# Fusion Development of Public Art and Urban Environment Design Based on Wireless Sensor Data Fusion

Authors: Zhen Xiao
Journal: Mobile Information Systems
 (2022)

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## Abstract

Driven by the market economy, the city’s infrastructure has been continuously improved, and the living standards of the people have been continuously improved. The need for the integrated development of public art and urban environmental design has become one of the important tasks in the entire urban construction work. However, in the integrated development, public art and urban environment, as two subjects, have different development histories and complex influencing factors. Combining this information for effective analysis is a computationally and processing intensive task. This paper uses the data fusion method in wireless sensors to study the fusion development of public art and urban environment design and understand the historical development and various characteristics of public art and urban environment design. And we apply it in fusion analysis experiments, use wireless sensors for information collection, use data fusion methods for analysis, and compare with traditional methods. The experimental results show that the wireless sensor data fusion method is used in the research of the fusion development of public art and urban environment design. The average value of associated fusion degree reaches 84.08% and the average value of balanced fusion degree reaches 80.60%, which has certain effectiveness. Popularizing it in the current stage of urban construction can highlight the city’s personality and style and enhance the city’s cultural taste and modern cultural atmosphere.


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## Body

## 1. Introduction

With the progress of the times and the improvement of the economic level, the social structure has begun to undergo earth-shaking changes, and the needs and levels of the masses for the material living environment have gradually increased. Improving urban construction and promoting the integrated development of public art and urban environmental design have become the primary tasks in the development process of each city. Public art and urban environment are not only an important part of the overall appearance of a city but also an important carrier of the urban cultural connotation. The effective integration of the two can enhance the overall image of the city and the aesthetics and temperament of the masses. However, in today’s era, the integration of public art and urban environment design not only stops at the satisfaction of functional conditions (residents’ clothing, food, housing, and transportation) but also needs to match the economic and cultural development of urban construction and play a coordinating and promoting role in all aspects. We improve the ecology and artistry of the entire city to meet the growing spiritual needs of residents. This will be a construction work with a huge amount of tasks, and in the analysis of the entire integration development, the influence and coordination of various factors are difficult to control. Therefore, relying on scientific and technological means, it is very urgent to carry out research work on the integration and development of public art and urban environment design.Under the rapid development of communication technology, wireless sensor data fusion shines brightly in market development and industrial applications and has exerted its own application value in many value fields. For example, it can be seen in agriculture, military, medical, finance, industry and commerce, and other industrial fields. It improves the core competitiveness of various industries in the market and promotes their continuous transformation and upgrading, fully catering to the characteristics of the information age. It not only changed the inherent way of production and life but also facilitated people’s life. Applying it to the research on the integrated development of public art and urban environment design can improve the quality and effect of design and construction work, and provide scientific basis and decision making for sustainable urban development.This paper integrates the data fusion method in wireless sensors into the fusion development analysis of public art and urban environment design. In the fusion results of multiple tests, cities use data fusion methods to analyze and calculate public art and urban environment data. The lowest absolute error is only 1.035, the highest is 2.031, and the relative error is 2.03% and 3.97%, respectively. And in the fusion results, the average degree of association and fusion of public art and urban environment design is 84.08%, and the average degree of balanced fusion is 80.60%. This shows that wireless sensor data fusion can play a high application value in the integrated development of public art and urban environment design.


## 2. Related Work

In recent years, many scholars have conducted in-depth research on public art and urban environment design. Fisher-Gewirtzman et al. [1] believed that the visual experience in public art and urban environment design is a part of daily life, which constantly influences and influences our choices [1]. Mitschke et al. [2] believed that the combination of field and laboratory testing is feasible in the design of public art and urban environment, and through the research, results illustrate the importance of art display in daily life [2]. L’Hostis [3] discussed the properties of urban environment and public art in optimizing distance in urban construction; in this sense, the two should be regarded as relevant principles of urban space design [3]. Artopoulos et al. [4] introduced a technique for using interactive and immersive opportunities to engage citizens and stakeholders in the management of relevant public open spaces for the integration of public art and urban environmental design [4]. In order to evaluate the impact of physical attributes on the integrated development of public art and urban environmental design, Israt and Adam [5] conducted a questionnaire survey and physical observations in two study areas of the city and obtained various sources of evidence [5]. Bagley and Fraser [6] discussed recent developments in the fusion of public art and urban environment design, as well as emerging opportunities to customize and possess some of these spatial spaces, developing an atmosphere of public inclusion and synergy for positive cities [6]. The fusion of public art and urban environment design has been developed in a relatively mature stage at this stage after profound research by countless scholars. However, with the continuous improvement of the economic level and the continuous renewal of urban construction, the requirements for public art and the urban environment are also constantly increasing. In order to meet the development of the times, it has become a smarter choice to apply wireless sensor data fusion to the research on the fusion development of public art and urban environment design.In order to deepen the wireless sensor data fusion, this paper understands its related application research. Aiello et al. [7] proposed an integrated pest management method for intensive production based on wireless sensor data fusion. This method is inexpensive and reduces the use of pesticides and fertilizers [7]. Bijarbooneh et al. [8] proposed a method that can take into account data connection mass and temperature and humidity dependent, which reduces power requirements to a strict level by allowing the acquisition of parameters through the extraction and redirection of data from sampled modules [8]. In order to improve the reliability and prolong the life of the wireless sensor network monitoring system, Yu et al. [9] proposed an adaptive prediction weighted data fusion algorithm based on clustering [9]. Wu et al. [10] believed that maritime search and rescue wireless sensor networks have always been the cornerstone of finding floating targets after shipwrecks. He formulated the cluster topology of MSR-WSN by defining the sea area for object detection [10]. Li [11] investigated data fusion and proposed a CRAE-based protection privacy conservation algorithm with existing classification methods, which can effectively diminish the amount of battery revenue available to satellite systems [11]. The correlations between transducer-to-target range and sampling capability, alongside associations between hesitant and cohesive sensors, have been quantified by Kejiang and Xiao [12] and provide guidance for confident sensing [12]. These studies provide a good analysis of wireless sensor data fusion. However, due to the rapid development of the times, intelligent algorithms have expanded from relatively professional technical fields to urban construction, and there are very few applied researches on the application of blending social art with public environment design. Therefore, there is an urgent need to investigate the evolution of the integration of social art and public environmental design based on wireless fusion of data from sensors.


