Research on a Comprehensive Monitoring System for Tunnel Operation based on the Internet of Things and Artificial Intelligence Identification Technology

This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather events,and movement of tectonic plates.The proposed system is based on the Internet of Things and artificial intelligence identification technology.The monitoring system will cover various aspects of tunnel operations,such as the slope of the entrance,the structural safety of the cave body,toxic and harmful gases that may appear during operation,excessively high and low-temperature humidity,poor illumination,water leakage or road water accumulation caused by extreme weather,combustion and smoke caused by fires,and more.The system will enable comprehensive monitoring and early warning of fire protection systems,accident vehicles,and overheating vehicles.This will effectively improve safety during tunnel operation.

An Intelligent Control Method for the Low-Carbon Operation of Energy-Intensive Equipment

Based on an analysis of the operational control behavior of operation experts on energy-intensive equipment,this paper proposes an intelligent control method for low-carbon operation by combining mechanism analysis with deep learning,linking control and optimization with prediction,and integrating decision-making with control.This method,which consists of setpoint control,self-optimized tuning,and tracking control,ensures that the energy consumption per tonne is as low as possible,while remaining within the target range.An intelligent control system for low-carbon operation is developed by adopting the end-edge-cloud collaboration technology of the Industrial Internet.The system is successfully applied to a fused magnesium furnace and achieves remarkable results in reducing carbon emissions.

A general Boolean semantic modelling approach for complex and intelligent industrial systems in the framework of DES

Discrete event system(DES)models promote system engineering,including system design,verification,and assessment.The advancement in manufacturing technology has endowed us to fabricate complex industrial systems.Consequently,the adoption of advanced modeling methodologies adept at handling complexity and scalability is imperative.Moreover,industrial systems are no longer quiescent,thus the intelligent operations of the systems should be dynamically specified in the model.In this paper,the composition of the subsystem behaviors is studied to generate the complexity and scalability of the global system model,and a Boolean semantic specifying algorithm is proposed for generating dynamic intelligent operations in the model.In traditional modeling approaches,the change or addition of specifications always necessitates the complete resubmission of the system model,a resource-consuming and error-prone process.Compared with traditional approaches,our approach has three remarkable advantages:(i)an established Boolean semantic can be fitful for all kinds of systems;(ii)there is no need to resubmit the system model whenever there is a change or addition of the operations;(iii)multiple specifying tasks can be easily achieved by continuously adding a new semantic.Thus,this general modeling approach has wide potential for future complex and intelligent industrial systems.

Correlation between critical thinking and emotional intelligence:a national crosssectional study on operating room nursing students in Iran

Objective:According to the World Federation of Medical Education,critical thinking should be part of the training of medical and paramedical students.Professionals can improve the quality of care of patients after surgery by having or acquiring this skill in health care.Also,Emotional intelligence is introduced as an impor tant and effective factor on the professional performance and mental health of healthcare professionals.Thus,the present study was designed and implemented to determine the relationship between emotional intelligence and critical thinking among operating room nursing students of medical sciences universities in Iran.Methods:This cross-sectional study was done on 420 operating room students in 10 top medical sciences universities of Iran in 2022.The sampling method in this research was multistage sampling.The data collection instruments included demographic characteristics,Rickett's critical thinking,and Bradberry-Greaves'emotional intelligence questionnaires.After receiving the ethics code,data collection was done for 2 months.For data analysis,descriptive and inferential analyses including independent t-tests,analysis of variance,and Pearson correlation were used.The collected data were analyzed by SPSS 18(IBM Corporation,Armonk,New York,United States).P-value<0.05 was considered significant.Results:The mean age of the students participating in this study was 23.02±3.70 years,with women constituting 67.4%of them.The results of data analysis indicated that the mean total score of critical thinking and emotional intelligence was 124.10±37.52 and 114.12±43.63,respectively.A direct significant correlation between critical thinking and emotional intelligence(r=0.459,P-value<0.001)and a significant relationship between gender and emotional intelligence(P-value=0.028)were found.Conclusions:Based on the present study results,educational managers in the Ministry of Health are suggested to consider suitable educational programs for improving critical thinking and emotional intelligence to enhance the quality of care provided by students in operating rooms.

Intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization

The decision-making method of tunnel boring machine(TBM)operating parameters has a significant guiding significance for TBM safe and efficient construction,and it has been one of the TBM tunneling research hotspots.For this purpose,this paper introduces an intelligent decision-making method of TBM operating parameters based on multiple constraints and objective optimization.First,linear cutting tests and numerical simulations are used to investigate the physical rules between different cutting parameters(penetration,cutter spacing,etc.)and rock compressive strength.Second,a dual-driven mapping of rock parameters and TBM operating parameters based on data mining and physical rules of rock breaking is established with high accuracy by combining rock-breaking rules and deep neural networks(DNNs).The decision-making method is established by dual-driven mapping,using the effective rock-breaking capacity and the rated value of mechanical parameters as constraints and the total excavation cost as the optimization objective.The best operational parameters can be obtained by searching for the revolutions per minute and penetration that correspond to the extremum of the constrained objective function.The practicability and effectiveness of the developed decision-making model is verified in the SecondWater Source Channel of Hangzhou,China,resulting in the average penetration rate increasing by 11.3%and the total cost decreasing by 10%.

Intelligent decision support system of operation-optimization in copper smelting converter

An artificial intelligence technique was applied to the optimization of flux adding systems and air blasting systems, the display of on line parameters, forecasting of mass and compositions of slag in the slagging period, optimization of cold material adding systems and air blasting systems, the display of on line parameters, and the forecasting of copper mass in the copper blow period in copper smelting converters. They were integrated to build the Intelligent Decision Support System of the Operation Optimization of Copper Smelting Converter(IDSSOOCSC), which is self learning and self adaptating. Development steps, monoblock structure and basic functions of the IDSSOOCSC were introduced. After it was applied in a copper smelting converter, every production quota was clearly improved after IDSSOOCSC had been run for 4 months. Blister copper productivity is increased by 6%, processing load of cold input is increased by 8% and average converter life span is improved from 213 to 235 furnace times.

Design and Implementation of a Battery Big Data Platform Through Intelligent Connected Electric Vehicles

The development of a battery management algorithm is highly dependent on high-quality battery operation data,especially the data in extreme conditions such as low temperatures.The data in faults are also essential for failure and safety management research.This study developed a battery big data platform to realize vehicle operation,energy interaction and data management.First,we developed an electric vehicle with vehicle navigation and position detection and designed an environmental cabin that allows the vehicle to operate autonomously.Second,charging and heating systems based on wireless energy transfer were developed and equipped on the vehicle to investigate optimal charging and heating methods of the batteries in the vehicle.Third,the data transmission network was designed,a real-time monitoring interface was developed,and the self-developed battery management system was used to measure,collect,upload,and store battery operation data in real time.Finally,experimental validation was performed on the platform.Results demonstrate the efficiency and reliability of the platform.Battery state of charge estimation is used as an example to illustrate the availability of battery operation data.

Research on Active Safety Methodologies for Intelligent Railway Systems

Safety is essential when building a strong transportation system.As a key development direction in the global railway system,the intelligent railway has safety at its core,making safety a top priority while pursuing the goals of efficiency,convenience,economy,and environmental friendliness.This paper describes the state of the art and proposes a system architecture for intelligent railway systems.It also focuses on the development of railway safety technology at home and abroad,and proposes the active safety method and technology system based on advanced theoretical methods such as the in-depth integration of cyber–physical systems(CPS),data-driven models,and intelligent computing.Finally,several typical applications are demonstrated to verify the advancement and feasibility of active safety technology in intelligent railway systems.

