Unmanned aerial vehicles towards future Industrial Internet:Roles and opportunities

Unmanned Aerial Vehicles(UAVs)are gaining increasing attention in many fields,such as military,logistics,and hazardous site mapping.Utilizing UAVs to assist communications is one of the promising applications and research directions.The future Industrial Internet places higher demands on communication quality.The easy deployment,dynamic mobility,and low cost of UAVs make them a viable tool for wireless communication in the Industrial Internet.Therefore,UAVs are considered as an integral part of Industry 4.0.In this article,three typical use cases of UAVs-assisted communications in Industrial Internet are first summarized.Then,the state-of-the-art technologies for drone-assisted communication in support of the Industrial Internet are presented.According to the current research,it can be assumed that UAV-assisted communication can support the future Industrial Internet to a certain extent.Finally,the potential research directions and open challenges in UAV-assisted communications in the upcoming future Industrial Internet are discussed.

Measurement and Strategy Research on the Green Development Level for the New Energy Vehicle Industry in Chongqing City

This article takes 2016-2022 as the inspection period to construct an evaluation index system for the green development level of the new energy vehicle industry.The entropy method and comprehensive index are used to measure the green development level of the new energy vehicle industry in Chongqing,and compared with neighboring provinces such as Yunnan,Guizhou,and Sichuan.Policy recommendations are proposed to promote the development of the new energy vehicle industry in Chongqing City.

A Cost-Efficient Environment Monitoring Robotic Vehicle for Smart Industries

Environmental monitoring is essential for accessing and avoiding the undesirable situations in industries along with ensuring the safety of workers.Moreover,inspecting and monitoring of environmental parameters by humans lead to various health concerns,which in turn brings to the requirement of monitoring the environment by robotics.In this paper,we have designed and implemented a cost-efficient robotic vehicle for the computation of various environmental parameters such as temperature,radiation,smoke,and pressure with the help of sensors.Furthermore,the robotic vehicle is designed in such a way that it can be dually controlled by using the remote control along with the distant computer.In addition,contrary to the existing researches,the GSM modules are used to achieve the two-way long distance communication between the robotic vehicle and the distant computer.On the distant computer,the above-mentioned environmental parameters can be monitored along with controlling the robotic vehicle with the help of Graphical User Interface(GUI).In order to fulfill the given tasks,we have proposed two algorithms implemented at the robotic vehicle and the distant computer respectively in this paper.The final results validate the proposed algorithms where the above-mentioned environmental parameters can be monitored along with the smooth-running operation of the robotic vehicle.

Digital Evaluation of Sitting Posture Comfort in Human-vehicle System under Industry 4.0 Framework

Most of the previous studies on the vibration ride comfort of the human-vehicle system were focused only on one or two aspects of the investigation. A hybrid approach which integrates all kinds of investigation methods in real environment and virtual environment is described. The real experimental environment includes the WBV（whole body vibration） test, questionnaires for human subjective sensation and motion capture. The virtual experimental environment includes the theoretical calculation on simplified 5-DOF human body vibration model, the vibration simulation and analysis within ADAMS/VibrationTM module, and the digital human biomechanics and occupational health analysis in Jack software. While the real experimental environment provides realistic and accurate test results, it also serves as core and validation for the virtual experimental environment. The virtual experimental environment takes full advantages of current available vibration simulation and digital human modelling software, and makes it possible to evaluate the sitting posture comfort in a human-vehicle system with various human anthropometric parameters. How this digital evaluation system for car seat comfort design is fitted in the Industry 4.0 framework is also proposed.

International Comparison and Enlightenment of the Industrial Policies for the New Energy Vehicles

For a long time, the new energy automobile market has been maintained locally and cannot fonn a mechanism of the market competition. Since this year, the State Council has repeatedly broken this abuse, and the abolition of the local catalogue of the new energy vehicles is the right remedy. In the implementation of the new energy vehicles, it is very important to advance the basic equipment. Compared with the purchase tax preferences, consumers need to improve the basic equipment such as the charging piles and improve the basic access environment. At present, the actual situation of the production and marketing of the new energy automobile industry in our country is that it develops fast but is not perfect, and its output and sales are large but its quality is not good. Behind the initial scale, it is the reality that the overall technical level is not high. We still haven't mastered many core technologies such as batteries, motors, and the electronic control and so on.