## 3. Method

### 3.1. Theory of Public Art and Urban Environment Design

The birth of public art is developed on the basis of the construction of the public domain, so it also has certain characteristics to some extent. The word public domain first appeared in Germany, and its definition is also translated into English according to the word public open in German, and it has been gradually passed down to this day. We turn a place that is free and open and allows multiple people to share and participate as a public space, and public art is the cultural and artistic creation in this public space. In the process of social development, the object of public art has always been the entire social group. In its creation, it will consider a variety of social factors such as race, ecology, and economy. And then, we use an artistic perspective and method to characterize the inextricable relationships among them. Therefore, public art can be regarded as an important symbol of the development of human art and culture.Throughout the development process of human culture, on the basis of the history and characteristics of public art, it is the theme of this paper to explore the relationship between public art and urban environment, and to deeply analyze the development of urban appearance and artistic connotation.As a very special space, the city is closely constructed without losing rhythm and is mainly used for the dissemination and preservation of human civilization. The development of public art after the 1980s can be said to be a process in which works of art gradually embrace the public and move toward environmental art. Re-examining its development process, we can clearly see that public art is closely related to urban development in various periods, and we can also see that contemporary public art gradually pays attention to the life of citizens and the urban environment in the process of growth. We call the space that can be seen visually in the urban environment as the tangible environment, and the main forms are shown in Table1. Judging by the property of the open space, most of them belong to the public space of the city. Through visual feedback, these tangible urban environments usually use nonverbal expressions to more directly affect people’s visual system, giving people’s consciousness and thinking hints and enlightenment.Table 1
Categories of public spaces in cities.
ScoreSequenceClassificationTangible space in the urban environment1Squares2Buildings3Sculptures4Gardens5Green spaces6Public facilitiesAs the main artistic creation in urban public space, public art is bound to be restricted and influenced by the environment. Public art decorates public space, and public space highlights public art. If every piece of public art is attached to the urban public space, then the value of public art depends on the degree of its integration with the real environment. On the other hand, it depends on whether public art meets the functional needs of the public space in the city where it is located. That is to say, contemporary public art with hugely different forms of expression in different eras is to meet the inner needs of the city, which covers politics, economy, culture, and people.The urban environment of each era is the epitome of human civilization in this era. As a very special cultural phenomenon, public art plays a particularly outstanding and important role in the development of contemporary urban and environmental art. It reflects the personality of the times in the process of urban development. After the 1950s, modernism went from prosperity to decline, and in the 1950s and 1960s, the postmodernist thought gradually matured, which had an impact on the idea of modernism. Until the 1960s, postmodern thought became a popular word in the world. Postmodernity has a distinctly reflective character and radical modernity, which is defined as an attitude, a way of thinking and feeling. Since then, modernity has entered a period of reflection. Then, with the postmodern movement and the social changes involved in modernity issues, art and culture began to leave the museum and seek the combination of art and environment in a wider space.On the one hand, this is a serious challenge to modernism, and that is, where are the true boundaries of art? Originally, this boundary has always been defended by modernists. On the other hand, it breaks the inner boundaries of art. Modernism distinguishes between art and nonart, aesthetic and everyday, and elite and mass. Although the self-discipline of art is maintained, it also greatly limits the social function of art. Postmodernism resolves these divisions of modernism, and art shows significant postmodernism characteristics with stronger tension. The first emphasizes the coordination with the environment, the second does not oppose decoration and uses a large number of decorations, and the third is usually symbolic or metaphorical. As the most vibrant part of contemporary art, public art casts aside the constraints of the original modernism, absorbs various design concepts, and presents a kaleidoscope of rich forms.Due to the characteristics of postmodernism focusing on decoration and integration with the environment, it is destined that the connection between public art and urban public space will be closer. At the same time, in the architectural field of urban space, public buildings are no longer just functional spaces, but are replaced by individualized and complex styles that integrate multiple elements, and are endowed with more cultural significance. At this time, the relationship between public art and architecture, which is an important part of urban design civilization, has also changed, and urban environmental design and public art have been blended. This is a manifestation of the functionalization of public art and the increasing emphasis on decoration and integration with the surrounding environment in the design of the urban environment itself. It is the inherent requirement of the development of urbanization to the stage of pursuing urban spiritual civilization.The positive impact of the current integrated development of public art and the environment on the city is reflected in the highlighting of the city’s individuality. In the 1950s, the modernist urban architectural style was popular and gradually reached its peak. The similarity of urban buildings is extremely high, the pursuit of functions and simple shapes, resulting in the same urban style; thousands of cities are one-sided; cities have no personality; and the buildings have no characteristics. This phenomenon is very common. Even in the modern business society where information technology is advancing by leaps and bounds, technology can easily create different urban environments. In addition to achieving innovation, it also enhances the commonality and similarity between cities. However, urban culture, urban area, and urban activities are different, and the urban characters are also diverse. Urban space has specificity on the basis of similar basic requirements. Then, the diversified characteristics brought by the public art’s intervention in urban space and its integration into the environment correspond to it, and become a magic weapon to show the city’s personality. The integrated development of urban environment and public art provides artists and designers with established places to exert their talents. Using art to shape space and show the new style of urban design is not only a pursuit of individuality but also to meet the appeal of art popularization.


