PDPT FRAMEWORK
Building Information System with Wireless Connected Mobile Devices
Ondrej Krejcar
Centre for Applied Cybernetics, VSB Technical University of Ostrava, 17. listopadu 15, Czech Republic
Keywords: Information system, mobile device, PDA, WiFi, PDPT framework.
Abstract: The proliferation of mobile computing devices and local-area wireless networks has fostered a growing
interest in location-aware systems and services. Additionally, the ability to let a mobile device determine its
location in an indoor environment at a fine-grained level supports the creation of a new range of mobile
control system applications. Main area of interest is in model of radio-frequency (RF) based system
enhancement for locating and tracking users of our control system inside buildings. The framework
described here joins the concepts of location and user tracking in an extended existing control system. The
experimental framework prototype uses a WiFi network infrastructure to let a mobile device determine its
indoor position as well as to deliver IP connectivity. User location is used to data pre-buffering and pushing
information from server to user’s PDA. Experiments show that location determination can be realized with a
room level granularity.
1 INTRODUCTION
The usage of various wireless technologies that
enable convenient continuous IP-level (packet
switched) connectivity for mobile devices has
increased dramatically and will continue to do so for
the coming years. This will lead to the rise of new
application domains each with their own specific
features and needs. Also, these new domains will
undoubtedly apply and reuse existing (software)
paradigms, components and applications. Today,
this is easily recognized in the miniaturized
applications on network-connected PDA’s that
provide more or less the same functionality as their
desktop application equivalents. The web browser
application is such an example of reuse. Next to this,
it is very likely that these new mobile application
domains adapt new paradigms that specifically
target the mobile environment. We believe that an
important paradigm is context-awareness. Context is
relevant to the mobile user, because in a mobile
environment the context is often very dynamic and
the user interacts differently with the applications on
his mobile device when the context is different.
While a desktop machine usually is in a fixed
context, a mobile device goes from work, to on the
road, to work in-a-meeting, to home, etc. Context is
not limited to the physical world around the user, but
also incorporates the user’s behaviour, and terminal
and network characteristics.
Context-awareness concepts can be found as
basic principles in long-term strategic research for
mobile and wireless systems such as formulated in
(WWRF). The majority of context-aware computing
to date has been restricted to location-aware
computing for mobile applications (location-based
services). However, position or location information
is a relatively simple form of contextual information.
To name a few other indicators of context awareness
that make up the parametric context space: identity,
spatial information (location, speed), environmental
information (temperature), resources that are nearby
(accessible devices, hosts), availability of resources
(battery, display, network, bandwidth), physiological
measurements (blood pressure, hart rate), activity
(walking, running), schedules and agenda settings.
Context-awareness means that one is able to use
context information.
We consider location as prime form of context
information. Our focus here is on position
determination in an indoor environment. Location
information is used to determine an actual user
position and his future position. We have performed
a number of experiments with the control system,
focusing on position determination, and are
encouraged by the results. The remainder of this
162
Krejcar O. (2006).
PDPT FRAMEWORK - Building Information System with Wireless Connected Mobile Devices.
In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics, pages 162-167
DOI: 10.5220/0001215001620167
Copyright
c
SciTePress
paper describes the conceptual and technical details
of this.
2 BASIC CONCEPTS AND
TECHNOLOGIES OF USER
LOCALIZATION
The proliferation of mobile computing devices and
local-area wireless networks has fostered a growing
interest in location-aware systems and services. A
key distinguishing feature of such systems is that the
application information and/or interface presented to
the user is, in general, a function of his physical
location. The granularity of location information
needed could vary from one application to another.
For example, locating a nearby printer requires fairly
coarse-grained location information whereas
locating a book in a library would require fine-
grained information.
While much research has been focused on
development of services architectures for location-
aware systems, less attention has been paid to the
fundamental and challenging problem of locating
and tracking mobile users, especially in in-building
environments. We focus mainly on RF wireless
networks in our research. Our goal is to complement
the data networking capabilities of RF wireless
LANs with accurate user location and tracking
capabilities for user needed data pre-buffering. This
property we use as information ground for extension
of control system.
2.1 Location-Based Services
Location-based services (LBS) are touted as 'killer
apps' for mobile systems. An important difference
between fixed and mobile systems is that the latter
operate in a particular context, and may behave
differently or offer different information and
interaction possibilities depending on this context.
