Apollon - 22/5/12 - 09:00 - User-driven Open Innovation Ecosystems
7 deus leaflet wp6
1. DEUS
Deployment and Ease Use of wireless Services
Positioning
Main challenges
Knowledge of the current location of an object or moving person is very useful for several
applications. In the use cases of DEUS, we want to guide a person through an exposition
in a museum or in a historical building. The person receives some sort of PDA when he
arrives at the museum, which then provides him with information based on his current
location (e.g. information on a specific painting, historical background of a room). It
could also guide someone to a specific part of the exposition, based on the interests of
the user. The main challenge in DEUS is to provide an easy-to-use and easy-to-deploy
indoor positioning solution which achieves room-level accuracy based on cheap, off-the-
shelf wireless sensor nodes.
DEUS Approach
The positioning application uses the wireless sensor network developed by DEUS and is
therefore based on the IEEE 802.15.4 radio technology. These wireless sensor nodes are
spread out over the building and gather the information needed to determine a user or
asset’s position. The user or asset that needs to be located is equipped with a wireless
sensor node that sends beacons, which are picked up by the other wireless sensor nodes.
These sensor nodes subsequently send this information to a positioning server. This
positioning server analyses the gathered information and calculates the user/asset’s
position. Applications that want the user or the asset’s position contact the positioning
server to receive the required information.
In the DEUS project, we have developed the communication protocol between the sensor
nodes and the positioning server and we have implemented three methods to determine
the position. These were evaluated separately and a hybrid solution was also considered.
2. DEUS
Deployment and Ease Use of wireless Services
DEUS solutions
The figure above shows the general concept of the positioning application. We want to
determine the position of the person on the left. This user is wearing a PDA and a
positioning tag (i.e. an IEEE 802.15.4-based sensor node). This sensor node sends
positioning beacons at regular intervals. The beacons are intercepted by the wireless
sensor nodes spread out in the building. The nodes individually combine the received
information and the measured link information into a measurement report and send this
report wirelessly to the positioning server. There, the information is gathered, processed
and a position for the user is calculated. This positioning information can then be used by
an application. This information is graphically visualized and can be accessed via a
webservice. An example can be found in the following figure. The blue dots are the
sensor nodes attached at fixed locations in the building, the red dot is the user’s position.
3. DEUS
Deployment and Ease Use of wireless Services
Implemented solutions
Proximity based
In this solution, the asset’s position is determined by finding the fixed sensor node that is
the closest to the asset. The range of the mobile node is limited so that only one fixed
node can receive the positioning beacons. The resulting accuracy depends on how far the
fixed sensor nodes are placed from each other.
Weighted algorithm
A more advanced solution is the weighted algorithm.
Weights between fixed nodes are calculated based on the
received signal strength. These weights are subsequently
used for triangulation. This method allows us to
compensate the fluctuating RSSI values. Using this
solution, an indoor accuracy of 5m can be achieved in one
room. However, larger fluctuations occur in hallways due
to multipath fading and reflection.
Map-based intelligence
An error that often occurs in the previous solutions is that the user can walk “through
walls”, i.e. the position of the user is erroneously switched to a neighbouring room. In
order to solve this, we use the map information to determine the exact room. More
precisely, with each door a sensor node is associated and we have to pass by this node in
order to enter or leave a room. Map information was received by TeleAtlas.
Hybrid Solution
Finally, we have implemented a hybrid solution that combines the three solutions above.
This has lead to an average accuracy of 3m, both in hallways as in larger rooms. This
accuracy is linked to the node density and will most likely increase when the node density
decreases. Further testing is needed to investigate this effect.
DEUS Proof of Concept implementation
The DEUS positioning solution can be used for indoor navigation. The user’s position is
determined via the sensor network and navigation info is given to the user by a GUI
interface. The map info is provided by TeleAtlas and the navigation software by
GeoSolutions.
4. DEUS
Deployment and Ease Use of wireless Services
Project partners
In cooperation with
IBBT research groups
UGent - IBCN http://www.ibcn.intec.ugent.be
UGent - WiCa http://www.wica.intec.ugent.be
UA - PATS http.www.pats.ua.ac.be
KU Leuven – DistriNet http.www.distrinet.cs.kuleuven.be
KU Leuven – CUO http://ww.soc.kuleuven.be/com/mediac/cuo
UHasselt - EDM http://www.edm.uhasselt.be/