2011 International Conference on Information and Electronics Engineering
IPCSIT vol.6 (2011) © (2011) IACSIT Press, Singapore
Visualization Cube for Tracking Moving Object
Phuoc Tran Vinh, Hong Nguyen Thi
University of Information Technology Vietnam National University - HCMC
Hochiminh City, Vietnam
Abstract. The attributes of a moving object are recorded as time series and visualized in real-time to estimate its
activities on route. Each attribute as a feature of object is represented as points in Space-Feature-Cube of which xy
plane is a map of study area and z axis indicates values of the feature. Integrated-Space-Cube integrates temporal data
of position from Space-Time-Cube and various features from Space-Feature-Cubes. Consequently, the position cube
and the feature cubes of the object can be disintegrated from the Integrated-Space-Cube. Considering the cubes of
position and features, users follow up the movement of the object and changes of its features on route. Estimating the
correlation among features in Integrated-Space-Cube, users can analyze effectively the status of features and causes of
their changes. In a tracking system, sensors of different features implemented on moving object are connected to
Integrated-Space-Cube. Data of position and features are sampled continuously with a suitable frequency and
transmitted to visualization computer. At a stationary place of the object, the curves of position and features are
extended into x axis on horizontal plane of another 3-dimension cube, tracking cube. The x axis symbolizes the
trajectory of the moving object; other axis on the plane represents time intervals at stationary positions of the object and
vertical axis represents values of features. Considering spatio-temporal correlation among features and position or
between position and time, users estimate the status and activities of object.
Keywords: space-cube, tracking system, geo-visualization, GVIS, real-time visualization GIS.
1. Introduction
Space-Time-Cube (STC) model represents a moving object as a spatio-temporal point. In STC, the
projection of an object point on map of xy plane determines position of the object in real-world and the
projection on the vertical axis indicates time corresponding to the location. The curve connecting the
projections of the points on map is quite similar to the trajectory of object. Accordingly, STC represents the
positions and corresponding times of a moving object as well as its trajectory. [1,7,10,14]
Due to activities on route, a moving object can change some features. In many cases, the change of
features of object on route needs to be monitored or recorded. An Integrated-Space-Cube (ISC) presented in
this paper is one effective solution to do that. From an ISC of a moving object, many Space-Feature-Cubes
(SFC) are disintegrated to show the change of object features. This technique can be applied well for systems
tracking vehicle.
In tracking system, an equipment of GPS (Global Positioning System) and variable-feature sensors is
implemented on moving object and connected to ISC. Data of the temporal position and features are
transmitted in real-time from object to a visualization computer to visualize in ISC. With a compatible soft
tool, user disintegrates ISC into STC, and SFCs to recognize and analyse the status of the object in real-time.
2. Space Cube for Moving Object
2.1. Space-Time-Cube for Position
Space-Time-Cube (STC) consists of the xy plane to determine the location, the z axis the moving time of
object. For a STC, an object is represented as a point of which the coordinate on xy plane of map indicates its
position in real-world and the projection on vertical axis indicates the time moment corresponding to this
position. [1,7,10,14] Tracking system records positions of a moving object at different time moments with
the same time intervals called sampling period [12] (Fig.1)
2.2. Space-Feature-Cube for Feature
Space-Feature-Cube (SFC) is formed by horizontal plane of map of the study area and vertical axis
representing a certain feature of moving object. In SFC, a feature of moving object is symbolized as one
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point of which projection on map plane indicates the position of the object in real-world and on vertical axis
indicates the value of feature corresponding to this position. Fig.2 shows that lorry weights are W0,W1,W2 at
P0,P1,P2, respectively, with W0=W1=W2. At P2, lorry weight reduces from W2 to W3 at P3. After that, lorry
comes to P4 with the weight W4=W3. At P4, lorry weight increases from W4 to W5 at P5.
Fig.1: Space-Time-Cube for Position.
2.3. Integrated-Space-Cube for Moving object
Fig. 2: Space-Feature-Cube for Feature
Data of position and features of an object are recorded in a table as time series [5]. In the table, column
indicates time, position or feature of the object and row records data of position and features of object at the
same time moment (Tab.I). An ISC for a moving object visualizes position integrated with features of the
object [9, 10]. At each position on the map of ISC corresponding with sampling time, a vertical bar [10] is
put to record the time and values of features (Fig.3).
TABLE I.
Time
TIME SERIES OF POSITION AND FEATURE
Position
Features
X
Y
Weight
Speed
Fuel
T0
X0
Y0
W0
S0
F0
T1
X1
Y1
W1
S1
F1
T2
X2
Y2
W2
S2
F2
T3
X3
Y3
W3
S3
F3
T4
X4
Y4
W4
S4
F4
Fig. 3: Integrated-Space-Cube
for Moving object
Visualization Computer
Users
GPS
Transmission
lines
Sensors
Fig. 4: The components of a Spatial Tracking System
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3. Tracking System
3.1. Introduction
Fig. 5: Space-Feature-Cubes disintegrated from ISC
A tracking system comprises three major components: (1) equipment of GPS [12,13] and feature sensors
on moving object to record temporal position and features of object; (2) transmission line to transmit position
and feature data from object to visualization computer; (3) visualization computer to support the users’
capacity of recognizing and estimation of object situation and activity. (Fig.4)
In a tracking system, data of position and features of a moving object are recorded at the same time
moments determined by sampling frequency of the system. They are transmitted to visualization computer to
store in database as data of times-series [5,12]. Here, the data are displayed visually to supply users with the
information of the object status in real-time. In addition, the data can also be stored in an equipment
implemented on moving object as a black box.
