Multi-sensor Information Fusion Technology Research Articles

Retracted: The Application of Multisensor Information Fusion Technology in Environmental Restoration

Retracted: The Application of Multisensor Information Fusion Technology in Environmental Restoration

Review of the field environmental sensing methods based on multi-sensor information fusion technology

Review of the field environmental sensing methods based on multi-sensor information fusion technology

Information Fusion-Based Fault Diagnosis Method Using Synthetic Indicator

Multisensor information fusion technology plays an essential role in fault diagnosis. Uncertain reasoning is the core of information fusion, and the DS evidence theory (DSE) has founded a general and popular framework for uncertainty reasoning. Under this framework, a novel information fusion method is developed in this article, to solve the problems of counterintuitive results, poor robustness, and “one-vote veto” when fusing highly conflicting evidence using DSE. We proposed a new synthetic indicator, which can effectively eliminate the conflicts between evidences. This synthetic indicator is composed of two indexes: measurement index of indirect conflicts and that of the evidence’s information itself. First, the divergence is used to measure the degree of conflict between bodies of evidence, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model is employed to deal with indirect conflicts. Second, the Deng entropy is utilized to quantitatively measure the uncertainty of evidences, and the relative credibility preference of the evidence is expressed by the fuzzy preference relation. Finally, the initial body of evidence frame is weighted and revised by synthetic indicator before adopting the Dempster Shafer (DS) fusion rule. The superiority of the developed method is illustrated by numerical examples and application cases. The results show that fault diagnosis using the developed information fusion method can have a higher diagnostic accuracy.

Preface

The 2022 2nd International Conference on Measurement Control and Instrumentation (MCAI 2022) was held in Guangzhou, China from July 22 to 24, 2022. In view of the current COVID-19 pandemic, it was chosen to be held online. MCAI 2022 promoted research and developmental activities in the fields of “Measurement Control” and “Instrumentation” as well as scientific information interchange between researchers, engineers, and practitioners working all around the world.In the conference, we had the honor of having invited both Prof. Guixiong Liu from South China University of Technology, China and Prof. Zhen Zhou, Guangzhou Hexin Instrument Co., Ltd., China to serve as our Conference General Chairs. The conference consisted of keynote speeches, oral presentations and online Q&A discussion, attracting 100 individuals and institutions worldwide. Primarily, keynote speakers were each allocated 30-45 minutes to hold their speeches. Then in the oral presentations, the excellent papers we had selected were presented by their authors by turns.We were delighted and honored to invite three prominent professors as keynote speakers to deliver their speeches. For a start, Prof. Zongmin Ma from North University of China showed us his research: Non-contact Atomic Force Microscopy Instruments and Atomic Scale Precision Measurements. By developing the ultra-high vacuum non-contact atomic force microscope (NC-AFM), he solved the key technologies of probe vibration control and precise detection, force spectrum measurement, and realized atomic scale imaging characterization in terms of non-destructive imaging of magnetic information and uncoupled measurement of surface charge. Besides, Assoc. Prof. Zhiwei Shi from Guangdong University of Technology, China made a report on Multi-sensor Information Fusion Technology for Intelligent Networked Vehicles. Aiming at the development of intelligent networked vehicles, he proposed a vehicle headlight far-light system based on multi-sensor information fusion, which mainly includes three major parts: information fusion, drive control and optical design, ensuring in a maximum degree the intelligent lighting functions and simple structure, low cost. The wonderful speeches of each keynote speaker had triggered heated discussion. Besides, every participant praised this conference for disseminating useful and insightful knowledge.List of Committee member is available in this pdf.

Deconstruction of Urban Public Space Art Design Using Intelligent Sensor and Information Fusion

The main purpose of smart city is to improve the quality of life, improve the efficiency of life, and save the energy resources of life, which is in line with the current global concept of low-carbon environmental protection, energy saving and emission reduction, and ecological sustainable development. Under the process of smart city, the development of urban public space is also committed to meeting the material and spiritual needs of residents’ lives. For the system hardware design, the street lamp node, and the concentrator node hardware design, the sensing node is composed of multiple sensors. Its main components are temperature sensor, infrared sensor, sound sensor, and light intensity sensor, which, respectively, realize the collection of temperature, infrared, sound, and light intensity information. The street light sensing system uses multisensor information fusion technology to detect the situation of people and vehicles in real time, so that people and vehicles can turn on the street lights and turn off the street lights of unmanned vehicles. Adjust the street light switch according to the intelligent analysis of the lighting demand scene in order to enhance the accuracy of the system to identify the lighting demand scene. This enables the system to provide safe lighting conditions for urban traffic while saving the power consumption of urban lighting. The sensor system of the street light randomly selects the detection results of temperature and humidity within a certain period of time. The error rate of the final test result is 1/2 of that of the traditional test, and the accuracy is far lower than that of the traditional measurement method. Regarding the lighting system of street lamps and public art in urban public spaces, it is worthy of extensive promotion to control street lamp lighting through sensor information fusion technology and reduce energy consumption.

