# Computer Dynamic Simulation Design of Ecological Packaging of New Energy Products Based on Internet of Things Technology

Authors: Jinna Zhang
Journal: International Transactions on Electrical Energy Systems
 (2022)

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## Abstract

The application of Internet of Things (IoT) technology has realized the transformation of people’s production and lifestyle, and also promoted the transformation of education and teaching mode. At present, the application of informatization in the field of product packaging is increasing. Advanced methods and techniques for visual presentation using virtual reality technology. This study has aimed to realize the process optimization of new energy product packaging design in the context of the Internet of Things to promote the ecological development of the product packaging industry. This study has proposed to use the IoT technology and virtual reality technology to know the integration of new energy product packaging and virtual simulation experiments, which is helpful to analyze and solve the objective system imbalance and ecological imbalance in the product packaging system. Drawing on the principles and laws of the IoT and virtual reality technology, the dynamic simulation process of ecological packaging is constructed and optimized to realize the “ecologicalization” of the packaging field. In a study of RFID tag algorithms in the context of IoT, the least data is transmitted atm = 4, which saves an average of 48 bits per identified tag compared to m = 6. Due to the number of queries and the amount of data transferred, the MICT algorithm chooses m = 4 when identifying 96-bit tags. In terms of recognition efficiency, the MICT algorithm achieves about 74%. Therefore, the dynamic simulation design of product packaging is very important at present.


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## Body

## 1. Introduction

With the maturity of mobile Internet technology and the advancement of wireless data transmission technology, wireless terminals have gradually become an emerging carrier of online shopping, from the previous online shopping that was purely computerized, and China has therefore entered the era of “handheld shopping.” For packaging, the changes and development of these times imply that people’s living conditions and the requirements for the quality of life are getting higher and higher. The traditional packaging used to protect products, facilitate transportation and promote sales can no longer fully meet people’s growing demand. With new demand, the market needs more perfect and intelligent packaging to adapt to this change. More than that, the development of the IoT has brought new opportunities to packaging, and cloud services and big data have provided more effective implementation methods for the selection and design of the packaging. Virtual reality technology and augmented reality technology have gradually penetrated into various fields because of their great advantages in user interaction experience. This diversified digital environment prompts packaging to change accordingly. How to reasonably apply the research results of these emerging technologies to packaging design to adapt to new consumption patterns and to be in line with future production and lifestyles is becoming more and more important. In the foreseeable future, intelligent packaging based on new technologies such as the Internet, IoT, virtual reality technology, and artificial intelligence will become one of the major trends in packaging development.By studying the relevant theories of digital intelligent packaging, the current situation of scattered and unsystematic research on digital intelligent packaging theory can be solved, and the intelligent packaging system can be further improved. It supplements the current theoretical research on the whole system of intelligent packaging and provides corresponding teaching theoretical sources. The difference between traditional packaging and new energy intelligent packaging is compared, the application cases of European digital information technology in packaging are analyzed, and the new energy intelligent packaging design method is summarized, which can provide theoretical reference for packaging designers and packaging practitioners. It makes theoretical preparations for the smooth entry of digital intelligent packaging into the market, and helps designers and packaging practitioners to better design and manufacture digital intelligent packaging. The packaging has been improved in terms of safety, environmental protection, economy, and humanization to meet people’s growing new packaging needs.Product packaging design has been one of the research topics of many scholars since ancient times. Among others, Guidoni has suggested that the growing popularity and sales of traditional packaging formats are placing a heavy burden on leading coffee producers, risking outright legislative bans and consumer boycotts [1]. Abunar and Alam have aimed to explore and identify Saudi shopper perceptions of sustainable (green) product packaging in order to maintain a sustainable green environment [2]. Guo et al. have proposed that the issue of garbage recycling for express parcels has aroused extensive discussion and attention with the increasing popularity of the concept of ecological civilization [3]. Liu and Wuhas explored the relationship between the VBN value belief criteria and the intentions used to design sustainable packaging [4]. Vambol et al. have already proposed that in the third stage of “storage and packaging,” it is necessary to take into account the specific characteristics, volatility, solubility, interaction with air and water, etc. of new energy packaging materials [5]. However, due to the objective problems of unsupported equipment and insufficient data sources, the above packaging technologies are still in a theoretical state and cannot be practiced in depth.The use of the IoT and virtual reality technology to carry out dynamic simulation design of product packaging is one of the popular fields. Among them, Shaikh et al. have proposed over the years that plastics are manufactured and used in different fields of packaging applications. With the development of the food industry, the demand for packaging materials is also increasing [6]. Krzyk and Drev have already suggested that the existing waste packaging treatment system in Slovenia has several disadvantages, as well as some advantages, relative to the system prevalent in developed countries. The main disadvantage is the lack of financial incentives to properly dispose of waste packaging, especially when they relate to individuals and households [7]. Lu and Shorey have already pointed to the growing interest in glass materials as packaging materials. Glass and its material properties offer many opportunities for advanced packaging applications. As an insulator, glass is very suitable because of its low electrical losses, especially at high frequencies [8]. New requirements have emerged in Shorey et al. electronic packaging. The growing demand for mobile communication and sensor solutions addressing the IoT (IoT) presents interesting new challenges [9]. Kawamura et al. has researched a new modeling approach for system packaging design. It is found that the information on system design can be divided into four parts: product system, design space, design algorithm, and design environment [10]. However, their research pays more attention to the process design of product packaging and does not integrate virtual reality technology into the design process well.The innovations of this study are: (1) The complete concept of digital intelligent packaging is perfected and classified reasonably. The current scattered research status of the application of digital information technology in packaging is solved, the theoretical framework of digital intelligent packaging is improved, and the theoretical source for future intelligent packaging education is provided. (2) Combined with the current successful design cases in China and Europe, the design methods of digital intelligent packaging are analyzed and summarized, providing theoretical sources and design ideas for packaging design practitioners. (3) The key technologies and application methods of digital intelligent packaging applications are summarized, and the application fields of digital intelligent packaging are explored and explored to provide direction for the application of digital intelligent packaging in the market. (4) The research focus of this study is the complete definition and reasonable classification of the concept of new energy intelligent packaging, content innovation, and construction of a perfect new energy intelligent theoretical system framework. According to the relevant design cases, the feasible method models of new energy intelligent packaging design are summarized.