New-Energy Vehicle Transmission System Optimization and Design

This paper discusses the optimization and design of the new-energy vehicle transmission systems.Traditional automatic transmission systems suffer from fuel consumption and emissions issues,as well as limitations in the efficiency of mechanical transmission systems.In order to solve these problems,different types of transmission systems are used in new-energy vehicles,including battery electric vehicles(BEV),hybrid electric vehicles(HEV),and fuel cell electric vehicles(FCEV).The key factors for optimizing the transmission systems of new-energy vehicles include battery technology and energy management system,electric motor and electronic control system,energy recovery and reuse technology,and lightweight and aerodynamic design of the vehicle.This paper also introduces methods and tools for designing new-energy vehicle transmission systems,including simulation tools,optimization algorithms and data analysis,as well as experimental verification and testing methods.Besides,new-energy vehicle transmission system designs are proposed,and future challenges and development directions are discussed through case studies.

Mastering the Production of Electric Vehicles as One of the Modern Instruments for the Development of the Iranian Automotive Industry

The article analyzes the problems of introducing electric vehicles,as well as their difference from cars with internal combustion engines.This type of transport has long been included in our everyday life.Today,in the era of the heyday of technology,a person understands that cars with an internal combustion engine(ICE)are almost on the edge of their existence.At present,the development of the production of electric vehicles should be considered as a promising direction of the Iranian automobile industry.At the moment,this market in Iran is not yet occupied by foreign companies,and therefore national companies have a chance to use the strategy of“growth together with the market”.

A Review of Current Research and Advances in Unmanned Surface Vehicles

Following developments in artificial intelligence and big data technology,the level of intelligence in intelligent vessels has been improved.Intelligent vessels are being developed into unmanned surface vehicles(USVs),which have widely interested scholars in the shipping industry due to their safety,high efficiency,and energy-saving qualities.Considering the current development of USVs,the types of USVs and applications domestically and internationally are being investigated.USVs emerged with technological developments and their characteristics show some differences from traditional vessels,which brings some problems and advantages for their application.Certain maritime regulations are not applicable to USVs and must be changed.The key technologies in the current development of USVs are being investigated.While the level of intelligence is improving,the protection of cargo cannot be neglected.An innovative approach to the internal structure of USVs is proposed,where the inner hull can automatically recover its original state in case of outer hull tilting.Finally,we summarize the development status of USVs,which are an inevitable direction of development in the marine field.

AI Based Traffic Flow Prediction Model for Connected and Autonomous Electric Vehicles

There is a paradigm shift happening in automotive industry towards electric vehicles as environment and sustainability issues gainedmomentum in the recent years among potential users.Connected and Autonomous Electric Vehicle(CAEV)technologies are fascinating the automakers and inducing them to manufacture connected autonomous vehicles with self-driving features such as autopilot and self-parking.Therefore,Traffic Flow Prediction(TFP)is identified as a major issue in CAEV technologies which needs to be addressed with the help of Deep Learning(DL)techniques.In this view,the current research paper presents an artificial intelligence-based parallel autoencoder for TFP,abbreviated as AIPAE-TFP model in CAEV.The presented model involves two major processes namely,feature engineering and TFP.In feature engineering process,there are multiple stages involved such as feature construction,feature selection,and feature extraction.In addition to the above,a Support Vector Data Description(SVDD)model is also used in the filtration of anomaly points and smoothen the raw data.Finally,AIPAE model is applied to determine the predictive values of traffic flow.In order to illustrate the proficiency of the model’s predictive outcomes,a set of simulations was performed and the results were investigated under distinct aspects.The experimentation outcomes verified the effectual performance of the proposed AIPAE-TFP model over other methods.

Automated Autonomous Vehicles: Prospects and Impacts on Society

All automobile manufacturing companies, Google and Microsoft have announced recently their production of the Fully Automated Autonomous Vehicles (FAAVs), otherwise known as driverless cars. A few FAAVs would be available in the market as early as in 2018, but mostly in 2020’s. When FAAVs will be available to and become affordable by the average consumers, the implications to the society would be far reaching. The purpose of the paper is to examine the prospect of the popularity of FAAVs and their socio-economic implications to the future society of the World. The paper examines potential impacts on selected sectors of the society including changes in demand for automobiles, its impact on the use of oil, on the environment, and on urban land uses, to list a few.