The Application of Multisensor Information Fusion Technology in Environmental Restoration

Multisensor information fusion technology is an advanced processing method that is different from classical data processing technology. Capability and operational accuracy, in order to make an effective comprehensive evaluation of environmental quality, the environmental monitoring system built by NB-IoT technology and sensor technology is used to conduct multisensor data fusion research on the collected environmental factors such as temperature, humidity, formaldehyde, PM2.5, and TVOC. At the same time, the two-level parallel fusion method is adopted to evaluate the environmental quality. Before data fusion, median filtering is used to eliminate abnormal data. Then, the Kalman filter algorithm is used to fuse multiple sets of similar sensors to obtain the best value of it. Finally, the fuzzy comprehensive evaluation method is used to fuse the different types of sensors at the decision-making level, in which the weight value is determined by the entropy method and the membership function is Gaussian. The different environment scenarios are tested by using the above algorithms, and the simulation results show that multisensor data fusion can obtain more abundant and effective environmental information, overcome the simplicity and limitation of single-factor sensor for environmental quality assessment, and improve the reliability and accuracy of the overall environmental quality assessment.

Outdoor scene understanding of mobile robot via multi-sensor information fusion

The present research on the multi-sensor information fusion technology of mobile robots aims to better understand the outdoor scene and improve the robot's perception of the environment. Firstly, a conversion algorithm is proposed based on two point-cloud-to-image algorithms, including the point cloud plane fitting and point cloud projection transformation. Moreover, the elevation map is constructed to describe the terrain characteristics of the scene based on the three-dimensional laser ranging data. Meanwhile, the conditional random field model is used to obtain landform characteristics from visual information. Besides, the projection transformation and information statistics methods are used to effectively integrate the laser information and the visual information with the grid in the elevation map as the carrier. Ultimately, the convolution neural network is used to realize the three-dimensional scene understanding. It is found that the average recognition rate of the outdoor scene understanding model based on multi-sensor information fusion is as high as 89.36%, and the image segmentation time of the proposed algorithm is not more than 180 ms.The latest research results refer to the use of SSAE in combination with the CRF algorithm. On the whole, the proposed model improves the real-time performance of the mobile robot under the premise of accuracy, and realizes the recognition and analysis ability of complex scenes through the construction of multi-sensor information. This study has important practical significance for promoting the development of the mobile robot autonomous industry.

Application of Wireless Network Multisensor Fusion Technology in Sports Training.

Fencing is an advantageous event for a country to participate in the Asian Games. The discussion and research on the means and methods of special fencing ability training are of great significance to the further development of fencing in the country. Based on the multisensor information fusion technology, this paper develops a special fencing training system with digital monitoring and intelligent decision-making. The multisensor information fusion technology scheme, which is reported in this paper, is used to perform decision-level fusion based on fuzzy inference technology whereas Kalman filter is used to optimize the original information. On the basis of the overall structure, mechanical mechanism, and performance analysis, the mechanical prototype of the fencing special ability training system was developed whereas design, processing, and debugging of the prototype were completed. Combined with the mechanical prototype design of various index parameter display structures based on multisensor information fusion technology, the digital processing of the fencing special ability training system is realized. The force, speed, position, and other characteristic quantities in the fencing special training system are collected by the pressure and rotational speed sensors respectively whereas USB communication technology is used for data transmission. On the basis of in-depth analysis of the characteristics of the special training system for fencing, an abstract system of pedaling power based on the center of gravity and trend models is designed where the Kalman filter is reserved for the special application fields. Moreover, the core role of Kalman filter is carried out when original data information is needed to be obtained. By constructing a force distribution pressure center trajectory measurement model, a training load and training parameter measurement model, and a training level evaluation model, the data-level raw information is specially processed to generate more training parameters that meet specific characteristics, making the multisensor information fusion technology more efficient. It is well integrated into the fencing special ability training system. By applying fuzzy reasoning technology, the special training parameters and the relationship between these parameters are transformed into fuzzy sets and fuzzy rules, and the perceptual knowledge of sports training experience is transformed into fuzzy rules. With this decision-level data fusion method, the fencing special training system has certain intelligent functions.