## 2. New Energy Product Packaging Design Based on Virtual Reality Technology

### 2.1. Design of Intelligent Packaging System

With the prosperity and development of the Internet in recent years, the emergence of more and more new technologies has brought a huge impact on the packaging industry, and the functions of packaging have also expanded [11]. Its classification architecture is shown in Figure 1:Figure 1
The new energy product ecological report supervisor classification system structure diagram.As can be seen from Figure1, in order to meet the needs of users in the new era, these new packaging forms have been able to achieve functions such as intelligent management and control, security, and anti-counterfeiting [12, 13]. Based on this, this study proposes the definition of digital intelligent packaging: digital intelligent packaging refers to the addition of emerging digital information technologies such as the IoT and VR/AR to packaging [14]. In this category form, there is a certain technical span between the two types of packaging, and there are also large differences in the way that various packaging types convey information.


### 2.2. Design of Product Packaging System

The foundation of packaging design is a professional basic course that combines theory and practice, science and art [15]. The purpose of this course is to cultivate students’ packaging design ability and master the exquisite artistic accomplishment and rich expression means of this discipline. It also keeps abreast of the changing economic pulse and the development trend of packaging design, and has the ability to independently apply design theory to packaging design, as shown in Figure 2.Figure 2
Basic system of packaging design.Each stage of system development studied in this study is shown in Figure3, which is divided into requirements analysis, system design, module development, testing, integrated deployment, operation and maintenance, and system evaluation.Figure 3
System design research flow chart.As can be seen from Figure3, the content design defines and divides the functions of each functional module to be displayed by the system according to the results of the requirement analysis and definition. The interface design has expounded the core idea and design concept of the system’s user-oriented interface design, and carried out the display of the user interface produced according to this theory.The organizational structure design is the organizational structure of the project files when the system is completed and delivered. According to the design of the modules and the entire framework, the framework core files, logic files, and data files are organized and organized in a well-organized and well-organized directory level and stored. Data prototyping is to carry out prototyping of various types of data used in this system, such as 3D model data, packaging style data, etc., in order to achieve maximum reuse and facilitate system function expansion.