Use of the AHP Methodology in Vehicle Design Process Dynamics: Determination of the Most Effective Concept Phases for the New Automotive Product

The function of decision-making in the management of new product development and vehicle design activities is achieved by defining, constructing or evaluating the outcome-oriented, and most effective steps from the sub-steps that form this basic process. The choice of the sub-stages of the basic process or the decision of how to do a job gains importance in terms of the efficiency of the firm’s activities. Therefore, the decision making function is one of the basic elements involved in the formation and development of the basic processes that can comply with the market dynamics of firms. With the new product being developed, the selection, the current editing or the evaluation of the steps that make up the vehicle design activities for the automotive industry companies that exist and compete in the market, bring about significant gains. In the manufacturing industry, the design of the vehicle determines the market spread, while the competitive conditions are driven by the new or improved product decision. In both cases, the automotive industry firms must know the stages of the most appropriate vehicle design in their own right, and the steps of forming new project dynamics must be devised in this direction. In this study, the result oriented activity of the current vehicle design phases used in the automotive industry companies is determined and the order of importance of the stages is listed. For this purpose, under the same conditions of competition (the same market, the same class vehicles develops and manufactures), 4 in the automotive firm administration, a total of 40 employees (4 × 10 process manager) with the vehicle design was evaluated by determining the effectiveness of the use of the stage. At this stage, analytic hierarchy methods applied to each of the phases are explored in practice instead of the use of the significance level automotive company. Study of the vehicle design phase of the automotive industry: structure, process modifications or new project reveals the important values to be configured according to the size.

Autonomous Vehicle Technologies Effects the Automotive Concept Design Stages with AHP Method

In the automotive concept design stages, functionally positioning the newly introduced autonomous technologies or remodelling the vehicle accordingly and evaluating the steps or determining the workload together with the collaboration intensity in the current flow is the initial step for the entire process efficiency. Therefore, the main purpose of the research is to reveal the effects of the autonomous technologies, which are newly included in the automotive concept design stages in automotive manufacturing industry companies that continue their lives under heavy competition conditions, according to the order of importance. The objective of this research is to both increase the efficiency of automotive concept design stages and to determine the measurement of the effects of new autonomous vehicle technologies in practice. Under the AHP method used in the research, the automotive concept design stages constitute the alternatives in the order of importance of the working structure, as well as the application variables of autonomous vehicle technologies, the criteria of the mathematical model. In addition, the research method modelled in the study, under the AHP mathematical model, reveals the performances or order of importance of the automotive concept design stages under autonomous technologies. Therefore, the resulting process performances constitute important inputs for efficiency and optimization studies under different research approaches. When the results of the study are examined, due to the high level of influence on the new vehicle concept design performance in automotive industry companies, the adaptation or application steps of autonomous vehicle technologies create new needs in the whole process. The determination of innovation creation clusters in the design process steps or the selection of the density of new technology adaptation in the stages and the order of importance provide a competitive advantage along with optimization in the basic functions of the automotive industry companies. However, the determination of new workload clusters in the mentioned automotive concept design process steps or the effect of autonomous technologies in the design stages, selection, transfer from theory to practice, multiple conflicting criteria and uncertain parameters create a very complex situation. For all these reasons, the Analytical Hierarchy Process (AHP), which is one of the widely used multi-criteria decision-making tools, is considered as a suitable approach for creating such order of importance and solving problems. In this study, an AHP mathematical model was created that determines the workload clusters created by autonomous vehicle technology applications that have just begun to guide the automotive concept design process, which is the main function of automotive manufacturing industry companies. Therefore, in line with the innovations, changes and adequacy criteria created by the current automotive concept design stages in the new autonomous vehicle technology adaptation, a stage order of importance has been selected.

Autonomous Vehicle Design in Lean Product Development Processes for Value Stream Map

The global automotive industry is giving a difficult and common test in order to create advanced life models in the near future plans or scenarios that include current autonomous vehicle technologies. Therefore, the main purpose of the research is to comparatively evaluate the impact of autonomous vehicle technologies, which are newly included in the automotive manufacturing industry under sustainable competition, on lean product development processes, value acquisition and preservation, in different organizational structures in the approach. Although mergers or brand acquisitions in the global automotive industry create joint R & D (Research Development) or joint new P & D (Product Development) process structures for the development of autonomous vehicle technologies, heavy competition continues in the market. These new processes create different needs for the merger and partnership of the renewed traffic infrastructures under national and international regulations, and for the implementation of the new autonomous life model. Firm and brand marriages, mergers or acquisitions in today’s automotive industry have ensured the high diffusion of lean product development processes under the stream of value creation or preservation carried out specific to the company under competition. Brand mergers in automotive industry companies struggling to survive under high competition create new work disciplines, professions, and engineering flow steps in lean product development processes. However, lean product development processes driven by technological innovation under simplification have resulted in the integration of parts and systems within the autonomous vehicle design structure, as well as creating new interdisciplinary value streams or different stakeholders. Therefore, the research revealed the significant effects of lean product development processes on the value stream in the automotive industry, on the mixed and lean product development process structure formed by new or existing vehicle systems (conventional vehicle) under the penetration of each existing and new discipline. This research compares the efficient operation steps of the process stakeholders in the autonomous vehicle design parts or systems containing innovation and new technology together with the value stream in the lean product development process, and the new process stakeholder’s business-oriented global and local automotive industry companies. New autonomous vehicle technologies, together with their unique software, hardware and development analysis, have been involved in the lean product development process with their interdisciplinary studies or expertise. Therefore, the study firstly focused on the technologies in environmental use together with the new basic features of autonomous vehicles, and then examined in depth the new or existing disciplines and interdisciplinary basic structure that these innovations affect under the value stream in the lean product development process. In addition, micro-level results and recommendations were shared, shedding light on how autonomous vehicle levels will create changes in the new product development process.