Monitoring and Analysis of Physical Exercise Effects Based on Multisensor Information Fusion

In this paper, multiple sensors are used to track human physiological parameters during physical exercise, and data information fusion technology is used to extract useful information for monitoring and analyzing the effects of physical exercise. This paper explores the interaction and developmental dynamics of multisensor information fusion technology and physical exercise data monitoring based on the interrelationship and interpenetration between the two. The design ideas and principles that should be followed for the software designed in this study are discussed from the perspective of the portable design of measurement instruments and the perspective of multisensor information fusion, and then, the overall architecture and each functional module are studied to propose a scientific and reasonable design model. The general methodological model to be followed for the development of this resource is designed, and the basic development process of the model is explained and discussed, especially the requirement analysis and structural design, and how to build the development environment are explained in detail; secondly, based on the course unit development process in this model, we clarify the limitations of the system through meticulous analysis of the measurement results, which provides a solid foundation for the next step of system optimization. Finally, with a focus on future development, we elaborate on the potential possible role and development trend of multisensor information fusion in the future period. In this paper, we propose to apply the multisensor data fusion algorithm to the monitoring, analysis, and evaluation of the effect of physical exercise, by collecting multiple human physiological parameters during physical exercise through multiple sensors and performing data fusion processing on the collected physiological parameters to finally evaluate the effect of physical exercise.

Intelligent Fault Diagnosis of Photoelectric Pod Bearing Based on Multi-information Fusion

Intelligent fault diagnosis technology has become the focus of research in various fields. Its realization depends on the acquisition of equipment state by sensors. Because the fault information provided by a single sensor has limitations and cannot fully reflect the fault state of the tested object, we need to use multiple sensors to collect and fuse the fault information of rolling bearings to ensure the accuracy and accuracy of intelligent fault diagnosis. Based on this, this paper analyzes the application of fuzzy rules of multi-sensor information fusion technology in the fault diagnosis of bearings in the optoelectronic pod, so as to provide a reference for the realization of intelligent fault diagnosis of each structure in the optoelectronic pod.

Intelligent Shopping Cart Design Based on the Multi-Sensor Information Fusion Technology and Vision Servo Technology

In order to promote the intelligent transformation of service-oriented robot used in supermarkets, an intelligent shopping cart has been designed in this paper to realize the integration of auto following, shopping and payment based on the multi-sensor information fusion technology and vision servo technology. Firstly, a distributed sensor fusion structure was designed including photoelectric, ultrasonic sensors and monocular camera. Then, all the collected data were fused during auto following process of the intelligent shopping cart, and the commodity information could be identified to form the billing information by which the customer could complete the payment by scanning the payment QR code and the corresponding records also can be viewed by logging in the Wechat applet.

A Matching Algorithm for Underwater Acoustic and Optical Images Based on Image Attribute Transfer and Local Features.

In the field of underwater vision, image matching between the main two sensors (sonar and optical camera) has always been a challenging problem. The independent imaging mechanism of the two determines the modalities of the image, and the local features of the images under various modalities are significantly different, which makes the general matching method based on the optical image invalid. In order to make full use of underwater acoustic and optical images, and promote the development of multisensor information fusion (MSIF) technology, this letter proposes to apply an image attribute transfer algorithm and advanced local feature descriptor to solve the problem of underwater acousto-optic image matching. We utilize real and simulated underwater images for testing; experimental results show that our proposed method could effectively preprocess these multimodal images to obtain an accurate matching result, thus providing a new solution for the underwater multisensor image matching task.

RETRACTED ARTICLE: Residential planning and layout design method based on multi-sensor information fusion

With the in-depth development of the market economy and the acceleration of the process of urbanization, a large number of people have poured into the city, and a large number of residential communities have been developed and constructed. Design quality in the development process is often replaced by output. Some companies attach importance to quality but do not know how to control quality. Based on this, this paper uses the method of multi-sensor information fusion to study the planning and layout design methods of residential areas, and provides a design basis for solving the problems of people’s living environment deterioration and increasingly scarce land resources. Based on the Rhinoceros and Grasshopper parametric platform, this paper integrates residential information model, performance prediction technology, and multi-sensor information fusion technology, taking residential planning and layout parameters as design variables. A set of intelligent optimization system for residential planning and layout based on multi-performance objective simulation was compiled. The “internal factors” and “external factors” that affect the results of RLIOS are studied, and then the residential planning and layout design methods are studied. Experiments have proved that no matter what algorithm is used, the performance of each target can be improved, the floor area ratio performance can be improved by 35.3–3.3%, and the open space performance can be improved by 12.6–31.36%. It shows that the residential planning and layout design method based on multi-sensor information fusion proposed in this paper improves the accuracy and efficiency of the work.

