CHEMICAL ENGINEERING TRANSACTIONS  
 

VOL. 62, 2017 

A publication of 

 

The Italian Association 
of Chemical Engineering 
Online at www.aidic.it/cet 

Guest Editors: Fei Song, Haibo Wang, Fang He 
Copyright © 2017, AIDIC Servizi S.r.l. 

ISBN 978-88-95608- 60-0; ISSN 2283-9216 

Research on Logistics Solutions for Dangerous Chemical 

Products 

Chengwu Zheng 

Yangtze Normal University, Chongqing 408100, China 

cwzheng@126.com 

The objective of this paper is to design and realize the logistic monitoring system for dangerous chemical 

products. As for problems of robbery accidents and leakage accidents during the transportation process of 

dangerous chemical products, the identification and tracking technology on moving objects in the real-time 

video stream transmission and video sequence are the main research objects; and the specific discussion and 

research on the video monitoring technology in the logistic monitor system of dangerous chemical products is 

carried out based on the research on theory principle and technology realization of existing video technology. 

The real-time transmission of video stream is achieved by collecting the video of YUV4:2:2 form, video coding 

& compression of H264 form and using RTP protocol, so that the identification and tracking on moving objects 

in the video sequence can be achieved. The experiment result indicates that the logistic monitoring system for 

dangerous chemical products designed in this paper can be effectively applied to identify the moving objects. 

Therefore, the logistic monitoring system for dangerous chemical products can be used to improve the stability 

and effectiveness of the transportation of dangerous chemical products.  

1. Introduction 

The weight of dangerous chemical products in road transportation in China is hundreds of millions of tons, 

which takes more than 30% in the volume of freight traffic (Dey, 2017). A city is located in the intersection of 

coastal economic development zone and Yangtze river economic development zone, which is the distributing 

centre for important liquid chemical products; more than 30 discharging quays for dangerous liquid-type 

chemical products are set up in this city (Memon et al., 2017), which has become the largest port city for the 

transportation of dangerous chemical products, and also the most important discharging centre for dangerous 

liquid-type chemical products in China (Paes et al., 2017). With the rapid economic development in China, the 

traffic volume of dangerous liquid-type chemical products is increased, and the variety is rich; vehicles and 

industry staff for the transportation of dangerous chemical products are also increased continuously 

(Proskurnikov, 2017). However, with the increasing volume of chemical products traffic, the entire quality of 

staff working in the industry of transportation of dangerous liquid-type chemical products is still increased 

slowly, and transportation accidents of liquid-type chemical products is subject to the occurrent frequency 

getting higher year-by-year; the accident damage degree is getting deeper and deeper, which endangers the 

production and living of the society, and also affects the life, property and succory greatly(Rato et al., 2017). If 

the dynamic supervision system is insufficient in the transportation of dangerous liquid-type chemical products, 

very serious consequence may be caused in case of accidents (Thekkudan et al., 2017). In order to solve the 

frequent robbery accidents of vehicle-mounted dangerous liquid-type chemical products, the project bidding is 

proposed by the government of a city (Wang et al., 2017).  

2. Domestic and foreign research status 

There are two types of video monitor technology products in the domestic and foreign markets (Wu et al., 

2017). One of which is the video monitor system using analog circuit technology, and the other one is the 

video monitoring using digital circuit technology (Wu et al., 2017). The digital monitoring technology is 

developed on the basis of analog-video monitoring technology, which requires the continuous improvement 

                                

 
 

 

 
   

                                                  
DOI: 10.3303/CET1762257 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Please cite this article as: Chengwu Zheng, 2017, Research on logistics solutions for dangerous chemical products, Chemical Engineering 
Transactions, 62, 1537-1542  DOI:10.3303/CET1762257   

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and perfection (Yuan, 2017). The popularization of digital video monitor system is the trend of future 

development based on current trend, which is of important practical significance. 

The digital video monitor system is usually divided into two types: the first type is the traditional computer-

multimedia working mode (Geng et al., 2016). The other type is the digital video-monitor system based on 

embedded technology. The rapid development of embedded technology is the strong technical support for the 

popularization of embedded-type digital video-monitor system (Park, 2016). The V4L2 programming 

specification is used in the video collection. As the Linux is the operation system for logistic monitor system of 

dangerous chemical products, the interface provided by the Linux operation system to the application vising 

the video driver is V4L2. (Sironi et al., 2016) The video capture interface is usually used in the video monitor 

system, and the monitor video is collected through V4L2. The flow of V4L2 is: open the camera; check and set 

up the property of the camera; set up the frame form of the video collected; set up the input and output 

methods; obtain the video data circularly; turn off the camera (Stoyanov et al., 2016). In case the video 

collection is completed, the original video should be subject to coding and compression so as to improve the 

utilization rate of communication bandwidth and storage space. H.264 is a standard of digital video co ding. It 

is established on the basis of MPEG-4, and the coding and decoding flow consists of five parts (Zeng et al., 

2016).  