### 3.2. Wireless Sensor Data Fusion

Wireless sensor networks have a finite volume of node energy, and decreasing the volume of data transmitted can effectively limit power usage [13]. Its plane structure is shown in Figure 1. Each sensor node can use its own data processing and data storage capabilities to first fuse the collected data. The purpose of energy saving can be achieved by reducing the amount of transmitted data by filtering noise and eliminating redundant information.Figure 1
Wireless sensor network plane structure diagram.Data fusion refers to analyzing, estimating, and comprehensively processing several observational information data obtained in time series under certain algorithm criteria. Information processing technology that can combine data that is more effective and more in line with user needs. It was first used in the military field. By collecting various sensor information distributed on the battlefield, we synthesize, filter, correlate, and synthesize the target data of interest, in order to assist people to make a complete and timely situation and threat assessment of the battlefield environment. This is a high-precision, high-probability acquisition of real-time battlefield information and real-time threat assessment. In order to successfully implement a tactical plan, correct strategic decision-making and correct command of combat forces are extremely important.The application of data fusion method in wireless sensor network is obviously different from that in traditional multisensor network. The traditional sensor data fusion technology integrates, evaluates, and judges various attributes in the information collected by the node so that the fusion result can describe the state of the corresponding object more accurately. An important purpose of data fusion in wireless sensor networks is to eliminate data redundancy in order to save energy, prolong system life cycle, and simplify data to reduce data traffic. The calculation model is shown in Figure2.Figure 2
Data fusion functional model diagram.The classification of wireless sensor data fusion is roughly divided into three categories, as shown in Table2.Table 2
Wireless sensor data fusion classification.
SequenceFusion levelAmount of dataInformation lossReal timeAbstract precisionFault toleranceDegree of fusion1Data layerLargeSmallPoorHighPoorLow2Feature layerMediumMediumFairMediumFairMedium3Decision layerSmallLargeGoodLowGoodHighData layer: data layer data fusion is to perform fusion calculation on the directly collected data from nodes. The data are evaluated and calculated without any processing on the information from multiple places, and the process is shown in Figure3. This degree of fusion is only related to the type of data received, not to application requirements and functionality. Due to the large amount of collected data and many of the same components, the fusion calculation and analysis amount of this method is large, and it is listed as the lowest level of fusion. The advantage of this type of fusion is that the result retains the original information, the information with its own small features that other fusion methods do not have. But at the same time, there will be some disadvantages such as low degree of fusion of results, large workload of the processor, and poor time correlation.Figure 3
Data layer data fusion legend.Feature layer: feature layer data fusion refers to extracting feature vectors that can reflect environmental attributes from each sensor data and then merging them. The key to feature layer data fusion is to extract the information with a large amount of information in the data that is useful to users. To filter redundant and useless information, it is even necessary to make trade-offs for data with a small amount of information [14]. The amount of computation and data fusion is medium among the three fusions, and the application range is wide. A schematic diagram of the feature-level fusion process is shown in Figure 4. Feature layer data fusion realizes the compression of information, further reduces the amount of transmitted data, and is beneficial to the real-time nature of information. The feature vector extracted by the fusion algorithm more directly reflects the current state of the environment, which can provide an important basis for decision analysis.Figure 4
Feature layer data fusion legend.Decision-making level: decision-making level data fusion refers to the process of classifying and judging the state of the monitoring environment by relying on the feature information generated by feature-level data fusion, and obtaining decision-making information. In cluster-based wireless sensor networks, the cluster head usually makes decisions on the environmental state within the coverage area of the cluster according to the collected data. Therefore, the decision-level data fusion must be based on the decision-making needs provided by the user, using the various characteristic information of the monitoring environment extracted by the feature-level data fusion, and using an appropriate fusion algorithm to achieve. A graphical depiction of the decision-level integration process for transferring decision information to the sink is provided in Figure5. The advantages of data fusion at the decision level are as follows: the amount of data fusion results is small, so less energy is consumed in the transmission process. Important information can effectively reflect the environment. When some sensor data have large errors or disturbances, the system can still obtain correct results after fusion and has strong fault tolerance and high flexibility.Figure 5