### 2.3. Packaging System Database Design

According to the design of the above conceptual model, combined with the T-SQL syntax, the following table is naturally created. The field names and data types of these tables are listed in detail here. It is shown in Tables1–3.Table 1
User table.
NumberingField nameType of dataAllow emptyRemark1UserIDncharNoUser ID2UserNicknamencharYesUser’s nickname3UserTelncharNoContact details4UserMailAdressncharYesE-mail address5RegisterTimeDatetimeNoRegistration time6AdminIDncharNoRegistered administrator7PasswdncharNoLogin passwordTable 2
Administrator table.
NumberingField nameType of dataAllow emptyRemark1AdminIDncharNoAdmin ID2AdminNamecharNoname3AdminLevelIntNoPermission level4AdminTelncharNoContact details5PasswdNcNoLogin passwordTable 3
Project table.
NumberingField nameType of dataAllow emptyRemark1ProjectIDncharNoProject ID2ProjectNamencharNoTitle3ProjectCategoryIntNoProject type4ProjectStateIntNoProject status5ProjectStartTimeDatetimeNoStarting time6ProjectEndTimeDatetimeYesEnd time7UserIDncharNoUser ID8DesignerIDncharYesDesigner IDThe three tables are part of the database tables of the entire system, including the user table, the administrator table, and the project table.


### 2.4. 3D Modeling Algorithm Based on Virtual Reality Technology

After obtaining the general outline of the image, in order to reduce the computational complexity of 3D reconstruction and improve the similarity between the reconstructed shape and the image, the outline data can be slimmed down, and the outline area can be interpolated to form enough 2D processing points [16, 17]. The basic idea is to connect the first and last points of the processing curve with a straight line, find the distance between all intermediate points and the straight line, and find the maximum distance value dmax compared to the thinning threshold tl. If dmax < th, all midpoints are discarded. If dmax > th, use this point as the boundary, divide the curve into two parts, and repeat the above procedure for the two parts of the curve until all points have been processed. For the interpolation calculation of the image contour area, the uniform random interpolation method has been adopted in this study. The basic idea is to calculate the four vertices of the minimum circumscribed rectangle of the input contour point, and take two vectors in the horizontal and vertical directions:(1)Dh=p2−p1⟶,(2)Dv=p1−p0⟶.Their modulo are(3)dh=p2−p1⟶,(4)dv=p1−p0⟶.Therefore, the random points that fall within the smallest bounding rectangle are(5)pr=p0+Dhdh,Dvdv,pu,pu∈U0,dh,U0,dv.It is further determined whether the pointpr falls within the contour area. If it falls within the contour area, the point is retained and the number of points is increased by 1, otherwise it is discarded. The above process is repeated until the number of interpolation points satisfies the set condition.This study needs to establish a virtual camera coordinate system to realize the camera calibration method. The perspective conversion process of camera imaging is derived as follows. World coordinate system to camera coordinate system: This transformation is a rigid body transformation and only needs to apply the rotation matrixR and displacement matrix T to the 3D point in the world coordinate system:(6)XcYcZc=RXwYwZw+T.The transformation is a process of projective perspective transformation, and the pinhole imaging model can be used to describe the transformation from 3D coordinates to 2D coordinates [16]. The imaging process is to invert the actual image formed by the pinhole surface (camera coordinate system) between the image plane (image coordinate system) and the object point plane. Assuming that there is a point M in the camera coordinate system, the coordinates of the display point P in the undistorted ideal image coordinate system can be derived from the similarity of the triangles:(7)Zcf=Xcx=Ycy,f is the focal length, which can be sorted:(8)x=f∗XcZc,(9)y=f∗YcZc.Display plane coordinate system: The display plane coordinate system can be transformed into a pixel coordinate system by scaling and translation. Pixel coordinates can be described by the following expressions:(10)u=a∗x+cx,(11)v=β∗y+cy.It sorts out(12)u=afXcZc+cx,(13)v=β∗fYcZc.Among them, the units ofa and β are pixels/meter; fx and fy are the focal lengths in the x and y directions, in pixels; (cx, cy) is the center of the image, in pixels. In summary, the final form of the camera coordinate system to the pixel coordinate system can be written as:(14)Zc=uv1=fx0cx0fycy001.The relationship between a 3D point in the world coordinate system and a 2D point in the pixel coordinate system is:(15)sm˜=ARTM˜,(16)suv1=fx0cx0fycy001.The unit ofa and β is pixel/meter, fx,fy is the focal length in the x and y directions, and the unit is pixel; cx,cy is the center of the image, and the unit is pixel. In summary, the final form of the camera coordinate system to the pixel coordinate system can be written as:(17)Zcuv1=fx0cx0fycy001XcYcZc.The relationship between the three-dimensional pointM=X,Y,ZT in the world coordinate system and the two-dimensional point m=u,vT in the pixel coordinate system is(18)suv1=fx0c0fyc001r11r12t1r21r23t2r31r33t3.s is the scaling factor, A is the camera’s internal parameter matrix, [R T] is the camera’s external parameter matrix, to calibrate the camera in the virtual camera coordinate system. This article has assumed that the world coordinate system of the scene is a right-handed coordinate system, the y-axis is up, the positive z-axis is facing the screen outward, and the virtual camera of the scene is located at the origin of the world coordinate without rotation, then the world matrix of the camera can be represented as a unit matrix. The three-dimensional point cloud corresponding to the last two-dimensional image is projected in the xoy plane, and the point cloud is all outside the positive direction of the z-axis [18, 19]. According to the formula, the inverse perspective transformation of a point in the world is:(19)Mworld=Mscreen∗Mview∗Mprojection−1.Since it is an identity matrix, the formula can be simplified to:(20)Mworld=Mscreen∗Mprojection−1.This study has introduced the specific implementation of the key algorithm of 3D modeling, which can be used in the ecological packaging of new energy products to make shopping more convenient and fast for consumers.