Interoperability technology of sports health monitoring equipment based on multi-sensor information fusion

Nowadays, the pace of society is accelerating, people’s living standard has been greatly improved compared with the past, and we pay more and more attention to the real-time, flexibility, and intelligence of medical services. Information fusion technology is the study of how to effectively and comprehensively utilize multi-sensor information to overcome information imperfections and uncertainties. In recent years, it has become a hotspot for research, but with the development of communication technology, electronic technology, and computers, the form of information becomes complicated and diverse in science and technology such as technology. In this case, the information obtained by a single sensor is always imperfect, so multiple sensors must be used to detect the target from multiple angles. Obtaining more dimensional information about the target and fusing it to ensure the integrity and accuracy of the information helps to accurately determine the physiological health of the human body. This paper analyzes the multi-sensor information fusion technology in detail, discusses the basic principle of multi-sensor information fusion, fusion process, fusion level, architecture and general fusion algorithm, constructs a sensor information fusion technology and its application model in biomedical detection, from the application framework, control structure of multi-sensor integrated system, information fusion, etc. The current situation of multi-sensor information fusion technology is studied in several aspects. An interoperability technology of sports health monitoring equipment based on multi-sensor information fusion is constructed. The experimental results show that the experimental efficiency is improved by 20% after using the application model in this paper, which has certain practicability.

Forecast of Fire Protection Situation in High-Rise Buildings Based on Multi-Sensor Information Fusion

With the continuous development of modern science and technology and the increase in the amount of multi-sensor information, the prediction of the fire protection situation of high-rise buildings has gradually become a challenge. This paper establishes a prediction system for the fire protection situation of high-rise buildings and uses multi-sensor information fusion technology for high-rise buildings. The building fire protection situation index weight is weighted, and the original sensors are optimized to verify the prediction effect of the high-rise building fire protection situation. The experimental analysis results show that this method can reduce the initiative of the weight of the fire protection index of high-rise buildings and improve the accuracy of prediction.

Research on Information Fusion Technology of MEMS Gyro Array

The measurement accuracy of MEMS gyroscope is relatively low. Starting from the software level, the multi-sensor information fusion technology of MEMS gyroscope array (MGA) is used to reduce the drift of MEMS gyroscope. Firstly, a signal acquisition and processing system for communicating with ADXRS810 gyroscope based on field-programmable gate array (FPGA) is designed. Secondly, the collected drift data of the gyroscope array is preprocessed. long-term drift trend terms are obtained by ensemble empirical mode decomposition (EEMD) and the linear function fitting, and the trend terms are filtered out to obtain a smooth and normal drift signal. Then, the data fusion model based on time series analysis is built for the gyroscope array and the error analysis is performed by Allan variance. Finally, based on the AR (1) model, the moving horizon optimization Kalman filter method is used to filter the drift data of the gyroscope array. The experiment shows that when the time domain length N=3, the bias instability of gyroscope 1, 2, 3 and 4 decreases from 9.716 o/h, 8.5682 o/h, 13.484 o/h and 26.414 o/h to 1.2922 o/h, 0.61147 o/h, 1.4184 o/h and 1.6964 o/h, respectively, and the average noise coefficient decreases by more than 85%. Compared with the ordinary Kalman filter method, the bias instability has been significantly improved.

Research Status and Development Trend of Water Cut Detection Methods for Crude Oil

Water cut detection of crude oil plays a very important role in the petroleum and petrochemical industry. At present, the existing crude oil water cut detection methods include capacitance method, conductance method, radio frequency method, Ray method, spectrum method. Firstly, the measuring principle, application conditions, advantages and disadvantages of the existing methods are summarized, and the factors affecting the measuring accuracy of the existing methods are analyzed. Afterwards, the latest development of water cut measurement technology of crude oil is mentioned, such as multi-sensor information fusion technology, tomography technology, neural network technology. With the emergence of new technology and new method, the development trend of crude oil water cut measurement technology is towards full range, high precision, intelligence, multi-parameter fusion, safety, energy saving, environmental protection and so on.