Decision layer data fusion legend.Many mathematical models are used in data fusion algorithms. We assume that there aren sensors in different orientations to measure related parameters simultaneously at time t, and the sensor sequence can be expressed as follows [15]:(1)St=S1t,S2t,…,Snt.Then,(2)Sit=X+ηit,i=1,2,n.In formula (2), Sit is the observed voltage level of the sensor Sit at time t, while X is the actual level. ηit is the transducer signal resistance Sit at time t. The a priori data Eηit and Dηit are unavailable.We document the collected samples from timet1 to tm, respectively, and the sampled parameter grid is as follows:(3)D=s1t1s1t2⋯s1tms2t1s2t2⋯s2tm⋮⋮⋱⋮snt1⋯⋯sntm.Individual items in matricesD indicate the measurements of a sensor at a given time. The pillars from the matrices indicate the measurements of the transducers’ serial for the corresponding moment in time. The rows in the matrix represent the sequence of sampled values over time for the same sensor.In this paper, the data integration algorithms examined are predicated on data trains occurring at the identical time and without regard to temporal relevance. Thus, the models for data fusion utilized by this category of data convergence methods are fairly basic and are represented as follows:(4)D=s1,s2,…,sn.SequenceD represents a sequence of sampled data for parameter X by the sensor sequence at a certain time. This kind of continuous formulation omits the template arguments. This is because the algorithm does not involve temporal dependencies. This expression is convenient for taking values and is more conducive to the treatment and calculation of figures by this category of operators.The resulting values obtained from the sensors are influenced to a greater or lesser extent by noise, so the recorded data vary. The effect of noise can be large or small, and these variables can contribute to large or small variations between the data. To obtain a quantitative indication of the size of the discrepancy between the data, the absolute distance is used to quantify the variations. The absolute distance,disij, is as follows:(5)disij=si−sj.Absolute distancedisij is described as a dimension that expresses the variance between two data. Intuitively, it could be thought of as the separation of two numerical figures on a string of digits, distance is a non-negative concept, and is therefore expressed as an absolute value.For the purpose of gauging the contribution of a data to the blending experience, the principle of a fusion density feature has been adopted. The fusion dimension feature can be presented as follows:(6)cij=expR⋅disij.Among them,R is a ceteris paribus function, and the convergence feature represents the degree of convergence of the si value compared with the sj value. When the immediate separation exists between the two, it suggests that the si value is less converged relative to the sj value and its convergence is low.Throughout the blending experience, the convergence degree of a data is supposed to be evaluated in conjunction with the complete spectrum of sampled segmentsD to provide a more unbiased and efficient representation of its features. For this purpose, a convergence degree matrix has been imported to allow for easier overall evaluation and profiling. The convergence degree matrix can be denoted as follows:(7)C=1c12⋯c1mc211⋯c2m⋮⋮⋱⋮cm1cm2⋯1.Elementcij in the matrix represents the degree of fusion of data si relative to data sj in sequence D.For the sampled data seriesD, a weighting factor is defined to measure the magnitude of each individual datum’s effects on the eventual convergence result. qi denotes the weighting factor si for the data. Then,(8)q1+q2+⋯+qn=1.The parameter of gravity can be considered in a limited meaning as the output of the convergence method, and the final expression of the fusion result is as follows:(9)result=q1×s1+q2×s2+⋯+qn×sn.Because of the discrepancy and emergence of noise, the magnitude of deviation from the true value varies from measurement to measurement. Usually, the transducers are given a set, defined suspension period. Depending on the allocation of the time spots subject to sampling, the signal chain of the sensorsi from time t1 to time tn is as follows:(10)Si=Si1,Si2,…,Sin.Assuming that there are nodes in the wireless sensor network measuring variables in identical situations, the survey information can be obtained from the grid as follows:(11)B=S11S12⋯S1nS21S22⋯S2n⋮⋮⋱⋮Sm1Sm2⋯Smn.However, in some cases, the measured position of the transducer junction at the instant does not bear any relation to the recorded value at the preceding instant. The measured quantities at this point can be represented as a sequence:(12)Yt=S1,S2,…,Sn.Elementsi in sequence Yt represents the sampled data of sensor Si at time t.LetX be the true value of the sampled data at time t; then, there are(13)si=X+vi,where vi in formula (13) represents the measurement noise of sensor Si at time t. Prior knowledge Evi and Dvi are both unknown.In data fusion theory, we often use fuzzy sets to represent the concepts of distance and sticking progress, as shown in Figure6.Figure 6
Convex fuzzy set legend.The maximum and minimum paste progress is expressed as follows:(14)σA,B=∑i=1nAμi∧Bμi∑i=1nAμi∨Bμi.The arithmetic mean minimum postprogress is expressed as follows:(15)σA,B=∑i=1nAμi∧Bμi1/2∑i=1nAμi+Bμi.The geometric mean minimum sticking progress is expressed as follows:(16)σA,B=∑i=1nAμi∧Bμi∑i=1nAμiBμi.The index sticking progress is expressed as follows:(17)σA,B=1eA−B.Confidence is applied to gauge the closeness in time of the measurements of the active junction to the measurements of other journals, hence the effectiveness of the figures. The confidence scale feature is founded on the notions of greatest and least intimacy in relation to fuzzy statistics. The confidence scale ofsi and sj in time can be denoted as follows:(18)sijt=minsi,sjmaxsi,sj1≤i,j≤n.Then, the confidence matrix can be expressed as follows:(19)Snt=S11tS12t⋯S1ntS21tS22t⋯S2nt⋮⋮⋱⋮Sn1tSn2t⋯Snnt.Thei-th line of credentialed mean is expressed as follows:(20)rit=∑j=1nsij−siin−1.