## 2.1. Design of Intelligent Packaging System

With the prosperity and development of the Internet in recent years, the emergence of more and more new technologies has brought a huge impact on the packaging industry, and the functions of packaging have also expanded [11]. Its classification architecture is shown in Figure 1:Figure 1
The new energy product ecological report supervisor classification system structure diagram.As can be seen from Figure1, in order to meet the needs of users in the new era, these new packaging forms have been able to achieve functions such as intelligent management and control, security, and anti-counterfeiting [12, 13]. Based on this, this study proposes the definition of digital intelligent packaging: digital intelligent packaging refers to the addition of emerging digital information technologies such as the IoT and VR/AR to packaging [14]. In this category form, there is a certain technical span between the two types of packaging, and there are also large differences in the way that various packaging types convey information.


## 2.2. Design of Product Packaging System

The foundation of packaging design is a professional basic course that combines theory and practice, science and art [15]. The purpose of this course is to cultivate students’ packaging design ability and master the exquisite artistic accomplishment and rich expression means of this discipline. It also keeps abreast of the changing economic pulse and the development trend of packaging design, and has the ability to independently apply design theory to packaging design, as shown in Figure 2.Figure 2
Basic system of packaging design.Each stage of system development studied in this study is shown in Figure3, which is divided into requirements analysis, system design, module development, testing, integrated deployment, operation and maintenance, and system evaluation.Figure 3
System design research flow chart.As can be seen from Figure3, the content design defines and divides the functions of each functional module to be displayed by the system according to the results of the requirement analysis and definition. The interface design has expounded the core idea and design concept of the system’s user-oriented interface design, and carried out the display of the user interface produced according to this theory.The organizational structure design is the organizational structure of the project files when the system is completed and delivered. According to the design of the modules and the entire framework, the framework core files, logic files, and data files are organized and organized in a well-organized and well-organized directory level and stored. Data prototyping is to carry out prototyping of various types of data used in this system, such as 3D model data, packaging style data, etc., in order to achieve maximum reuse and facilitate system function expansion.


## 2.3. Packaging System Database Design

According to the design of the above conceptual model, combined with the T-SQL syntax, the following table is naturally created. The field names and data types of these tables are listed in detail here. It is shown in Tables1–3.Table 1
User table.
NumberingField nameType of dataAllow emptyRemark1UserIDncharNoUser ID2UserNicknamencharYesUser’s nickname3UserTelncharNoContact details4UserMailAdressncharYesE-mail address5RegisterTimeDatetimeNoRegistration time6AdminIDncharNoRegistered administrator7PasswdncharNoLogin passwordTable 2
Administrator table.
NumberingField nameType of dataAllow emptyRemark1AdminIDncharNoAdmin ID2AdminNamecharNoname3AdminLevelIntNoPermission level4AdminTelncharNoContact details5PasswdNcNoLogin passwordTable 3
Project table.
NumberingField nameType of dataAllow emptyRemark1ProjectIDncharNoProject ID2ProjectNamencharNoTitle3ProjectCategoryIntNoProject type4ProjectStateIntNoProject status5ProjectStartTimeDatetimeNoStarting time6ProjectEndTimeDatetimeYesEnd time7UserIDncharNoUser ID8DesignerIDncharYesDesigner IDThe three tables are part of the database tables of the entire system, including the user table, the administrator table, and the project table.


