 days.

Figure 5: Outlook of the base station.

3 THE NUMBER OF REMOTE

STATIONS

3.1 Bit Error Rate and Transmission

Time

In usual case, it is not difficult for the base station to

do image processing faster than the speed of video

signal transmission, if it uses some hardware image

processor

. Then, the performance of the monitoring

system considerably depends on the communication

system.

We roughly estimate the transmission time,

assuming that the bit error stochastically occurs in

Poisson process and that only error detection

function is effective in the communication between

the remote station and the base one.

Let

and

T be the original necessary

transmission time without any error occurrence and

the average transmission time under the environment

where bit error occurs with the probability

(BER:

Bit Error Rate), respectively. And, let

S be the

packet length, we have

T = T

×(1+

) (1)

Based on (1), the relation between

and T is

illustrated in Figure 6.

Figure 3: Outlook of the remote station.

Figure 4: Example of the installation.

ICINCO 2004 - ROBOTICS AND AUTOMATION

486

Figure 6: The relation between BER and

transmission time

3.2 Estimation of Connectable Units

Now we suppose that all remote stations have to

send one image data to the base station. Let Rn and

Tc be the number of remote stations and the average

transmission time per image data including dialling

time, etc., respectively. There happens many

collisions in connection to the channel (or line),

however with or without any collision, we can

roughly estimate that the total time for all image data

to be sent is approximately Tc×Rn.

Let C be a miscellaneous time such as dialling

time. And let

Nave and Lt be the average number

of image data to be sent and the effective (or active)

time for communication between the base station and

remote stations, respectively. Then, among those

parameters and the aforementioned time

and Tc,

the following relational expressions hold.

Tc = T

×(1+

)+C (2)

Tc×Nave×Rn ≦Lt (3)

From (3), the number of connectable remote

stations Rn can be calculated. Now we assume that

the bit error rate

is 1.0×10

-7

and that the

transmission rate is 9600bps as aforementioned. In

this case, for the simplicity, we set each parameter as

follows.

=45 [sec/image],

=256 [Byte] =2048 [bit],

=1.0 × 10

-7

, C=10[sec], Lt=24[hours/day]=

86400[seconds/day], Nave=24[images/day] per

remote station.

From (2) and (3), we have

Tc =55 (4)

Rn≦Lt /(Tc×Nave)=65.5 (5)

Then, as a rough estimation in this case, we can

tell that it is possible to effectively use remote

stations up to 65 units. If we consider the worse

condition of bit error rate 1.0×10

-4

, we can calculate

that about 56 units of remote stations are effective.

4 CONCLUSION

We have developed a compact wireless remote

monitoring system that is capable of outdoor image

acquisition in all weather and all day. The remote

station has a built-in CPU and a camera, which is

attached by a solar battery for power feeding. The

built-in camera can acquire images using auto focus,

auto iris, lens zooming, and night vision functions. It

can automatically change into an infrared one,

depending on the lightness. The remote station is

usually based on an event driven method, i.e., it runs

according to the wireless sensor’s signal. Since each

wireless sensor transmits its own radio ID signal, the

remote station can control the viewpoint of camera

according to the signal. Because of those functions

and the compactness of the remote station, multi

remote stations can be flexibly installed as a

multivision system in arbitrary configuration.

The base station also can control the remote

station by giving a compulsory command signal, so

it can obtain monitored images periodically or at any

time from the remote stations.

The proposed monitoring system is adopted by

more than 20 local governments in Japan and is

currently running well.

REFERENCES

K.Yamada, et al., 2000. A Parking Lot Monitoring System

Using Image Processing. IEEJ Trans. EIS, Vol.120-C,

No.6, pp.784-790, (2000-6) (in Japanese).

T.Sogo, H.Ishiguro, Mohan M.Trivedi, 2000. Real-Time

Human Tracking System with Multiple Omni-

Directional Vision Sensors. IEICE Trans. D-II, Vol.

J83- D-II, No.12, pp.2567-2577, (2000-12) (in

Japanese).

H.Mori, A.Utsumi, J.Ohya, M.Yachida, R.Nakatsu, 2001.

Human Motion Tracking Using Non-synchronous

Multiple Observations. IEICE Trans. D-II,Vol.J84-D-

II, No.1, pp102-110, (2001-1) (in Japanese).

H.Nagahara, Y.Yagi, M.Yachida, 2001. Resolution

Improving Method from Multi-Focal Omnidirectional

Images. IEICE Trans. D-II ， Vol.J84-D-II ， No.8,

pp1882-1890, (2001-8) (in Japanese).

1.E-08 1.E-07 1.E-06 1.E-05 1.E-04 1.E-03

BER

Transm ittion time[sec]

Send A C K per packet.

Send A C K w hole data received.

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