New Autonomous Vehicle Technologies Effect on Automotive Concept Design Stages

New road transportation systems solutions create significant changes in existing automotive manufacturing industry products and technologies, from design to use. The conveniences within the framework of new approaches brought by autonomous vehicle technologies primarily make individuals transition from driver duty to passenger and high-comfort alternative travel technologies. Therefore, the research: defining the path followed by the autonomous vehicle technologies, which lead to the development of the said new life model and automotive products within the future fiction, in the stages of designing new concept vehicles in practice or measuring the effect on the processes constitute important values for the future prediction of this sector. In addition, the research has focused on the effects of interdisciplinary studies at the automotive concept design stages, which are at the beginning of today’s lean and new product development process, where innovation goals or technologies emerge with more concrete needs. New autonomous vehicle technologies and the main purpose of revealing the interdisciplinary studies created by new disciplines in the current automotive concept design stages make significant contributions to the optimization of the lean product development process and value creation. For this reason, the automotive manufacturing industry, which is on the eve of a major transformation with the said new autonomous vehicle technologies;determining the needs or sustainable position in the flow of digital perception and orientation systems;determining value creation criteria related to the functioning of automotive concept design processes or new acceptance criteria through one-on-one interviews in the field;constitutes the focus of the research. The research has examined the new interdisciplinary studies and effects of new autonomous vehicle technologies in the automotive concept design phase, which is the first step of lean product development, with local and global automotive industry company comparisons in operation. Therefore, the differences and similarities between the concept design stages of global automotive companies that are both co-developers of new autonomous vehicle technologies and manufacturing automotive products and local automotive manufacturing companies that only assemble them determine the future competitive structuring of the industry.

Experimental Vehicles Program Aides in Innovative Hands-on Learning Experiences

The EVP （experimental vehicles program） was created in 2004 as an umbrella program for five different undergraduate experimental vehicle design teams. These projects consist of the Solar Vehicle, Moonbuggy, Baja SAE （sina app engine）, Formula SAE and Solar Boat. The goal of the EVP is to foster undergraduate student development through hands-on construction of experimental vehicles with the guidance of faculty mentors and partnerships with both national and international industry leaders. Each EVP project performs a vital function in the professional development of students. The projects provide a forgiving environment in which students can test their classroom knowledge in a real-world setting and learn important skills such as leadership, effective communication and working as a team member. Furthermore, the students in the EVP develop highly versatile and qualified skill sets that will allow them to fill various positions within the workplace. In the past, 90% of EVP graduates have been able to obtain highly regarded national and international positions upon graduation due to their real-world experience gained throughout their involvement in the EVP. Each year the EVP sponsors up to 60 interdisciplinary students that come together in peer-led teams to combine and expand upon their classroom knowledge in building innovative vehicles. The successes of the MTSU （Middle Tennessee State University） EVP have been recognized by becoming the national model for hands-on engineering education; helping engineering students take classroom knowledge and apply it to real-world situations. Students work to design, construct, and test novel vehicle designs for participation in national and international competitions. Due to the competitive nature of each of the events, students must use cutting edge technology and design methods in order to create the best entries possible. Often times, this means creating partnerships with industry leaders who help mentor the students from the design conception, the fabrication through the manufacturing of each vehicle.