## 2.4. 3D Modeling Algorithm Based on Virtual Reality Technology

After obtaining the general outline of the image, in order to reduce the computational complexity of 3D reconstruction and improve the similarity between the reconstructed shape and the image, the outline data can be slimmed down, and the outline area can be interpolated to form enough 2D processing points [16, 17]. The basic idea is to connect the first and last points of the processing curve with a straight line, find the distance between all intermediate points and the straight line, and find the maximum distance value dmax compared to the thinning threshold tl. If dmax < th, all midpoints are discarded. If dmax > th, use this point as the boundary, divide the curve into two parts, and repeat the above procedure for the two parts of the curve until all points have been processed. For the interpolation calculation of the image contour area, the uniform random interpolation method has been adopted in this study. The basic idea is to calculate the four vertices of the minimum circumscribed rectangle of the input contour point, and take two vectors in the horizontal and vertical directions:(1)Dh=p2−p1⟶,(2)Dv=p1−p0⟶.Their modulo are(3)dh=p2−p1⟶,(4)dv=p1−p0⟶.Therefore, the random points that fall within the smallest bounding rectangle are(5)pr=p0+Dhdh,Dvdv,pu,pu∈U0,dh,U0,dv.It is further determined whether the pointpr falls within the contour area. If it falls within the contour area, the point is retained and the number of points is increased by 1, otherwise it is discarded. The above process is repeated until the number of interpolation points satisfies the set condition.This study needs to establish a virtual camera coordinate system to realize the camera calibration method. The perspective conversion process of camera imaging is derived as follows. World coordinate system to camera coordinate system: This transformation is a rigid body transformation and only needs to apply the rotation matrixR and displacement matrix T to the 3D point in the world coordinate system:(6)XcYcZc=RXwYwZw+T.The transformation is a process of projective perspective transformation, and the pinhole imaging model can be used to describe the transformation from 3D coordinates to 2D coordinates [16]. The imaging process is to invert the actual image formed by the pinhole surface (camera coordinate system) between the image plane (image coordinate system) and the object point plane. Assuming that there is a point M in the camera coordinate system, the coordinates of the display point P in the undistorted ideal image coordinate system can be derived from the similarity of the triangles:(7)Zcf=Xcx=Ycy,f is the focal length, which can be sorted:(8)x=f∗XcZc,(9)y=f∗YcZc.Display plane coordinate system: The display plane coordinate system can be transformed into a pixel coordinate system by scaling and translation. Pixel coordinates can be described by the following expressions:(10)u=a∗x+cx,(11)v=β∗y+cy.It sorts out(12)u=afXcZc+cx,(13)v=β∗fYcZc.Among them, the units ofa and β are pixels/meter; fx and fy are the focal lengths in the x and y directions, in pixels; (cx, cy) is the center of the image, in pixels. In summary, the final form of the camera coordinate system to the pixel coordinate system can be written as:(14)Zc=uv1=fx0cx0fycy001.The relationship between a 3D point in the world coordinate system and a 2D point in the pixel coordinate system is:(15)sm˜=ARTM˜,(16)suv1=fx0cx0fycy001.The unit ofa and β is pixel/meter, fx,fy is the focal length in the x and y directions, and the unit is pixel; cx,cy is the center of the image, and the unit is pixel. In summary, the final form of the camera coordinate system to the pixel coordinate system can be written as:(17)Zcuv1=fx0cx0fycy001XcYcZc.The relationship between the three-dimensional pointM=X,Y,ZT in the world coordinate system and the two-dimensional point m=u,vT in the pixel coordinate system is(18)suv1=fx0c0fyc001r11r12t1r21r23t2r31r33t3.s is the scaling factor, A is the camera’s internal parameter matrix, [R T] is the camera’s external parameter matrix, to calibrate the camera in the virtual camera coordinate system. This article has assumed that the world coordinate system of the scene is a right-handed coordinate system, the y-axis is up, the positive z-axis is facing the screen outward, and the virtual camera of the scene is located at the origin of the world coordinate without rotation, then the world matrix of the camera can be represented as a unit matrix. The three-dimensional point cloud corresponding to the last two-dimensional image is projected in the xoy plane, and the point cloud is all outside the positive direction of the z-axis [18, 19]. According to the formula, the inverse perspective transformation of a point in the world is:(19)Mworld=Mscreen∗Mview∗Mprojection−1.Since it is an identity matrix, the formula can be simplified to:(20)Mworld=Mscreen∗Mprojection−1.This study has introduced the specific implementation of the key algorithm of 3D modeling, which can be used in the ecological packaging of new energy products to make shopping more convenient and fast for consumers.


