[IEEE 2014 Third International Conference on Agro-Geoinformatics - Beijing, China (2014.8.11-2014.8.14)] 2014 The Third International Conference on Agro-Geoinformatics - Research on sensor data visualization method based on real-time dynamic symbol

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  • Research on sensor data visualization method based on real-time dynamic symbol

    Donglai Jiao College of Geographical and Biological Information

    Nanjing University of Posts and Telecommunications Nanjing, China


    Lizhi Miao*,Jie Jiang College of Geographical and Biological Information

    Nanjing University of Posts and Telecommunications Nanjing, China


    AbstractGeographic information system has been widely used in sensor device management . The sensor was abstracted into the map symbol and displayed on the map. while it is difficult to realize the real-time data visualization in the GIS visualization process, this paper studied the design method of the real-time dynamic map symbol, applying the communication protocol to the process of modeling and visualization of the map symbol. this study builds data model of real-time dynamic map symbol from two aspects(data communication protocol, visualization), and put forwards the combining method of the communication protocol, dynamic symbol real-time sensor data visualization in the GIS environment. so as to realize the sensor data visualization based on the real-time dynamic map symbol.

    KeywordsMap Symbol; Internet of things; Geographic information system; communication protocol; real-time visualization.

    I. BACKGROUND The Internet of things(IOT) is an intelligent perception

    information network system with sensor identifier which promote the communication between human and things. It is a new developing technology after the computer, the Internet and mobile communication network[1]. Nowadays, Related technology of the Internet of things has been widely used in many fields, such as intelligent transportation, environmental protection, intelligent logistics etc. Geographic Information System provides the space for foundation for the development of the Internet of things. The spatial analysis, visualization and other functions of GIS, are powerful supporting for IOT applications. Managing the sensor of IOT with location character based on GIS is a common practice to combine GIS with the IOT. The formidable spatial data management makes GIS have the advantage in sensor management of IOT, but geo-visualization in GIS has defects in terms of real-time information visualization of the sensor. Map symbol rendering was the main approach for geo-visualization, the mainstream GIS software, such as SuperMap, MapGIS, ArcInfo etc, are based on the visualization of map symbols. In device management process, map symbol can be viewed as a conceptual model of device, which reflects the basic attributes of sensor device(space objects)[2,3]. Establishing communication of map symbol and the sensor data based on

    communication protocol can realize the real-time visualization for the sensor.

    The research of the map symbol related to visualization focuses on the visual variables. Bertin studied the visual variables earliest and put forward shape, orientation, size, brightness, density and color, which were used in cartography[4]. Yu considered that visual variables should include the shape, size, orientation, brightness, density, structure, color and position[5].

    Expanding variable in time and space based on visual variables is the way to study the map symbol variable system. Hua[6] extended four dynamic parameters(long, rate, rder, rhythm) on the basis of Bertin's theory. He also established the mapping between symbol dynamic parameters and the changing features based on temporal comprehensive principles, and used the symbol dynamic parameters to show the temporal characteristics of geographic entities. Zhu[7] designed a dynamic map symbols based on the combination of multiple transformation based on the structure of key frame-layer-primitive-geometric which packed the symbols state description and operation process(different transformation for different parameters). Miu put forward the real-time dynamic map by combining with computer animation technology which extend and expand the concept of dynamic symbols[8]. The essence of the real-time dynamic map is that the real-time data source change leads to the map change. Miao[9,10] summarized the expression method of dynamic phenomena in drawing, and pointed out that the dynamic repression is related to the specific conditions and the purpose of map. Wu studied the issues of map symbol conflict in visualization[11,12], and discussed the rendering methods commonly used in the process of symbol configuration. In the light of the conflict problems in the allocation of symbols, Wu put forward the solution based on the spatial relationship and the voronoi diagram. Yang analyzed analysis the spatio-temporal expression of the current spatio-temporal database[13], and realized the visualization of spatio-temporal data by using computer animation, dynamic symbol and dynamic map technology.

    In GIS-IOT, the sensor was abstracted as a map symbol. However, when the traditional map symbols were used in the field of the IOT (such as sensor management), due to the lack of the supporting of communication protocol and real-time data processing, the traditional map symbol is hard for real-time This work is supported by The National Natural Science Foundation of

    China (41101358, 41101359);Surveying, Mapping and Geoinformation Research Project of Jiangsu(JSCHKY201403). *Corresponding author. .

  • visual of the sensor. Therefore, the combination of communication protocol and map symbol modeling which makes the dynamic change of map symbol and the sensor data effectively united is very important. The new data model of map symbol based on communication protocol and real-time data processing technology can provide a new way for real-time data visualization for sensor.

    II. MAP SYMBOLS AND SENSOR DATA VISUALIZATION Visualization of the real-time data of sensor essentially

    belongs to the data visualization. Data visualization technology is the theory that convert the data into graphic displayed on the screen, and the process of the visualization is interactive. The process of data visualization is defined as the filtering, mapping, drawing, feedback[14,15]. The visualization process includes two levels, namely the data level and the graphic level. The data level is used to represent the logical and measurable relations between objects. The graphic level show the logical and measurable relations in graphical mode which consist of the graphic elements.

    When the devices were management by GIS, the sensors were abstracted into map symbols, with the help of the map symbol rendering process provided by GIS, the sensors were represented on the map. The data item of real- time sensor data need to visualization is diverse, and the traditional rendering takes the whole map symbol for unit can not meet the requirements. The description method based on graphic element is the main method to design the map symbol. Each map symbol can be decomposed into several elements, Different graphic elements can be combined into different map symbols, the visual variables of map symbol can be reflected in the drawing parameters of the graphic element. The drawing parameters include position, shape, color, brightness, size, direction, and texture. The combination of graphic element controlled by drawing parameters can easily produce a variety of expression effect. For the rendering takes the map symbols for units cant satisfy the sensor data visualization, the map symbols need to be decomposed into graphic elements, and realize sensor data visualization by establishing the mapping relationship between the data and the graphic element. In order to meet the requirements, we need to store and manage graphic element in map symbol design process, establish ID for each element, in order to establish the mapping relations.