Preface

The 2021 7th International Symposium on Sensors, Mechatronics and Automation System (ISSMAS 2021) was held on January 29-31, 2021 as a virtual conference due to the growing concerns over the coronavirus outbreak (COVID-19), and in order to protect the well-being of our attendees, partners, and staff as our number one priority. The idea of the conference is for the scientists, scholars, engineers and students from the Universities all around the world and the industry to present ongoing research activities, and hence to foster research relations between the Universities and the industry. The conference will be held every year to make it an ideal platform for people to share views and experiences in Sensors, Mechatronics and Automation System and related areas.This scientific event brings together more than 100 national and international researchers in Sensors, Mechatronics and Automation System. On top of the local participants coming from different national universities, international participants are also registered from different countries, namely Germany, India, Malaysia. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 5-10 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches.In the keynote presentations part, we invited three professors as our keynote speakers. The first keynote speakers, Prof. Xiaochuan Chen, from College of Mechanics of Donghua University, China was invited to present his talk Finite element analysis of cotton ginning state based on ANSYS. In his keynote speech, in order to analyze the stress condition of the seed cotton in the process of cotton gin and improve the quality of lint, a new cotton model was presented based on the idea of composite laminate---laminated cotton model. Prof. Shahid Hussain, from Jiangsu University, China was our second keynote speakers. He presented a talk: New Diversities in Nanomaterials for Gas Sensing Application. His presentation discussed that in the recent years, metal sulfide nanostructured materials have become established in different research fields thanks to their excellent properties. Assoc. Prof. Yiyang Chen, from School of Mechanical and Electrical Engineering, Soochow University, China as our finale keynote speakers. He presented a talk: The Background Theory and Recent Progress of Iterative Learning Control. The novelty of this talk concentrated on the cooperation between the advantages of ILC and massive repetitive industrial manufacturing tasks, so that a targeted ILC algorithm can be developed to bring a competitive application perspect as well as significant economic effect.The proceedings are a compilation of the accepted papers and represent an interesting outcome of the conference. Topics include but are not limited to the following areas: Sensors, Actuators and Their Applications, Multi-sensor Information Fusion Technology, Measurement Methods, Technologies and Their Applications, Smart Materials, Design, Processing and Smart Structures and more related topics. All the papers have been through rigorous review and process to meet the requirements of International publication standard.We would like to acknowledge all of those who supported ISSMAS 2021. The help and contribution of each individual and institution was instrumental in the success of the conference. In particular, we would like to thank the organizing committee for its valuable inputs in shaping the conference program and reviewing the submitted papers.List of Committee member, Conference Chairman, Technical Program Committees, Organizing Committee are available in the pdf

Multisensor Information Fusion‐Assisted Intelligent Art Design under Wireless Virtual Reality Environment

Under the background of intelligent technologies, art designers need to use information technology to assist the design of art factors and fully realize the integration of art design and information technology. Multisensor information fusion technology can more intuitively and visually carry out a more comprehensive grasp of the objectives to be designed, maximize the positive effects of art design, and achieve its overall optimization and can also help art designers get rid of the traditional monolithic and obsolete design concepts. Based on multisensor information fusion technology under wireless virtual reality environment, principles of signal acquisition and preprocessing, feature extraction, and fusion calculation, to analyze the information processing process of multisensor information fusion, conduct the model construction and performance evaluation for intelligent art design, and propose an intelligent art design model based on multisensor information fusion technology, we discuss the realization of multisensor information fusion algorithm in intelligent art design and finally carry out a simulation experiment and its result analysis by taking the environment design of a parent‐child restaurant as an example. The study results show that using multisensor information fusion in the environmental design of parent‐child restaurant is better than using a single sensor for that; at the same time, using force sensors has a better environmental design effect than using vibration sensors. The multisensor information fusion technology can automatically analyze the observation information of several sources obtained in time sequence under certain criteria and comprehensively perform information processing for the completion of the decision‐making and estimation tasks required for intelligent art design.

Sports Information Acquisition and Functional Training System Based on Multisensor Information Fusion

Since entering the 21st century, multisensor information fusion technology has developed rapidly, and multisensor information fusion is a trend in the coming years and even decades. This article is aimed at studying how the traditional sports information acquisition and functional training system can be implemented under the multisensor information fusion. This article proposes the use of multisensor information fusion technology to conduct an in‐depth study on the traditional ways of acquiring sports information and the cognition of sports information by different groups of people, as well as the use of multisensor information fusion technology to update the functional training system and discuss whether this new functional training system is in line with the speed and rhythm of the current era compared with the traditional training system. The results of obtaining sports information from different groups of people show that more people know about sports events at home and abroad, reaching 22.5%. Under the same circumstances, 60% of the elderly are willing to pay attention to sports information, while only 30% of the young people are willing to pay attention to sports information. And from 2016 to 2021, the number of people in functional training nationwide has increased from 200,000 to 1.5 million.