Location is often the principal aspect determining
the context. Many different technologies are used to
provide location information. Very common is the
GPS system, which uses a network of satellites and
provides position information accurate within 10–20
m. However, due to its satellite based nature, it is not
suited for indoor positioning. In cellular
telecommunication networks such as GSM, the cell
ID gives coarse-grained position information with an
accuracy of about 200 m to 10 km. For fine-grained
indoor location information, various technologies
are available, based on infrared, RF, or ultrasonic
technologies often using some type of beacon or
active badge. Given the ubiquity of mobile devices
like PDAs, however, active badges will probably be
superseded by location technologies incorporated in
these devices.
In the context of our experimental setup, we need
indoor position information accurate enough to
determine the room in which the user is located. We
must deploy a separate location technology, where
we use the information available from a WiFi
network infrastructure to determine the location with
room-level accuracy. By this information possible
user track is estimate.
2.2 WiFi - IEEE 802.11
The Institute of Electrical and Electronics Engineers
(IEEE) develops and approves standards for a wide
variety of computer technologies. IEEE designates
networking standards with the number 802. Wireless
networking standards are designated by the number
11. Hence, IEEE wireless standards fall under the
802.11 umbrella. Ethernet, by the way, is called
802.3 (Reynolds, 2003).
The 802.11b is an updated and improved version
of the original IEEE 802.11 standard. Most wireless
networking products today are based on 802.11b.
802.11b networks operate at a maximum speed of 11
Mbps, slightly faster than 10-BASE-T Ethernet,
providing a more than fivefold increase over the
original 802.11 spec. The 802.11 standard provided
for the use of DSSS and FHSS spread-spectrum
methods. In 802.11b, DSSS is used.
We use only 802.11b infrastructure (PDA has
only this standard) so other standards (802.11a or g)
is not needed to describe. However, it can be
possible to develop a PDPT framework with it.
2.3 Data Collection
A key step in the proposed research methodology is
the data collection phase. We record information
about the radio signal as a function of a user’s
location. The signal information is used to construct
and validate models for signal propagation. Among
other information, the WaveLAN NIC makes
available the signal strength (SS) and the signal-to-
noise ratio (SNR). SS is reported in units of dBm
and SNR is expressed in dB. A signal strength of s
Watts is equivalent to 10*log10(s/0.001) dBm. A
signal strength of s Watts and a noise power of n
Watts yields an SNR of 10*log10(s/n) dB. For
example, signal strength of 1 Watt is equivalent to
30 dBm. Furthermore, if the noise power is 0.1 Watt,
PDPT FRAMEWORK - Building Information System with Wireless Connected Mobile Devices
163
the SNR would be 10 dB. The WaveLAN driver
extracts the SS and the SNR information from the
WaveLAN firmware each time a broadcast packet is
received. It then makes the information available to
user-level applications via system calls. It uses the
wlconfig utility, which provides a wrapper around
the calls, to extract the signal information.
2.4 Localization Methodology
The general principle is that if a WiFi-enabled
mobile device is close to such a stationary device –
Access Point (AP), it can “ask” the location
provider’s position by setting up a WiFi connection.
If the mobile device knows the position of the
stationary device, it also knows that its own position
is within a 100-meter range of this location provider.
Granularity of location can improve by triangulation
of two or several visible WiFi APs as described on
figure [Fig. 1].
Figure 1: Localization principle - triangulation.
Figure 2: PDA Locator – AP intensity & Positioning.
The PDA client will support the application in
automatically retrieving location information from
nearby location providers, and in interacting with the
server. Naturally, this principle can be applied to
other wireless technologies.
The application (locator) based on .NET
language is now created for testing. It is
implemented in C# using the MS Visual Studio
.NET 2003 with compact framework and a special
OpenNETCF library enhancement (Tiffany, 2003)
and (WWRF). Current application [Fig. 2] records
just one set of signal strength measurements. By this
set of value the actual user position is determined.
2.5 WiFi Middleware
The WiFi middleware implements the client’s side
of location determination mechanism on the
Windows Mobile 2005 PocketPC operating system
and is part of the PDA client application. The
libraries used to manage WiFi middleware are:
AccessPoint, AccessPointCollection, Adapter,
AdapterCollection, AdapterType, ConnectionStatus,
Networking, NetworkType, and SignalStrength.
Methods from the Net library are used for example
to display Visible WiFi AP. See figure [Fig. 3].
dtVisibleAP = new DataTable("Visible
AP");
DataRow drDataRow;
adptrColection =
networking.GetAdapters();
foreach (Adapter adptr in
adptrColection)
{
Application.DoEvents();
if (adptr.Type==AdapterType.Ethernet)
{
foreach (AccessPoint ap in
adptr.NearbyAccessPoints)
{ drDataRow = dtVisibleAP.NewRow();
drDataRow["BSSID"] =
(ap.Name.ToString());
drDataRow["Signal [%]"] =
((ap.SignalStrength.Decibels).ToString(
));
dtVisibleAP.Rows.Add(drDataRow);
}
}
}
Figure 3: Sample code – signal strength from AP.