After the video is collected, coded and compressed by the monitoring system, in case the video is to be 

transmitted or stored, the UDP or RTP protocol is usually used for transmission. The video can be watched in 

real time by the observer when it is transmitted with RTP protocol, and the RTP protocol is used in many 

famous Internet video websites (Youku, Tudou and You Tube) for video transmission (Chithambaranadhan et 

al., 2015). Many objects may occur in the same scene in the real world, and such objects are independent to 

each other, which should be processed separately, and may be interest in one or more types of things in one 

scene. The detection of moving objects is implemented in the sequence image by combining the moving 

objects, and the methods of which mainly includes the statistic model, optical field flow and image difference 

image (Naeem et al., 2015). The optical flow field is of important value in fields such as object identification 

and object segmentation etc (Li et al., 2014). 

3. Dangerous chemical products and their transportation 

According Article 3 of the newly-revised Safety Management Rules on Dangerous Chemical Products, 

dangerous chemical products (hereinafter after referred to as “DCP”) means the highly toxic chemicals and 

other chemicals with the toxic, corrosive, explosive, combustion and comburent properties etc. and which are 

harmful to human body, facilities and environment; which requires special protection. It may be considered as 

the DCP when three features mentioned above are equipped (Silva et al., 2011). According to the national 

standard of the People’s Republic of China of 2010 – Classification and Marking of Dangerous Chemicals 

Commonly Used, the DCP is divided into three types in China based on the dangerousness: physical and 

chemical danger, health danger and environment danger.  

Self-operated logistics transportation: all logistics businesses of this mode rely on their own logistic system to 

complete the transportation of DCP (Ranky, 2007), and the main economic source of these enterprises is not 

logistics.  

Outsourcing logistic transportation: generally speaking, enterprise always only focus on their own core 

business; and in order to enhance their core competitiveness, business related the logistics of enterprises is 

always contracted by the third party-logistic enterprise. See the outsourcing logistic transportation pattern in 

Figure 1.  

 

Figure 1: Relevant Patterns of Outsourcing Logistic Transportation 

Transportation of common distribution: or it can also be sharing logistic transportation of the third party; it is of 

large difference to the coordinated distribution transportation, generally speaking, goods or products (most of 

which are of the same type) of many owners are collected together so as to be distributed and transported by 

the same third-party logistic enterprise, by which the vehicle resource can be saved and the transportation 

efficiency can be improved.  

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Mixed-type logistic transportation: this logistic pattern is the integration of advantages in outsourcing 

transportation pattern and self-operation pattern so as to achieve mutually reinforcing and organic combination.  

4. Entire structure design of the software and software module division 

The structure of the logistic monitor system of dangerous chemical products is divided into five layers, and 

necessary service is provided by each layer to the last layer. The lowest layer is the embedded hardware 

platform based on ARM11 processor, and the hardware design and manufacture is outsourced by OEM 

manufacturers so as to save the limited time and project fund; the hardware actually used in the project 

includes the USB camera, 3G module and liquid sensor based on RS232 interface etc. are obtained by 

purchasing. See the hierarchical structure division diagram of logistic monitoring system of dangerous 

chemical products in Figure 2.  

 

Figure 2: Hierarchical Structure Division Diagram of Logistic Monitoring System of Dangerous Chemical 

Products 

The hardware driven layer is above the hardware layer, and the function of which is to make various hardware 

available for the operation system and to make the selected operation system equipped with basic drivers, 

such as the USB camera driver, 3G module driver etc. The existence of basic hardware driver in the operation 

system is the first indicator, and the read-write of RS232 interface should be completed by writing the standard 

serial communication programming. 

The application-layer software is divided into submodules based on demand analysis. The logistic monitoring 

system of DCP consists of seven submodules, and the conclusion is obtained based on Party A’s demand 

analysis. See the software module division of DCP logistic monitor system in Figure 3.  