Analysis of Potential Causes of Safety Failure of New Energy Vehicle Power Batteries

The aim of this paper is to analyze the potential reasons for the safety failure of batteries for new-energy vehicles.Firstly,the importance and popularization of new energy batteries are introduced,and the importance of safety failure issues is drawn out.Then,the composition and working principle of the battery is explained in detail,which provides the basis for the subsequent analysis.Then,the potential impacts of factors such as overcharge and over-discharge,high and low temperature environments,internal faults,and external shocks and vibrations on the safety of the batteries are analyzed.Finally,some common safety measures and solutions are proposed to improve the safety of new energy batteries,in hopes of improving the safety of batteries for new-energy vehicle.

面向工业场景的无人机时空众包资源分配

无人机时空众包资源分配是工业物联网能源管理中的重要任务之一.尽管现有方法考虑了联合反映时间敏感性和公平性的信息新鲜度指标,但忽略了无人机禁飞区和窃听者对数据新鲜度的影响.本文提出了一种基于深度强化学习的无人机时空众包资源分配方法,在考虑无人机禁飞区约束和对窃听者发送干扰信号以保障数据安全的情况下,最小化平均信息新鲜度和物联网设备能耗,从而得到最优无人机轨迹、发射干扰信号功率和物联网发射功率.然而,无人机时空众包中的资源分配复杂且存在挑战,主要表现为决策变量类型多且与考虑服务质量要求的系统性能指标关系复杂.本文将该问题建模为马尔可夫决策过程并使用先进的深度强化学习算法求解该问题,即软演员–评论家(SAC)算法.在多无人机场景下验证了所提出算法在解决无人机时空众包资源分配任务中的有效性和正确性.另外,SAC算法相较于其他两种先进的深度强化学习算法,即深度确定性策略梯度算法和双延迟深度确定性策略梯度算法,具有更快的收敛速度和更优的解.最后,分析了最优无人机数目的选择方案.

Overview of Energy and Environmental Issues in the Passenger Automobile Industry

The global supplies of petroleum are on the decline and the dwindling resource has become increasingly difficult to access. Improved technology is increasingly been required to access petroleum that is in hard to reach geographical environments and has chemical composition that is not entirely compatible with existing processing techniques. Alternative energy involves energy from renewable and non-depleting sources such as wind and solar, offer many opportunities for research and development and are been widely developed globally. These sources of energy are expected to reduce the threat of a changing climate, air pollution and oil dependence caused by the automobile industry. There are many economic, environmental and societal benefits of employing various alternative energy sources or options in the passenger automobile industry for motive power. Transitioning from a monoculture of hydrocarbon-based transportation will be just as signify- cant as investments in research and development needed to develop a portfolio of cost-competitive and safe alternative powertrain technologies that can effectively retire the fossil fueled internal combustion engine, without much of any economic stress. In this work, we couple energy and environmental issues to obtain a realistic indication of the future of alternative powertrain technologies for the future of the passenger automobile industry.

Task Offloading Optimization for AGVs with Fixed Routes in Industrial IoT Environment

In order to solve the delay requirements of computing intensive tasks in industrial Internet of things,edge computing is moving from theoretical research to practical applications.Edge servers(ESs)have been deployed in factories,and on-site auto guided vehicles(AGVs),besides doing their regular transportation tasks,can partly act as mobile collectors and distributors of computing data and tasks.Since AGVs may offload tasks to the same ES if they have overlapping path segments,resource allocation conflicts are inevitable.In this paper,we study the problem of efficient task offloading from AGVs to ESs,along their fixed trajectories.We propose a multi-AGV task offloading optimization algorithm(MATO),which first uses the weighted polling algorithm to preliminarily allocate tasks for individual AGVs based on load balancing,and then uses the Deep Q-Network(DQN)model to obtain the updated offloading strategy for the AGV group.The simulation results show that,compared with the existing methods,the proposed MATO algorithm can significantly reduce the maximum completion time of tasks and be stable under various parameter settings.

Optimal Deep Learning Model Enabled Secure UAV Classification for Industry 4.0

Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology that shows attention to the interaction between machine and human beings.In the literature,various authors have focused on resolving security problems in UAV communication to provide safety for vital applications.The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification(CSODL-SUAVC)model for Industry 4.0 environment.The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image classification.Primarily,the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation(ML-DWT),CSO-related Optimal Pixel Selection(CSO-OPS),and signcryption-based encryption.The proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover images.The secret images,encrypted by signcryption technique,are embedded into cover images.Besides,the image classification process includes three components namely,Super-Resolution using Convolution Neural Network(SRCNN),Adam optimizer,and softmax classifier.The integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV communication.The proposed CSODLSUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct aspects.The simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.