3.2. Integrated-Space-Cube in Tracking System
In a system tracking moving object, an equipment of GPS [13] and feature sensors is implemented on the
object to record and send data of position and features of the object to visualization computer [10,12] to
visualize on ISC. For a system tracking vehicle, each lorry is installed an equipment of GPS and feature
sensors of weight, fuel oil, etc. Data from the equipment of GPS and the feature sensors are transmitted to
visualization computer in real-time. Here, the data of position, weight, speed, etc. of lorry are processed to
visualize on ISC in real-time. An ISC of lorry is disintegrated into different cubes (Fig.5):
- Space-Time-Cube: to visualize the position and route of lorry;
- Space-Feature-Cubes: to visualize the status of features: + Space-Weight-Cube to visualize the weight
change of lorry; + Space-Fuel-Cube to visualize the fuel consume of lorry; + Space-Speed-Cube to visualize
speed change of lorry on route.
In each space cube, the curve connecting spatial points of a certain feature indicates the variability of this
feature of lorry on route. The curves show the activities and situation of lorry on route in real-time.
3.3. Integrated-Space-Cube to Estimate Correlation Visually
In fact, the features of a lorry change a lot on its route because of various causes. The visualization of
ISC supports to estimate the correlation between lorry position and a study feature or among its features and
detects the abnormal activities of the lorry in real-time. Actually, the cube can be disintegrated into cubes of
a study feature or cube of few features to estimate the correlation between position and the study feature or
the correlation among the different features (Fig.5).
ISC of a moving object can be disintegrated into a cube of position, one or many cubes of features. The
feature curves of disintegrated cubes can be extended as curves in 2-dimension coordinate system. In that,
lorry trajectory is a horizontal axis on which spatial sampling positions of lorry are traced; values of different
features are indicated on the vertical axis (Fig.6b). Considering the correlation among curves of position,
time and features, user recognizes the changes of features and estimates the cause of an event happening on
route of moving object [6,10].
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(a)
(c)
(b)
Fig. 6: The visualization correlation among features of a moving lorry
At unmoving place, the activities of the object are represented in a Tracking Cube (Fig.6c). As an
example, lorry stops at P1(x1,y1) to unload goods from t1 to t2, its weight reduces from Wa to Wb, Wb<Wa.
After that, lorry re-loads new goods from t2 to t3, its weight increases to Wc, Wc>Wb. At the end, lorry carries
new goods to P2(x2,y2), etc. In the cube, a horizontal axis symbolizes the trajectory of the object, another axis
on horizontal plane represents time and vertical axis feature.
Consequently, ISC, Disintegrated Cubes, and Tracking Cube answer the following questions (Tab.II):
-
Where the feature changes. The feature curve answers this question.
-
When the feature changes. The correlation between feature curve and position curve answers this
question.
-
What the feature changes. The feature curves answer
this question.
-
How the feature changes. The feature curve answers
this question.
-
Why the feature changes. The correlation between
curves of changed feature and other features or
position answers this question.
TABLE II. RELATIONS AMONG QUESTIONS
Based on the information
To answer
Where
When
When
Where
What + Where + When
How
When+Where+What+How
Why
4. Conclusion
Integrated-Space-Cube integrates all data of temporal position and features into a cube to follow up the
movement of an object. Integrated-Space-Cube is disintegrated into Cubes of various features to visualize the
variability of one or few features.
Integrated-Space-Cube visualizes the features of a moving object based on the model of 3-dimension
cube. Basically, each feature changing in time is visualized in Integrated Space-Cube as the feature changing
in space. Consequently, the correlation among object features is estimated based on the feature curves as a
function of position. Therefore, Integrated-Space-Cube is suitable for systems tracking moving objects of
independent features.
In a system tracking vehicle, GPS equipment and feature sensors are implemented on vehicle to record
data of its position and features and transmit to visualization computer. The activities of vehicle are followed
up in real-time. Data of position and features are visualized on the Integrated-Space-Cube in real-time.
The visualization of position and features of a moving object in a real-time Integrated-Space-Cube
answers the questions of Where, When, What, How, Why concerning the activities of this object.
5. Acknowledgment
This study is created at the TRANTECH Ltd. (GlobalGIS) in Hochiminh City, Vietnam.
6. Biography
Phuoc Tran-Vinh is Associate Professor of Informatics, Vice Rector and Chair of the GIS Program at the
University of Information Technology (UIT) in Vietnam. He received his Ph.D. in Informatics from Vietnam National
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University. From 1994 to 2006, he was founder and Director of the Center for Developing IT and GIS (DITAGIS), one
of the first research institutes about GIS in Vietnam in 1990s. In 2005, he obtained the gold medal from MOST for his
contribution to the development of science and technology, specially GIS in Vietnam. He is also a technical consultant
of TRANTECH Ltd. (GlobalGIS), a company focuses on developing government GIS systems and spatial tracking
systems in Vietnam. His interests include real-time spatial information system, geo-visualization, real-time geovisualization, GIS for administration, access control in government GIS systems, real-time GIS for disaster and climate
change. His contact information is Phuoc.gis@gmail.com
Hong Nguyen Thi is a lecturer of Rubber Industrial College in Binhphuoc Province, Vietnam. She received M.S in
Computer Science from Vietnam National University – HCMC. She is a Ph.D. student of the UIT with the topic of
visualization in GIS and presented some first researches at MapAsia 2010 and ICMLC 2011. Her contact information is
Hongnguyen1611@gmail.com
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