The hierarchy can be implemented to the DCP logistic monitoring system again after the submodule division is 

defined. The video collection module is the basis for the operation of application software; the local storage 

and video flow transmission is implemented after the video is coded and compressed, and the playing of real-

time video floe as well as the identification and tracking of moving objects are the function presented to users 

directly. The layer of DCP logistic monitoring system will be divided again in the application software. See the 

module hierarchy of DCP logistic monitoring system in Figure 4.  

 

Figure 3: Software Module Division of DCP Logistic Monitor System 

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Figure 4: Module Hierarchy of DCP Logistic Monitoring System 

The identification and tracking modules of moving objects are corresponding to the identification and tracking 
type of moving objects, and the main function of such type is to identify and track the moving objects in the 
video sequence. The data members of such type must include the feature points under tracking as well as the 
property of the tracking feature points. Member functions of such type must include basic functions such as 
the function of detection feature points and function of tracking feature points. The identification and tracking 
type of moving objects is subject to the use of member functions such as the video collection type, video 
coding and compression type as well as video transmission type; therefore, the identification and tracking type 
of moving objects relay on such types. See the dependency relationship between identification and tracking 
types of moving objects in Figure 5.  

 

Figure 5: Dependency Relationship between Identification and Tracking Types of Moving Objects 

According to the division of DCP logistic monitoring system types and the analysis on dependency relationship, 
the dependency relationship used in the system can be obtained. See the dependency relationship among 
types in Figure 6.  
The quality of video transmission is improved based on existing network bandwidth and network speed 
foundation, and the key is to select the appropriate network transmission protocol. See the architectural 
design figure of communication protocol in Figure 7. 

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Figure 6: Dependency Relationship among Types 

 

Figure 7: Architectural Design of Communication Protocol 

5. Conclusion 

The objective of this paper is to design and achieve one DCP logistic monitoring system. The video of 
YUV4:2:2 form is collected in the system, and the video coding and compression is of H264 form; the RTP 
protocol is used to achieve the transmission of real-time video flow so as to achieve the identification and 
compression of moving objects in video sequence. Excess software and hardware resources are used in the 
system operation, which is of high CPU usage rate. The thread of the system operation includes the video 
collection and compression real-time playing of the video, video flow transmission as well as the identification 
and tracking of moving objects; multiple threads are under the simultaneous operation, which requires a lot of 
hardware resources, which is the defect of the system. The specific resolution of moving objects cannot be 
achieved by the identification and tracking of moving objects effectively, only the moving objects can be 
identified in the video sequence. The demand analysis instruction of DCP logistic monitoring system clearly 
indicates that personnel around the oil tank truck must be identified, however, the current system can only be 
used to identify the moving objects, but cannot distinguish that if the object is human being or a thing.  

Acknowledgement 

Project supported by the Scientific Research Institute of the yangtze normal number: 2017KYQD17. 

Reference  

Chithambaranadhan D., Veeramuthu V., Nguyen Q., Lommasson T.C., Goldberg R., Boström T., 2015, 

Efficiency Improvement in Nonprime Crystalline Silicon Solar Cells by Chemical Isolation of Shunts Under 

Front Metallization, IEEE Journal of Photovoltaics, 5, 206-211, DOI: 10.1109/JPHOTOV.2014.2373815. 

Dey G.R., Das T.N., 2017, Dielectric Barrier Discharge of Moist Nitrogen: A Methodology for Exclusive NO 

Generation, IEEE Transactions on Plasma Science, 1-6, DOI: 10.1109/TPS.2017.2716976. 

1541



Geng Y., Chen J., Fu R., Bao G., Pahlavan K., 2016, Enlighten Wearable Physiological Monitoring Systems: 

On-Body RF Characteristics Based Human Motion Classification Using a Support Vector Machine, IEEE 

Transactions on Mobile Computing, 15, 656-671, DOI: 10.1109/TMC.2015.2416186. 

Li J., Choi T.M., Cheng T.C.E., 2014, Mean Variance Analysis of Fast Fashion Supply Chains with Returns 

Policy, and Cybernetics: Systems IEEE Transactions on Systems, Man, 44, 422-434, DOI: 

10.1109/TSMC.2013.2264934. 

Memon S.F., Ali M.M., Pembroke J.T., Chowdhry B.S., Lewis E., 2017, Measurement of Ultralow Level 

Bioethanol Concentration for Production Using Evanescent Wave Based Optical Fiber Sensor, IEEE 

Transactions on Instrumentation and Measurement, 1-9, DOI: 10.1109/TIM.2017.2761618. 