## 3. RFID Tag Algorithm Based on IoT

RFID tag algorithm can help the research of item identification module in product packaging design. The simulation of the algorithm is carried out under the software environment of matlab7.0. It refers to the setting of algorithm simulation conditions in the standard of EPC global Class 1 Generation2 and literature materials [20, 21]. This simulation experiment does not consider factors such as communication control between the reader and the tag, redundancy check and system energy consumption, and simulates the ideal situation where the algorithm recognizes the tag. In this study, according to the experimental conditions, the m value is obtained when the performance of the MICT algorithm is optimal through the simulation experiment, and the deviation between the experimental value and the theoretical value of the proposed MICT algorithm is analyzed. Finally, it compares with several classical tree anti-collision algorithms in terms of time complexity and communication complexity. Its comparison chart is shown in Figure 4:Figure 4
Statistics of time complexity and communication complexity under different m values. (a). Comparison of the number of recognition cycles with different m values (b). Comparison of the amount of transmitted data with differentm values.It can be seen from Figure4(a) that when m = 2, the number of tags identified by the MICT algorithm is the same, and the number of query cycles required is the most. When m = 6, the demand for the number of queries is the least. Since it adopts the m-M encoding method, the label length is 96 bits. The data shown in Figure 4(b) is very intuitive, when m = 2, the communication complexity is the largest. The communication complexity decreases gradually as m increases. When m = 4, the communication complexity is the smallest [22, 23].Table4 lists the theoretical recognition efficiency of the MICT algorithm with different values of m when the number of tags increases rapidly. Here, the value of the number of tags is set to 100, 500, 2000, and 5000.Table 4
Theoretical recognition efficiency values under different conditions.
Value ofmNumber of tags100 (%)500 (%)2000 (%)5000 (%)262.0162.2162.5762.47372.8972.3972.8972.27481.6781.4781.6081.49588.4088.6088.4088.61693.2693.4193.8293.42It can be seen from Table4 that when the value of m is large enough, the theoretical recognition efficiency of the MICT algorithm is stable at 93%, and the minimum recognition efficiency is also kept above 60%. When the recognition efficiency is above 80%, the value of m is basically all greater than 3. When the value of m is greater than 6, the length of the encoded label will be much larger than the numerical length of the label itself. It can be seen from the above that the time complexity of the proposed MICT algorithm gradually decreases with the increase of m. It can be seen from the calculation formula of the recognition efficiency that when the number of labels is constant, the time complexity is lower [24, 25].Figures5(a) and 5(b) respectively show the comparison between the MICT algorithm and the BS, QT, CT, and OBS-MCBR algorithms in terms of time complexity and communication complexity.Figure 5
Statistics of the number of recognition cycles and the amount of. transmitted data for different algorithms. (a). The number of recognition cycles of different algorithms (b). The amount of data transmitted by different algorithms.
(a)(b)It can be seen from Figure5(a) that when m = 6, the performance of the MICT algorithm is the best. In Figure 5(b), comparing several algorithms in terms of the amount of transmitted data, it can be seen that the performance of the BS algorithm is the worst, while the MICT algorithm transmits the least amount of data when m = 4.


## 4. Optimal Design of Ecological Packaging System for New Energy Products

### 4.1. Product Functional New Energy Criteria and Element Analysis Model

As the end of the product and the beginning of the logistics, packaging is the intermediate link before the product becomes a commodity and has sales value. The conceptual design of new energy packaging for the whole life cycle of packaging needs to consider many design parameters within the system boundary. However, the new energy concept design criteria that constrain the two functions of protection and display should be comprehensive optimization on protection, economy, sales and new energy performance. It gives a graph of the relationship between functions, elements, and criteria. It is shown in Figure6:Figure 6
Map of functions, elements, and criteria.It can be seen from Figure6 that the packaging constraint criteria based on new energy and cost constraints have the coupling of interspersed influences when reflecting the two functions. For example, the protection that reflects protection and the sales that reflect display should have both new energy and economic constraints. Under the influence of the coupling caused by the interlacing of design elements, it is often difficult to optimize the packaging design that follows the original traditional rules. Moreover, if the product packaging design, manufacture and use are completed, it is found that there is a deviation in the realization of a certain function and criterion. It brings a lot of hidden dangers to the cost of the entire product packaging, and the integration and dimensionality reduction of multiple factors in the conceptual design stage greatly reduces the design difficulty and reduces the negative impact caused by the disorder of design factors.