## 3.1. Theory of Public Art and Urban Environment Design

The birth of public art is developed on the basis of the construction of the public domain, so it also has certain characteristics to some extent. The word public domain first appeared in Germany, and its definition is also translated into English according to the word public open in German, and it has been gradually passed down to this day. We turn a place that is free and open and allows multiple people to share and participate as a public space, and public art is the cultural and artistic creation in this public space. In the process of social development, the object of public art has always been the entire social group. In its creation, it will consider a variety of social factors such as race, ecology, and economy. And then, we use an artistic perspective and method to characterize the inextricable relationships among them. Therefore, public art can be regarded as an important symbol of the development of human art and culture.Throughout the development process of human culture, on the basis of the history and characteristics of public art, it is the theme of this paper to explore the relationship between public art and urban environment, and to deeply analyze the development of urban appearance and artistic connotation.As a very special space, the city is closely constructed without losing rhythm and is mainly used for the dissemination and preservation of human civilization. The development of public art after the 1980s can be said to be a process in which works of art gradually embrace the public and move toward environmental art. Re-examining its development process, we can clearly see that public art is closely related to urban development in various periods, and we can also see that contemporary public art gradually pays attention to the life of citizens and the urban environment in the process of growth. We call the space that can be seen visually in the urban environment as the tangible environment, and the main forms are shown in Table1. Judging by the property of the open space, most of them belong to the public space of the city. Through visual feedback, these tangible urban environments usually use nonverbal expressions to more directly affect people’s visual system, giving people’s consciousness and thinking hints and enlightenment.Table 1
Categories of public spaces in cities.
ScoreSequenceClassificationTangible space in the urban environment1Squares2Buildings3Sculptures4Gardens5Green spaces6Public facilitiesAs the main artistic creation in urban public space, public art is bound to be restricted and influenced by the environment. Public art decorates public space, and public space highlights public art. If every piece of public art is attached to the urban public space, then the value of public art depends on the degree of its integration with the real environment. On the other hand, it depends on whether public art meets the functional needs of the public space in the city where it is located. That is to say, contemporary public art with hugely different forms of expression in different eras is to meet the inner needs of the city, which covers politics, economy, culture, and people.The urban environment of each era is the epitome of human civilization in this era. As a very special cultural phenomenon, public art plays a particularly outstanding and important role in the development of contemporary urban and environmental art. It reflects the personality of the times in the process of urban development. After the 1950s, modernism went from prosperity to decline, and in the 1950s and 1960s, the postmodernist thought gradually matured, which had an impact on the idea of modernism. Until the 1960s, postmodern thought became a popular word in the world. Postmodernity has a distinctly reflective character and radical modernity, which is defined as an attitude, a way of thinking and feeling. Since then, modernity has entered a period of reflection. Then, with the postmodern movement and the social changes involved in modernity issues, art and culture began to leave the museum and seek the combination of art and environment in a wider space.On the one hand, this is a serious challenge to modernism, and that is, where are the true boundaries of art? Originally, this boundary has always been defended by modernists. On the other hand, it breaks the inner boundaries of art. Modernism distinguishes between art and nonart, aesthetic and everyday, and elite and mass. Although the self-discipline of art is maintained, it also greatly limits the social function of art. Postmodernism resolves these divisions of modernism, and art shows significant postmodernism characteristics with stronger tension. The first emphasizes the coordination with the environment, the second does not oppose decoration and uses a large number of decorations, and the third is usually symbolic or metaphorical. As the most vibrant part of contemporary art, public art casts aside the constraints of the original modernism, absorbs various design concepts, and presents a kaleidoscope of rich forms.Due to the characteristics of postmodernism focusing on decoration and integration with the environment, it is destined that the connection between public art and urban public space will be closer. At the same time, in the architectural field of urban space, public buildings are no longer just functional spaces, but are replaced by individualized and complex styles that integrate multiple elements, and are endowed with more cultural significance. At this time, the relationship between public art and architecture, which is an important part of urban design civilization, has also changed, and urban environmental design and public art have been blended. This is a manifestation of the functionalization of public art and the increasing emphasis on decoration and integration with the surrounding environment in the design of the urban environment itself. It is the inherent requirement of the development of urbanization to the stage of pursuing urban spiritual civilization.The positive impact of the current integrated development of public art and the environment on the city is reflected in the highlighting of the city’s individuality. In the 1950s, the modernist urban architectural style was popular and gradually reached its peak. The similarity of urban buildings is extremely high, the pursuit of functions and simple shapes, resulting in the same urban style; thousands of cities are one-sided; cities have no personality; and the buildings have no characteristics. This phenomenon is very common. Even in the modern business society where information technology is advancing by leaps and bounds, technology can easily create different urban environments. In addition to achieving innovation, it also enhances the commonality and similarity between cities. However, urban culture, urban area, and urban activities are different, and the urban characters are also diverse. Urban space has specificity on the basis of similar basic requirements. Then, the diversified characteristics brought by the public art’s intervention in urban space and its integration into the environment correspond to it, and become a magic weapon to show the city’s personality. The integrated development of urban environment and public art provides artists and designers with established places to exert their talents. Using art to shape space and show the new style of urban design is not only a pursuit of individuality but also to meet the appeal of art popularization.