    Since the dynamic map symbols organized by graphic elements, and the visual variable of element can be controlled by drawing parameters. Therefore establishing the mapping between the sensor data and drawing parameters can ultimately implement the linkage of sensor data change and the visual variable change.

    A. Mapping sensor data and visual variables Sensor dynamic data gets into the system via an external

    data exchange equipment, such as I/O boards, PLC smart meters, intelligent modules etc. external data exchange equipment matches to the type of sensors, and achieve the data

    by the driver, the driver sets the communication, device address and the logical name of the external device. The sensor data type is defined as a discrete variable memory, I/O discrete variable, real variable memory, I/O integer variables, memory string variable, I/O string variables and so on. Different data types use different mapping methods in visualization.

    For example, when using the "circle" to express the density of PM2.5, we need to establish the correspondence between "circle" diameter and the density of PM2.5, the size of the "circle" will change when rendering according to the density probed by the sensor . Similarly, for the same area at different times, changes in PM2.5 density can also be expressed in a time sequence of changes inside by this method. PM2.5 density, and in the symbol is the "circle" in size, changes with time. Therefore, the process of mapping the sensor data and visual data is actually a process of variable state visualization.

    Different domain of sensor data take difference ways during the mapping process of drawing graphic element parameter values, and the visual effect of expression are not the same (Fig 1). For example, when the data of the sensor changes consecutively, it can be expressed by the varying color, the initial value and the final value of the color has the direct corresponding relation to the data domain, the middle value of color was calculated by linear methods. the process can also be described by the shape change of graphic element which implements by specified the relationship between the minimum height and the maximum height of the graphic element and the scope of domain.

    Fig. 1. Differnt mapping method for different value domain

    B. Mapping between visual variable and parameters of graphic element The graphic elements in map symbol were controlled by

    drawn parameter during rendering. Table 1 describes the correspondence between the drawn parameters of point symbol and the visual variables (part).


    Parameter Visual variable Graphic element PenColor color Line, Ellipse, Polygon, Solid Line etc FillColor color Line, Ellipse, polygon etc Height shape Triangle, Rectangle etc Width shape Triangle, Rectangle etc Size size Line, Ellipse, Polygon etc Angle direction Line, Ellipse, Polygon etc FillModel Texture Rect fill, Ellipse fill etc

  • C. The mapping method of Sensor data and visual variables Since graphic element drawing parameters and visual

    variable is one to one relationship, so the mapping between the sensor data and visual variables is the core issues of a visual mapping. According to the changing characteristics for sensor data, interpolation mapping and direct mapping were the main two types. for example, a gradient sensor data can be described by color variables with interpolation mapping (Fig 2 a), and direct mapping is suitable for the discrete sensor data because the mapping between discrete value and visual variables is relatively simple which can be described by rules (Fig 2 b).

    Fig. 2. interpolation mapping and direct mapping

    If the mapping method is the interpolation type, in the map symbol design process, we need to define the domain of sensor data, and define the visual variables and their corresponding range which ensure that the sensor data border and visual variable boundary values were one-to-one mapping(Fig 3). The middle visual variable value is calculated by the interpolation functions, such as color_mid, shape_mid, size_mid.

    Fig. 3. The rules of interpolation mapping

    Unlike the interpolation mapping, there is no linear relationship between the sensor data and visual variables in direct mapping procession, therefore we need to establish mapping rules of sensor data and visual variables. The production rule is a common way to describe the rules that define the conditions and results by using production ("IF ...

    THEN") schema.Conditions and results are described by the regular expression. Expression is composed of three parts: the sensor data item name, relational operators and map symbol visual variable values, relational operators use the traditional logical operators(Fig 3), such as "=", ">", "> = "," 0.08" />

  • on spatial. on the one hand, define spatial function code in protocol, on the other hand, develop spatial query in the process of parsing which can implement by data service middleware. The middleware exchange data with sensor, and set up the effective link among sensor - data exchange equipment - data middleware - data parsing-GIS layer.

    B. Message management for sensor dynamic data Considering the fact that sensor data acquisition depend on

    the data service middleware on the server, long connection mechanism by TPC/IP is used between the middleware and the client. The client continuously intercepts the data information from the server, the driver module was triggered after client receiving new data, and the map symbols render again. when the map scope changes, the long connection mechanism timely inform scope change to the middleware on the server, the middleware adjust the message queue for the corresponding.

    C. Driver module The driver module is the core of the real-time sensor data

    visualization by dynamic map symbol. The module convert the real-time sensor data to standard data that satisfies requirements of the data mapping, and then load the mapping rules, convert the real-time data to visual variables of the graphic element, and finally output visualization.


    This experiment takes data acquisition for remote electric meter as an example, the real-time state of remote electric meter was displayed by dynamic map symbol. OpenLayers and GeoServer were used to build the WebGIS. This experiment takes electric degree and residual energy as the sensor data that the map symbols display. The display of real-time meter data by the dynamic map symbol as Fig 5.

    Fig. 5. The visualization of real-time meter data by dynamic map symbol

    VI. CONCLUSION Map symbol plays an important role in GIS visualization.

    This paper analyzed the characteristics of the real-time sensor data. The visualization methods for real-time sensor data was put forward which is based on the mapping relation between graphic element and sensor date. In order to achieve the visualization by the dynamic map symbol, this paper designed the...


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