The 9th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI 2012)
Nov. 26-28, 2012 in Daejeon Convention Center(DCC), Daejeon, Korea
Self-Configuration for Surveillance Sensor Network
Alexander Filonenko, Fei Yang, Andrey Vavilin, and Kang-Hyun Jo
Electrical Engineering Department, University of Ulsan, Ulsan, 680-749, Republic of Korea
(Tel : +82-10-5657-1664; E-mail: {alexander, yangfei, andy, jkh2011}@islab.ulsan.ac.kr)
Abstract - This paper describes an autonomous monitoring
system to supervise environmental parameters such as
temperature, humidity, poisonous gases or smoke
concentration, etc. This system is designed as a set of
sensor nodes connected via a wireless network. The
feature of this system is its ability to autonomously
configure the network structure and synchronize data
between nodes. This allows the network to be
fault-tolerant. Each sensor node consists of three layers.
The bottom layer includes a 5 to 12 volts battery and a
stabilizer. The middle level consists of an 8-bit
microcontroller, LCD (Liquid Crystal Display), SD
(Secure Digital) card reader, and a set of sensors. The top
level includes RF (Radio Frequency) communication
module and GPS (Global Positioning System) module.
Each sensor node is able to work as a standalone unit and
as a part of a sensor network. The experimental works
were performed for ensuring worth using in real time.
development 10 sensor nodes were assembled on
perfboards (Fig. 1(a)).
Sena ProBee-ZE10 2.4 GHz modules are used for
wireless communication. Outdoor sensor nodes were
designed to be used indoors and outdoors in various
environmental conditions including the wind, the rain, and
the light snow (Fig. 1(b), 1(c)).
Keywords - sensor network, environmental surveillance,
ZigBee.
1. Introduction
Nowadays any wireless sensor network implements
computation, sensing and wireless communication
functions [1]. Researchers [2] have developed the network
which implements these functions. According to their
design a working ability of the whole network depends on
the operability of the main sensor node. The second
shortcoming is that data could not be gathered in real time.
Other researchers’ system has a drawback: its operability
fully depends on availability of wireless communication
[3].
The system which is proposed in this article should
overcome the drawbacks which were mentioned above.
The full-scale sensor network includes online sensor
nodes, main coordinators, and back-end users where the
data gathered and analyzed. GUI (Graphical User
Interface) based on the sensor network is supported for an
operator to make a decision such as evacuation of the
personnel or call to a fire station at an emergency situation.
The implemented system is designed to operate
autonomously during one week without recharge and send
data in real time.
2. Hardware
As in [4] each sensor node consists of the same core
elements but may use different types of sensors according
to the current task. For the prototyping stage of
Fig. 1. Sensor nodes: (a) the prototype, (b) the
intermediate design, (c) the final desing, (d) the final
working module.
Figure 1(d) shows the working module in a case which
proved its reliability during outdoor tests. The case
consists of two floors. The box with sensors projects from
the second floor. The opened bottom part of the box allows
gathering adequate environmental data while roof and
walls protect sensors from water and snow.
The sensor network uses two types of computers. The
first one is the data storage where a UART terminal and a
MySQL database are used to store data from all the
sensors.
The second type of computer is a back-end user with
the GUI for an operator.
3. Communication Protocol
The wireless mesh network ZigBee standard is used
which based on the IEEE 802.15.4 standard.
There are three types of sensor network members: a
sensor node, a data storage, and a black box.
The function of the black box is to save to its SD card
environmental data of every node. This increases stability
of gathering statistical data. If data storages unavailable on
other nodes, the black box might work and save all the
needed data for a long time because it uses its own battery.
Unlike [5] the sensor node never goes to the sleep mode.
It increases power consumption (up to 0.9 watts) but
allows sending real-time data without significant delays.
The ZigBee protocol makes it possible for sensor nodes
automatically choose the best way of the data transmission.
If sensor nodes could not find any black box during 10
minutes, one of existing sensor nodes is reconfigured to be
the new black box. Every data storage and black box at the
moment of entering to the network sends the broadcast
instruction. This instruction uses pattern:
+SENDER_NAME|COMMAND_CODE\n
After initial operations every sensor node sends data to
all black boxes and data storages using the following
pattern:
+SENDER_NAME|[T:Temperature][;H:Humidity]
[;G:Gases][;S:Smoke][;D:Dust][;GPS_data]\n
Data storage may send command to the exact sensor
node or the black box to make them change their type to
black box and sensor node respectively.
There are constraints exist for ProBee modules. The
maximum payload of the message is 90 bytes. ZigBee
compliance rules prevent flooding of the network by
limiting the network to a maximum of 9 broadcasts over 8
seconds[6].
logs sensor data using the SD card. If temperature or
concentration of poisonous gases became too high, the
microcontroller turns on all devices and tries to find a
network again. In the emergency case data transmission
delays should be minimal. Other sensor nodes stop
sending their own data. From this moment data is sent only
by the sensor nodes which detect extreme temperature and
gas concentration.
Every sensor node has its own hard coded unique ID.
This allows creating a white list of nodes which can send
or receive data. Using that kind of list increases security
but decreases flexibility of the network.
5. Software
Sensor network should cooperate with computer
network. Figure 2 shows the principle of network
members’ interaction.
The data storage is a computer with MySQL database
connected to the sensor network via ZigBee.