## 3.2. Wireless Sensor Data Fusion

Wireless sensor networks have a finite volume of node energy, and decreasing the volume of data transmitted can effectively limit power usage [13]. Its plane structure is shown in Figure 1. Each sensor node can use its own data processing and data storage capabilities to first fuse the collected data. The purpose of energy saving can be achieved by reducing the amount of transmitted data by filtering noise and eliminating redundant information.Figure 1
Wireless sensor network plane structure diagram.Data fusion refers to analyzing, estimating, and comprehensively processing several observational information data obtained in time series under certain algorithm criteria. Information processing technology that can combine data that is more effective and more in line with user needs. It was first used in the military field. By collecting various sensor information distributed on the battlefield, we synthesize, filter, correlate, and synthesize the target data of interest, in order to assist people to make a complete and timely situation and threat assessment of the battlefield environment. This is a high-precision, high-probability acquisition of real-time battlefield information and real-time threat assessment. In order to successfully implement a tactical plan, correct strategic decision-making and correct command of combat forces are extremely important.The application of data fusion method in wireless sensor network is obviously different from that in traditional multisensor network. The traditional sensor data fusion technology integrates, evaluates, and judges various attributes in the information collected by the node so that the fusion result can describe the state of the corresponding object more accurately. An important purpose of data fusion in wireless sensor networks is to eliminate data redundancy in order to save energy, prolong system life cycle, and simplify data to reduce data traffic. The calculation model is shown in Figure2.Figure 2
Data fusion functional model diagram.The classification of wireless sensor data fusion is roughly divided into three categories, as shown in Table2.Table 2
Wireless sensor data fusion classification.
SequenceFusion levelAmount of dataInformation lossReal timeAbstract precisionFault toleranceDegree of fusion1Data layerLargeSmallPoorHighPoorLow2Feature layerMediumMediumFairMediumFairMedium3Decision layerSmallLargeGoodLowGoodHighData layer: data layer data fusion is to perform fusion calculation on the directly collected data from nodes. The data are evaluated and calculated without any processing on the information from multiple places, and the process is shown in Figure3. This degree of fusion is only related to the type of data received, not to application requirements and functionality. Due to the large amount of collected data and many of the same components, the fusion calculation and analysis amount of this method is large, and it is listed as the lowest level of fusion. The advantage of this type of fusion is that the result retains the original information, the information with its own small features that other fusion methods do not have. But at the same time, there will be some disadvantages such as low degree of fusion of results, large workload of the processor, and poor time correlation.Figure 3
Data layer data fusion legend.Feature layer: feature layer data fusion refers to extracting feature vectors that can reflect environmental attributes from each sensor data and then merging them. The key to feature layer data fusion is to extract the information with a large amount of information in the data that is useful to users. To filter redundant and useless information, it is even necessary to make trade-offs for data with a small amount of information [14]. The amount of computation and data fusion is medium among the three fusions, and the application range is wide. A schematic diagram of the feature-level fusion process is shown in Figure 4. Feature layer data fusion realizes the compression of information, further reduces the amount of transmitted data, and is beneficial to the real-time nature of information. The feature vector extracted by the fusion algorithm more directly reflects the current state of the environment, which can provide an important basis for decision analysis.Figure 4
Feature layer data fusion legend.Decision-making level: decision-making level data fusion refers to the process of classifying and judging the state of the monitoring environment by relying on the feature information generated by feature-level data fusion, and obtaining decision-making information. In cluster-based wireless sensor networks, the cluster head usually makes decisions on the environmental state within the coverage area of the cluster according to the collected data. Therefore, the decision-level data fusion must be based on the decision-making needs provided by the user, using the various characteristic information of the monitoring environment extracted by the feature-level data fusion, and using an appropriate fusion algorithm to achieve. A graphical depiction of the decision-level integration process for transferring decision information to the sink is provided in Figure5. The advantages of data fusion at the decision level are as follows: the amount of data fusion results is small, so less energy is consumed in the transmission process. Important information can effectively reflect the environment. When some sensor data have large errors or disturbances, the system can still obtain correct results after fusion and has strong fault tolerance and high flexibility.Figure 5