2.6 Predictive Data Push
Technology
This part of project is based on model of location-
aware enhancement, which we used in created
control system. These information about are useful
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in framework to increase real dataflow from wireless
access point (server side) to PDA (client side).
Primary dataflow is enlarged by data pre-buffering.
These techniques form the basis for predictive data
push technology (PDPT). PDPT copies data from
information server to clients PDA to be on hand
when user comes at desired location.
The benefit of PDPT consists in reduction of
time needed to display desired information requested
by a user command on PDA. Time delay may vary
from a few seconds to number of minutes. It
depends on two aspects. First one is the quality of
wireless Wi-Fi connection used by client PDA. A
theoretic speed of Wi-Fi connection is max 825
kB/s. However, the test of transfer rate from server
to client’s PDA, which we have carried out within
our Wi-Fi infrastructure provided the result speed
only 160 KB/s. The second aspect is the size of
copied data. The application (locator) based on .NET
language is now created for testing. Current
application (see figure [Fig. 2]) records just one set
of signal strength measurements. By this set of value
the actual user position is determined.
2.7 Framework Design
PDPT framework design is based on most
commonly used server-client architecture. To
process data the server has online connection to the
control system. Data from technology are
continually saved to SQL Server database (Tiffany,
2003) and (Reynolds, 2003). The part of this
database (desired by user location or his demand) is
replicated online to client’s PDA where it is
visualized on the screen. User PDA has location
sensor component which continuously sends to the
framework kernel the information about nearby
AP’s intensity. The kernel processes this information
and makes a decision if and how a part of SQL
Server database will be replicated to client’s SQL
Server CE database.
The kernel decisions constitute the most
important part of whole framework because the
kernel must continually compute the position of the
user and track and make a prediction of his future
movement. After doing this prediction the
appropriate data (part of SQL Server database) are
pre-buffered to client’s database for future possible
requirements. The PDPT framework server is
created as Microsoft web services to handle as
bridge between SQL Server and PDPT PDA Clients.
Figure 4: System architecture – UML design.
3 EXPERIMENTS
We have executed a number of indoor experiments
with the PDPT framework, using the PDPT PDA
application. WiFi access points are placed at
different locations in building, where the access
point cells partly overlap. We have used
triangulation principle of AP intensity to get better
granularity. It has been found that the location
determination mechanism selects the access point
that is closest to the mobile user as the best location
provider. Also, after the loss of IP connectivity,
switching from one access point to another (a new
best location provider) takes place within a second
in the majority of cases, resulting in only temporary
loss of IP connectivity. This technique partially uses
a special Radius server (RADIUS) to realize
“roaming” known in cell networks. User who loss
the existing signal of AP must ask the new AP to get
IP. This is known as “renew” in Ethernet networks.
At the end of this process, user has his same old IP
and connection to new AP. Other best technique to
realize roaming is using of WDS (Wireless Decision
System).
Currently, the usability of the PDPT PDA
application is somewhat limited due to the fact that
the device has to be continuously powered. If not,
the WiFi interface and the application cannot
execute the location determination algorithm, and
the PDPT server does not receive location updates
from the PDA client.
PDPT FRAMEWORK - Building Information System with Wireless Connected Mobile Devices
165
Battery Power Consumption for PDPT Locator
338
327
255
140
128
100
223
215
165
50 100 150 200 250 300 350
9
8
7
6
5
4
3
2
1
Test [No]
Time [min]
Figure 5: Battery power consumption graph.
3.1 Battery Power Consumption
Tests
We have executed a number of tests of battery
power consumption with three PDA devices running
PDPT Locator. The tests were executed from 100 %
battery level to 20 % battery level with balanced
load. The first was HTC Blue Angel PH20B which
is known also as MDA III from T-Mobile (Intel
XScale PXA263 CPU, MS WM2005 OS). The
second one was iPAQ h4150 from Hewlett &
Packard Company (H&P) (Intel XScale PXA255
CPU, MS WM2003 OS). The third one was iPAQ
hx4700 from H&P (Intel XScale PXA270 CPU, MS
WM2003 SE OS). These devices have Li-Ion battery
with different capacity (1490 mAh, 1000 mAh and
1800 mAh). MDA III device has integrated GSM
module in addition.