To access network data back-end user needs a computer
with the installed GUI program connected to the Internet
(Fig. 3). This program analyzes data, builds charts, and
shows the position of sensor nodes and visual information
in real time. This program can use Google maps, Ovi maps,
and others. This allows operator to keep vigilant watch
over some territory and react to critical changes of
environmental parameters.
Fig. 2. Network architecture.
4. Self-Configuration
Every sensor network member is in the range of the
signal of a least two other members. This allows us not to
lose “tails” of members [7] in case when one of them
failed.
There is at least the one black box in the network. If
there is no response from any of black boxes,
microcontroller configures one of the sensor nodes to
become the new black box.
If the SD card of the black box became almost full,
microcontroller reconfigures this node to become the
sensor node and sends the command to the other sensor
node which converts that node to the black box.
If the SD card of the sensor node became full it turns off
the SD card module to save power.
If there is no wireless signal, the sensor node turns off
wireless module, LCD, and GPS. In this mode the node
Fig. 3. Back-end user GUI.
6. Experiments
Experiments were conducted to check properties of
sensors and quality of the network itself. All the sensor
nodes enter the network in 5-10 seconds depending on
distances between nodes.
First of all the maximum communication range was
checked in urban conditions. The line of sight was
partially occluded by trees. Table 1 shows that modules
have different signal power but all of them can work
within 428 meters without losing packets. The module
“48D0” can send signal farther than shown in the table but
it started losing data.
smoke sensor reached steady-state in 5716 cycles. Every
cycle in this test lasted 1.5 seconds. That means the smoke
sensors requires 2.4 hours before it starts to show real data.
Table 1 Maximum communication range tests.
Module name
Maximum range (meters)
1884
428
48D5
435
48D4
438
48D9
439
48D3
443
187F
444
48D2
451
48D1
457
48D0
464
Average range
444
In the fog maximum distance decreased to 220 meters.
In park area where the line of sight was fully blocked by
trees and bushes, the maximum distance was 120 meters.
When data was sent through the building, the range went
down to 50 meters. The network has proved its reliable
work within 4-points transmission when data from the
sender to the receiver was retransmitted by two
intermediate sensor nodes.
Minimum delay between messages which guarantees
100% error-free communication was tested. Maximum
possible length of the message was used (90 bytes). If the
sensor node can send data to the computer directly, the
minimum possible delay was 0.33 seconds. If the sensor
node sends the message to two computers, the delay
should be 1.5 seconds. If 4-point transmission is used, the
delay could not be less than 3 seconds. On the other hand
the less the length of the message the less can be the delay.
For example, the network works without errors when the
wireless module sends 2 bytes every 100 milliseconds.
During tests the database contained more than 600000
records. Thanks to indexing every standard query to the
database can be done during 0.05 seconds. Receiving
about 100000 records to build the long period chart takes 2
seconds.
Tests showed that using of the one black box and
computer is optimal to make data gathering stable. Further
increase in the number of devices leads to a noticeable
increase in network latency.
The GUI should not require high end computers, so it
was tested on the netbook where it consumed about 30
megabytes of the RAM and up to 40% of the 1.66 GHz
processor time (without charts building).
The temperature and humidity sensor shows real data
right after it received power. Gas and smoke sensors
require time to get warmed up. Figure 4 shows that the
Fig. 4. Warming up time.
The gas sensor requires 3 hours to warm up. The high
peak near the 6100th cycle occurred when a cigarette was
smoked nearby.
Figure 5 shows the data gathered in September 26-27
during 24 hours. Figure 4 actually shows first 8 hours of
the test on Fig. 5. Temperature is shown in Celsius degree.
Humidity, gas, and smoke concentrations are shown in
percent.
Fig. 5. September 26-27 outdoor test results.
It can be seen again that the system requires time to
enter the working condition. Changes in temperature and
humidity have no effects on the smoke sensor. At day time
temperature increased and humidity decreased. The
poisonous gases concentration slightly increased in day
time.
Figure 6 shows results of the test conducted in the 1
week in July 2012. Sensor nodes were placed on
windowsills to get data both indoors and outdoors.
Temperature changed almost periodically according to
time of day. Humidity was less stable. On July 20 air
conditioning was turned on because of high temperature in
the rooms and poisonous gases concentration surprisingly
increased. The gas sensor detects hydrogen sulfide,
ammonia, ethanol, and carbon monoxide. At the same time
smoke sensor values increased. The smoke sensor also
detects carbon monoxide. The test was repeated with air
conditioner again and similar results were received. We
conjecture that filters cannot filter this poisonous gas.
7. Conclusion
We have successfully developed the self-configurable
surveillance sensor network which could overcome
drawbacks of other researchers’ networks. The averange
communication range is 444 meters. Our network works in
real time; it is programmed to be stable and useful even in
emergency cases. Hundreds of operators may watch over
the factories, campuses and other territories even if
operator is situated on the opposite side of the world. We
have successfully connected the sensor network and the
Internet. Thanks to self-configuration the sensor network
is more intelligent than previous ones.
In future works we would like to combine the proposed
method of reliable network communications with
flexibility of UAV based on the multi agent concept in a
mobile autonomous surveillance system. Such system will
be capable to perform effective autonomous monitoring of
huge areas with low resource consumption.
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Fig. 6. July 19-25 mixed test results.
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