Decision layer data fusion legend.Many mathematical models are used in data fusion algorithms. We assume that there aren sensors in different orientations to measure related parameters simultaneously at time t, and the sensor sequence can be expressed as follows [15]:(1)St=S1t,S2t,…,Snt.Then,(2)Sit=X+ηit,i=1,2,n.In formula (2), Sit is the observed voltage level of the sensor Sit at time t, while X is the actual level. ηit is the transducer signal resistance Sit at time t. The a priori data Eηit and Dηit are unavailable.We document the collected samples from timet1 to tm, respectively, and the sampled parameter grid is as follows:(3)D=s1t1s1t2⋯s1tms2t1s2t2⋯s2tm⋮⋮⋱⋮snt1⋯⋯sntm.Individual items in matricesD indicate the measurements of a sensor at a given time. The pillars from the matrices indicate the measurements of the transducers’ serial for the corresponding moment in time. The rows in the matrix represent the sequence of sampled values over time for the same sensor.In this paper, the data integration algorithms examined are predicated on data trains occurring at the identical time and without regard to temporal relevance. Thus, the models for data fusion utilized by this category of data convergence methods are fairly basic and are represented as follows:(4)D=s1,s2,…,sn.SequenceD represents a sequence of sampled data for parameter X by the sensor sequence at a certain time. This kind of continuous formulation omits the template arguments. This is because the algorithm does not involve temporal dependencies. This expression is convenient for taking values and is more conducive to the treatment and calculation of figures by this category of operators.The resulting values obtained from the sensors are influenced to a greater or lesser extent by noise, so the recorded data vary. The effect of noise can be large or small, and these variables can contribute to large or small variations between the data. To obtain a quantitative indication of the size of the discrepancy between the data, the absolute distance is used to quantify the variations. The absolute distance,disij, is as follows:(5)disij=si−sj.Absolute distancedisij is described as a dimension that expresses the variance between two data. Intuitively, it could be thought of as the separation of two numerical figures on a string of digits, distance is a non-negative concept, and is therefore expressed as an absolute value.For the purpose of gauging the contribution of a data to the blending experience, the principle of a fusion density feature has been adopted. The fusion dimension feature can be presented as follows:(6)cij=expR⋅disij.Among them,R is a ceteris paribus function, and the convergence feature represents the degree of convergence of the si value compared with the sj value. When the immediate separation exists between the two, it suggests that the si value is less converged relative to the sj value and its convergence is low.Throughout the blending experience, the convergence degree of a data is supposed to be evaluated in conjunction with the complete spectrum of sampled segmentsD to provide a more unbiased and efficient representation of its features. For this purpose, a convergence degree matrix has been imported to allow for easier overall evaluation and profiling. The convergence degree matrix can be denoted as follows:(7)C=1c12⋯c1mc211⋯c2m⋮⋮⋱⋮cm1cm2⋯1.Elementcij in the matrix represents the degree of fusion of data si relative to data sj in sequence D.For the sampled data seriesD, a weighting factor is defined to measure the magnitude of each individual datum’s effects on the eventual convergence result. qi denotes the weighting factor si for the data. Then,(8)q1+q2+⋯+qn=1.The parameter of gravity can be considered in a limited meaning as the output of the convergence method, and the final expression of the fusion result is as follows:(9)result=q1×s1+q2×s2+⋯+qn×sn.Because of the discrepancy and emergence of noise, the magnitude of deviation from the true value varies from measurement to measurement. Usually, the transducers are given a set, defined suspension period. Depending on the allocation of the time spots subject to sampling, the signal chain of the sensorsi from time t1 to time tn is as follows:(10)Si=Si1,Si2,…,Sin.Assuming that there are nodes in the wireless sensor network measuring variables in identical situations, the survey information can be obtained from the grid as follows:(11)B=S11S12⋯S1nS21S22⋯S2n⋮⋮⋱⋮Sm1Sm2⋯Smn.However, in some cases, the measured position of the transducer junction at the instant does not bear any relation to the recorded value at the preceding instant. The measured quantities at this point can be represented as a sequence:(12)Yt=S1,S2,…,Sn.Elementsi in sequence Yt represents the sampled data of sensor Si at time t.LetX be the true value of the sampled data at time t; then, there are(13)si=X+vi,where vi in formula (13) represents the measurement noise of sensor Si at time t. Prior knowledge Evi and Dvi are both unknown.In data fusion theory, we often use fuzzy sets to represent the concepts of distance and sticking progress, as shown in Figure6.Figure 6
Convex fuzzy set legend.The maximum and minimum paste progress is expressed as follows:(14)σA,B=∑i=1nAμi∧Bμi∑i=1nAμi∨Bμi.The arithmetic mean minimum postprogress is expressed as follows:(15)σA,B=∑i=1nAμi∧Bμi1/2∑i=1nAμi+Bμi.The geometric mean minimum sticking progress is expressed as follows:(16)σA,B=∑i=1nAμi∧Bμi∑i=1nAμiBμi.The index sticking progress is expressed as follows:(17)σA,B=1eA−B.Confidence is applied to gauge the closeness in time of the measurements of the active junction to the measurements of other journals, hence the effectiveness of the figures. The confidence scale feature is founded on the notions of greatest and least intimacy in relation to fuzzy statistics. The confidence scale ofsi and sj in time can be denoted as follows:(18)sijt=minsi,sjmaxsi,sj1≤i,j≤n.Then, the confidence matrix can be expressed as follows:(19)Snt=S11tS12t⋯S1ntS21tS22t⋯S2nt⋮⋮⋱⋮Sn1tSn2t⋯Snnt.Thei-th line of credentialed mean is expressed as follows:(20)rit=∑j=1nsij−siin−1.