### 4.2. Conceptual Design Boundary of New Energy Packaging

Most current new energy designs use an input-output model when quantifying a product’s carbon footprint, including setting goals and thresholds. The steps of classification, inventory analysis, and impact assessment of carbon emission sources are shown in Figure7:Figure 7
General flow and model of carbon emissions calculation.As can be seen from Figure7, target and boundary determination: This process is to define the scope of emission sources that affect the calculation of carbon footprint. All carbon footprint calculations should be calculated within the bounds. The boundary not only defines the scope, but also defines certain rules within the scope, such as which types of carbon emission sources are not included in the carbon footprint calculation model. The determination of goals and boundaries is very important. Accurate goals and boundaries are the premise for the reliability of carbon footprint accounting.Inventory analysis: Inventory analysis is the process of analyzing the emission sources that may generate carbon footprints in the product life cycle within the boundary range. The appearance of the inventory provides the basis for checking/verifying the breakdown of carbon footprint accounting.Classification of environmental problems: To which category of environmental problems should each problem that produces environmental loads within the boundary and in the list belong, for example, some elements in the list produce and some produce dust that pollutes the environment. The classification of environmental problems not only provides help for the calculation of carbon footprint, but also provides a reference for other environmental problems generated in the whole life cycle of products.As can be seen from the figure, almost every year, new institutions are involved in the supervision of network information content. Especially in 2012, the emergence of a large number of new institutions marked an important development in China’s Internet content control system at that time.This study interprets the boundaries of the system as follows: A set of criteria determines which unit processes are part of the product system. The new energy packaging concept design conforms to the new energy packaging standards. In order to complete the “protection” + “display” of the product packaging, it is determined that the packaging concept design is the research stage of the product packaging functional life cycle system. The resulting system boundary is shown in Figure8.Figure 8
Boundary of the new energy packaging concept design system.It can be seen from Figure8 that the system boundary of the new energy packaging concept design is the comprehensive consideration of various factors in the whole life cycle at the “front end” of the packaging life cycle. Within the system boundary of the new energy packaging conceptual design unit, there is a set of “subunit” physical property analysis, demand analysis, functional principle, conceptual scheme, and scheme selection. In addition, the superiority of the algorithm cannot be explained only by the accuracy and mean square error. In the real network environment, there are many kinds and complex intrusions, so more precise indicators are needed to measure the effect of the algorithm. In this study, confusion matrix is used to evaluate intrusion detection in real network environment. Compared with the system boundary of the whole life cycle of packaging, the packaging concept design starts from the physical property analysis of the packaged object to the end of the scheme selection, and the boundary parameters of each “sub-unit” are different. However, the influence relationships are similar. For example, within the system boundary of conceptual design, physical property analysis determines packaging requirements. Packaging requirements are the basis for function-principle-scheme solutions. In the entire packaging life cycle, the “front-end” role of packaging concept design has a decisive impact on other stages of the life cycle. This will affect the establishment of packaging carbon footprint models.


## 4.1. Product Functional New Energy Criteria and Element Analysis Model

As the end of the product and the beginning of the logistics, packaging is the intermediate link before the product becomes a commodity and has sales value. The conceptual design of new energy packaging for the whole life cycle of packaging needs to consider many design parameters within the system boundary. However, the new energy concept design criteria that constrain the two functions of protection and display should be comprehensive optimization on protection, economy, sales and new energy performance. It gives a graph of the relationship between functions, elements, and criteria. It is shown in Figure6:Figure 6
Map of functions, elements, and criteria.It can be seen from Figure6 that the packaging constraint criteria based on new energy and cost constraints have the coupling of interspersed influences when reflecting the two functions. For example, the protection that reflects protection and the sales that reflect display should have both new energy and economic constraints. Under the influence of the coupling caused by the interlacing of design elements, it is often difficult to optimize the packaging design that follows the original traditional rules. Moreover, if the product packaging design, manufacture and use are completed, it is found that there is a deviation in the realization of a certain function and criterion. It brings a lot of hidden dangers to the cost of the entire product packaging, and the integration and dimensionality reduction of multiple factors in the conceptual design stage greatly reduces the design difficulty and reduces the negative impact caused by the disorder of design factors.