Naeem A., Shabbir A., Hassan N.U., Yuen C., Ahmad A., Tushar W., 2015, Understanding Customer 

Behavior in Multi-Tier Demand Response Management Program, IEEE Access, 3, 2613-2625, DOI: 

10.1109/ACCESS.2015.2507372. 

Paes R., Kay J.A., Cassimere B., 2017, Applying Arc Resistant Technologies to Medium Voltage Variable 

Speed Drives, IEEE Transactions on Industry Applications, 1, DOI: 10.1109/TIA.2017.2761824. 

Park Y., Kweon I.S., 2016, Ambiguous Surface Defect Image Classification of AMOLED Displays in 

Smartphones, IEEE Transactions on Industrial Informatics, 12, 597-607, DOI: 10.1109/TII.2016.2522191. 

Proskurnikov A.V., Cao M., 2017, Synchronization of Goodwin 's Oscillators under Boundedness and 

Nonnegativeness Constraints for Solutions, IEEE Transactions on Automatic Control, 62, 372-378, DOI: 

10.1109/TAC.2016.2524998. 

Ranky P.G., 2007, Engineering Management-Focused Radio Frequency Identification (RFID) Model Solutions, 

IEEE Engineering Management Review, 35, 20-30, DOI: 10.1109/EMR.2007.899727. 

Rato T.J., Blue J., Pinaton J., Reis M.S., 2017, Translation-Invariant Multiscale Energy-Based PCA for 

Monitoring Batch Processes in Semiconductor Manufacturing, IEEE Transactions on Automation Science 

and Engineering, 14, 894-904, DOI: 10.1109/TASE.2016.2545744. 

Silva A.F., Goncalves A.F., de Almeida Ferreira L.A., Araujo F.M.M., Mendes P.M., Correia J.H., 2011, A 

Smart Skin PVC Foil Based on FBG Sensors for Monitoring Strain and Temperature, IEEE Transactions 

on Industrial Electronics, 58, 2728-2735, DOI: 10.1109/TIE.2010.2057233. 

Sironi A., Türetken E., Lepetit V., Fua P., 2016, Multiscale Centerline Detection, IEEE Transactions on Pattern 

Analysis and Machine Intelligence, 38, 1327-1341, DOI: 10.1109/TPAMI.2015.2462363. 

Stoyanov T., Vaskevicius N., Mueller C.A., Fromm T., Krug R., Tincani V., Mojtahedzadeh R., Kunaschk S., 

Ernits R.M., 2016, No More Heavy Lifting: Robotic Solutions to the Container Unloading Problem, IEEE 

Robotics Automation Magazine, 23, 94-106, DOI: 10.1109/MRA.2016.2535098. 

Thekkudan V.N., Vaidyanathan V.K., Ponnusamy S.K., Charles C., Sundar S., Vishnu D., Anbalagan S., 

Vaithyanathan V.K., Subramanian S., 2017, Review on nanoadsorbents: a solution for heavy metal 

removal from wastewater, IET Nanobiotechnology, 11, 213-224, DOI: 10.1049/iet-nbt.2015.0114. 

Wang J., Barback C.V., Ta C.N., Weeks J., Gude N., Mattrey R.F., Blair S.L., Trogler W.C., Lee H., Kummel 

A.C., 2017, Extended Lifetime In Vivo Pulse Stimulated Ultrasound Imaging, IEEE Transactions on 

Medical Imaging, 1, DOI: 10.1109/TMI.2017.2740784. 

Wu F., Wen C., Guo Y., Wang J., Yu Y., Wang C., Li J., 2017, Rapid Localization and Extraction of Street 

Light Poles in Mobile LiDAR Point Clouds: A Supervoxel-Based Approach, IEEE Transactions on 

Intelligent Transportation Systems, 18, 292-305, DOI: 10.1109/TITS.2016.2565698. 

Wu J., Ye C., Sheng V.S., Zhang J., Zhao P., Cui Z., 2017, Active learning with label correlation exploration 

for multi-label image classification, IET Computer Vision, 11, 577-584, DOI: 10.1049/iet-cvi.2016.0243. 

Yuan J., 2017, Learning Building Extraction in Aerial Scenes with Convolutional Networks, IEEE Transactions 

on Pattern Analysis and Machine Intelligence, 1, DOI: 10.1109/TPAMI.2017.2750680. 

Zeng J., Chu W.S., la Torre F.D., Cohn J.F., Xiong Z., 2016, Confidence Preserving Machine for Facial Action 

Unit Detection, IEEE Transactions on Image Processing, 25, 4753-4767, DOI: 10.1109/TIP.2016.2594486. 

 

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