## 4. Experimental Results and Analysis

The integration development analysis experiment of public art and urban environment design in this paper uses wireless sensors to collect public art and urban environment information in two cities A and B in a province from 2017 to 2021. The province is located in the coastal area, with developed economy and trade, and each city has a long history and culture. Its basic information is shown in Table3. In this paper, the collection results are used as reference values. City A uses data fusion technology for integrated development analysis, and city B adopts traditional methods for integrated development analysis.Table 3
Experimental province and city information.
SequenceCity informationNumerical value1Geographical locationSoutheast coast2ClimateSubtropical monsoon climate3Population39.73 million4Area124,000 square kilometers5Gross product4239.500 billionBasic information on public art and urban environment design: the basic information of public art and urban environment design collected in this paper mainly starts from the structure of the whole city. From the four perspectives of the interaction and publicity of public art and the functionality and creativity of urban environment design, we will understand the development status of urban public spheres, as shown in Figures7 and 8.Figure 7
City public art information: (a) public art interactive information; (b) public art publicity information.
(a)(b)Figure 8
Urban environment design information: (a) functional information for urban environment design; (b) creative information for urban environment design.
(a)(b)From Figure7, it can be seen that the interaction and publicity of public art in the two cities A and B are not ideally developed. And in the process from 2017 to 2021, the interactive growth of public art is slow, the average of public art interactivity in city A is only 72.36%, and that in city B is 72.70%. In the public characteristics of public art, the average value of city A is 78.18%, and that of city B is 69.36%, which is closely related to the economic development of the two cities. The average economic production of city A ranks high in the whole province, and its social development is relatively advanced, which promotes the construction of the urban public realm. Therefore, in the characteristics of publicity, city A is ahead of city B. However, from the perspective of the overall development situation, the public art in city A and city B is relatively backward and needs to continue to be innovated.It can be seen from Figure8 that the functional development of urban environmental design in cities A and B is generally good. Because the natural landscape resources of the city are very rich, coupled with the geographical advantages of the coast, the water area is relatively large, and the ecological atmosphere is very harmonious, and the urban environment is more functional. But there is still room for improvement in terms of creativity. The urban environment not only relies on natural resources but also needs to be planned and adjusted, and different arts and cultures must be integrated to create a style and connotation that is completely different from other cities.Integrated development: before the fusion development analysis, this paper firstly optimizes the collected data of public art and urban environment design, and then performs fusion calculation. The fusion effect under the two methods is shown in Figure9.Figure 9
Fusion results relative error and absolute error: (a) the absolute error of the fusion result; (b) the relative error of the fusion result.
(a)(b)It can be seen from Figure9 that in the fusion results of multiple tests, the absolute error of city A using the data fusion method for data analysis and calculation is only 1.035, the highest is 2.031, and the relative error values are 2.03% and 3.97%, respectively. The absolute error value of city B using traditional methods for data analysis and calculation reached 1.553, the highest value was 3.716, and the relative error values were 3.48% and 4.99%, respectively. This shows that in the integrated development of public art and urban environment design, the data fusion method can integrate various influencing factors, as well as measuring and quantifying the actual advantages and disadvantages of different elements; on the basis of effective feedback of important information, the public art and urban environment design are well integrated.It can be seen from Figure10 that in the fusion results of public art and urban environment design in city A, the average degree of association fusion is 84.08%, and the average degree of balanced fusion is 80.60%. In the fusion results of public art and urban environment design in city B, the average degree of association fusion is 75.04%, and the average degree of balanced fusion is 75.91%. Based on these data, we can see that wireless sensors combine the development history of public art in city A with the urban environment design, and the city art and culture are well integrated in the whole public realm environment. It makes the urban environment better than city B in terms of relevance and balance, which is something that traditional methods cannot do. In today’s urban construction, the integration of public art and urban environment design in city A can effectively meet the dual development of economy and culture.Figure 10
Result of the fusion degree of public art and urban environment design: (a) the fusion result of cityA’s public art and urban environment design; (b) the fusion result of city B’s public art and urban environment design.
(a)(b)


## 5. Conclusions

Whether public art and urban environmental design can achieve a good integration and development determines the subsequent development direction of the entire city. In order to improve the efficiency and accuracy of data analysis, this paper analyzes the fusion development of public art and urban environment design using the data fusion method in wireless sensors, and achieves an ideal fusion effect. In this paper, although the data fusion method based on wireless sensor has carried out in-depth research on the fusion development of public art and urban environment design, there remain many weaknesses. The present paper does not go far enough in terms of detail and range of research. In the course of this study, the choices and obtaining of laboratory materials were performed under conditions that were strictly ideally suited. Its completeness and effectiveness are not enough, and some interference factors involved in the test process are not taken into account. The scholarly standard of research is also restricted, and the application of science and technology in urban construction is still in its infancy. In the future, we will continue to improve the quality of our research work by analyzing from more perspectives on the basis of available knowledge and proficiency.



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*Source: 3301100-2022-08-10.xml*