## 4.2. Conceptual Design Boundary of New Energy Packaging

Most current new energy designs use an input-output model when quantifying a product’s carbon footprint, including setting goals and thresholds. The steps of classification, inventory analysis, and impact assessment of carbon emission sources are shown in Figure7:Figure 7
General flow and model of carbon emissions calculation.As can be seen from Figure7, target and boundary determination: This process is to define the scope of emission sources that affect the calculation of carbon footprint. All carbon footprint calculations should be calculated within the bounds. The boundary not only defines the scope, but also defines certain rules within the scope, such as which types of carbon emission sources are not included in the carbon footprint calculation model. The determination of goals and boundaries is very important. Accurate goals and boundaries are the premise for the reliability of carbon footprint accounting.Inventory analysis: Inventory analysis is the process of analyzing the emission sources that may generate carbon footprints in the product life cycle within the boundary range. The appearance of the inventory provides the basis for checking/verifying the breakdown of carbon footprint accounting.Classification of environmental problems: To which category of environmental problems should each problem that produces environmental loads within the boundary and in the list belong, for example, some elements in the list produce and some produce dust that pollutes the environment. The classification of environmental problems not only provides help for the calculation of carbon footprint, but also provides a reference for other environmental problems generated in the whole life cycle of products.As can be seen from the figure, almost every year, new institutions are involved in the supervision of network information content. Especially in 2012, the emergence of a large number of new institutions marked an important development in China’s Internet content control system at that time.This study interprets the boundaries of the system as follows: A set of criteria determines which unit processes are part of the product system. The new energy packaging concept design conforms to the new energy packaging standards. In order to complete the “protection” + “display” of the product packaging, it is determined that the packaging concept design is the research stage of the product packaging functional life cycle system. The resulting system boundary is shown in Figure8.Figure 8
Boundary of the new energy packaging concept design system.It can be seen from Figure8 that the system boundary of the new energy packaging concept design is the comprehensive consideration of various factors in the whole life cycle at the “front end” of the packaging life cycle. Within the system boundary of the new energy packaging conceptual design unit, there is a set of “subunit” physical property analysis, demand analysis, functional principle, conceptual scheme, and scheme selection. In addition, the superiority of the algorithm cannot be explained only by the accuracy and mean square error. In the real network environment, there are many kinds and complex intrusions, so more precise indicators are needed to measure the effect of the algorithm. In this study, confusion matrix is used to evaluate intrusion detection in real network environment. Compared with the system boundary of the whole life cycle of packaging, the packaging concept design starts from the physical property analysis of the packaged object to the end of the scheme selection, and the boundary parameters of each “sub-unit” are different. However, the influence relationships are similar. For example, within the system boundary of conceptual design, physical property analysis determines packaging requirements. Packaging requirements are the basis for function-principle-scheme solutions. In the entire packaging life cycle, the “front-end” role of packaging concept design has a decisive impact on other stages of the life cycle. This will affect the establishment of packaging carbon footprint models.


## 5. Conclusions

Based on the IoT and virtual reality technology, this study has helped the dynamic simulation design of ecological packaging for new energy products. Starting from the system architecture and functional modules, the design basis and research process have been introduced, the optimization design is carried out based on the traditional product packaging process, and the 3D modeling algorithm in virtual reality technology is introduced to help build a new energy-optimized packaging model. As a form of intelligent packaging, digital intelligent packaging is constantly updating its connotation with the development of intelligent packaging. The proposal and evolution of its concept, like intelligent packaging, changes with the changes in market environment and technical background, and constantly absorbs new technical forms and new packaging concepts. First of all, from the definition of digital intelligent packaging, it has been pointed out that this packaging form will not be static. It is an emerging package that can be updated and upgraded. The purpose of classifying it properly and introducing its rationale and application in packaging is to make the technology easier to understand and learn. However, there are still some problems in this study. The parameter discussion involved in packaging ontology does not include the cost and environmental problems caused by management and services at the enterprise level. For the packaging of special products, there may be environmental and economic problems caused by large costs and management confusion in management and service. How to further expand the boundary scope and make the accounting of carbon footprint and cost more comprehensive in the packaging concept design stage is one of the contents that should be focused on in the follow-up research.



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