Test Type CPU [MHz] Scan WiFi Backlight
1 400 2 s ext. 50%
2
MDA
III
400 10 s norm. off
3 100 2 s norm. off
4 h4150 400 2 s ext. 50%
5 400 10 s norm. off
6 100 2 s norm. off
7 hx4700 624 2 s ext. 50%
8 624 10 s norm. off
9 104 2 s norm. off
Figure 6: Battery tests description.
The test chart [Fig. 5] shows number of results. The
first, most evident and expected result is caused by
different battery packs. The power consumption is
worse for h4150 model and the best for hx4700
model. The second aspect is evident as well. The
score is better when the backlight is turned off.
However, the very large score is at hx4700 test case
comparing to two other PDA. The last interested
result is however in 100 MHz CPU speed setting.
The speed decreasing was controlled by special
utility managing the core of operating system. When
the maximum speed of CPU was decreased, the
working time of PDA increased about several
percent. This result is last useful thing for enlarge
battery power consumption.
The practical type of PDA usage with PDPT
application is somewhere between minimum and
maximum score of these tests for such model of
PDA. For example the mean usage of the worse
PDA iPAQ h4150 is about two hours of working
time so it is not very comfortable, but it is usable for
many types of operations. Other two devices have
battery consumption time higher so practical use is
without remarkable limitation.
3.2 Data Transfer Increase Tests
Using PDPT Framework
The result of utilization of PDPT framework is
mainly at data transfer speed reducing. The second
test is focused on real usage of developed PDPT
Framework and his main issue at increased data
transfer. At table [Fig. 7] are summary of eighteen
tests with three type of PDA and three type of data
transfer mode. Each of these eighteen tests is
fivefold reiterated for better accuracy. At table are
only average values from each iteration.
Test Type Mode
Data
[kB] Time [s]
Speed
[kB/s]
1 SQl CE 257 0.4 643
2 SQl CE 891 0.4 2228
3 SQL 257 5 51
4
MDA III
SQL 891 13 69
5 PDPT 257 1.1 234
6 PDPT 891 3.2 278
7 SQl CE 257 0.5 514
8 SQl CE 891 0.5 1782
9 h4150 SQL 257 5 51
10 SQL 891 14 64
11 PDPT 257 1.2 214
12 PDPT 891 3.7 241
13 SQl CE 257 0.3 857
14 SQl CE 891 0.4 2228
15 hx4700 SQL 257 5 51
16 SQL 891 13 69
17 PDPT 257 0.9 286
18 PDPT 891 2.5 356
Figure 7: Data transfer tests description.
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166
The data mode column has three data transfer mode.
The SQL CE mode represents the data saved at
mobile device memory (SQL Server CE) and the
data transfer time is very high. The second mode
SQL means data which are stored at server (SQL
Server 2005). Primary the data are loaded over
Ethernet / Internet to SQL Server CE of mobile
device and secondary the data are shown to user.
The data transfers time consumption of this method
is generally very high and the waiting time for user
is very large. The third data mode PDPT is
combination of previous two methods. The PDPT
mode has very good results in form of data transfer
acceleration. Realization of this test consists at user
movement from location A to B at different way
direction. Location B was a destination with
requested data which are not contained at SQL CE
buffer in mobile device before test.
4 CONCLUSION
The main objective of this paper is in the
enhancement of control system for locating and
tracking of users inside a building. It is possible to
locate and track the users with high degree of
accuracy.
In this paper, we have presented the control
system framework that uses and handles location
information and control system functionality. The
indoor location of a mobile user is obtained through
an infrastructure of WiFi access points. This
mechanism measures the quality of the link of
nearby location provider access points to determine
actual user position. User location is used in the core
of server application of PDPT framework to data
pre-buffering and pushing information from server
to user PDA. Data pre-buffering is most important
technique to reduce time from user request to system
response.
The experiments show that the location
determination mechanism provides a good indication
of the actual location of the user in most cases. The
median resolution of the system is approximately
five meters. Some inaccuracy does not influence the
way of how the localization is derived from the WiFi
infrastructure. For the PDPT framework application
this was not found to be a big limitation as it can be
found at chapter Experiments. The experiments also
show that the current state of the basic technology
used for the framework (mobile device hardware,
PDA operating system, wireless network
technology) is now at the level of a high usability of
the PDPT application.
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319-326, ISSN 1790-5079
Reynolds, J.: Going Wi-Fi: A Practical Guide to Planning
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The Internet Engineering Task Force RADIUS Working
Group: http://www.ietf.org/
The Wireless World Research Forum (WWRF):
http://www.wireless-world-research.org/
OpenNETCF - Smart Device Framework:
http://www.opennetcf.org/
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