A New Generation of Intelligent Mapping and Remote Sensing Scientific Test Satellite Luojia-301

With the continuous improvement of the performance and the increasing variety of optical mapping and remote sensing satellites,they have become an important support for obtaining global accurate surveying and mapping remote sensing information.At present,optical mapping and remote sensing satellites already have sub-meter spatial resolution capabilities,but there is a serious lag problem in mapping and remote sensing information services.It is urgent to develop intelligent mapping and remote sensing satellites to promote the transformation and upgrading to real-time intelligent services.Firstly,based on the three imaging systems of the optical mapping and remote sensing satellites and their realization methods and application characteristics,this paper analyzes the applicable system of the intelligent mapping and remote sensing satellites.Further,according to the application requirements of real-time,intelligence,and popularization,puts forward the design concept of integrated intelligent remote sensing satellite integrating communication,navigation,and remote sensing and focuses on the service mode and integrated function composition of intelligent remote sensing satellite.Then expounds on the performance and characteristics of the Luojia-301 satellite,a new generation of intelligent surveying and mapping remote sensing scientific test satellite.And finally summarizes and prospects the development and mission of intelligent mapping remote sensing satellites.Luojia-301 satellite integrates remote sensing and communication functions.It explores an efficient and intelligent service mode of mapping and remote sensing information from data acquisition to the application terminal and provides a real service verification platform for on-orbit processing and real-time transmission of remote sensing data based on space-ground internet,which is of great significance to the construction of China’s spatial information network.

Research progress on intelligent operation and maintenance of bridges

In the context of the increasing scale of bridges and the increasing service life of bridges,it is very important to carry out efficient,accurate and intelligent bridge operation and maintenance.In recent years,advanced equipment,technology and intelligent algorithms have developed rapidly.It is necessary to apply advanced equipment and algorithms to bridge operation and maintenance business to facilitate the digitalization and intelligence of bridge operation and maintenance.To grasp the research progress on the bridge intelligent operation and maintenance,this paper summarizes the research progress in recent years from the aspects of intelligent detection equipment and technology,intelligent monitoring equipment and technology,intelligent data analysis,intelligent evaluation and early warning,and intelligent repair and maintenance.According to the review,more and more smart devices have been used to replace human beings to detect dangerous and hidden bridge components.At the same time,image processing,radar and other technologies have been used to analyze component damage more objectively and quantitatively.To solve the shortcomings of traditional sensors such as short life and low robustness,more non-contact measurement methods have been proposed.Scholars have proposed various intelligent algorithms to process the massive amount of bridge health monitoring data to improve the quality of the data.To achieve the rapid perception of bridge status and timely early warning of structural abnormalities,different from traditional theoretical calculations,scholars have tried to use data-driven methods to intelligently evaluate and early warning of bridge structural status.In terms of intelligent repair and maintenance,more intelligent algorithms have been used to optimize structural maintenance strategies and determine the best maintenance time by integrating multisource heterogeneous data.All these provide strong support for the automation,digitization and intelligence of bridge operation and maintenance.

Operation optimization of the steel manufacturing process: A brief review

Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel manufacturing process is essential to reduce the production cost, increase the production or energy efficiency, and improve production management. In this study, the operation optimization problem of the steel manufacturing process, which needed to go through a complex production organization from customers' orders to workshop production, was analyzed. The existing research on the operation optimization techniques, including process simulation, production planning, production scheduling, interface scheduling, and scheduling of auxiliary equipment, was reviewed. The literature review reveals that, although considerable research has been conducted to optimize the operation of steel production, these techniques are usually independent and unsystematic.Therefore, the future work related to operation optimization of the steel manufacturing process based on the integration of multi technologies and the intersection of multi disciplines were summarized.

A Review of the Design and Feasibility of Intelligent Water-Lubrication Bearings

Water-lubrication bearings are critical components in ship operation.However,studies on their maintenance and failure detection are highly limited.The use of sensors to continually monitor the working operation of bearings is a potential approach to solve this problem,which is collectively called intelligent bearings.In this literature review,the recent progress of electrical resistance strain gauges,Fiber Bragg grating,triboelectric nanogenerators,piezoelectric nanogenerators,and thermoelectric sensors for in-situ monitoring is summarized.Future research and design concepts on intelligent water-lubrication bearings are also comprehensively discussed.The findings show that the accident risks,lubrication condition,and remaining life of water-lubricated bearings can be evaluated with the surface temperature,coefficient of friction,and wear volume monitoring.The research work on intelligent water-lubricated bearings is committed to promoting the development of green,electrified,and intelligent technologies for ship propulsion systems,which have important theoretical significance and application value.

Smart City: On Urban Operational Collaboration

This paper expounds the origin of urban operational coordination problem in historical setting, points out that operational coordination problem is essential to cities, induces the major challenges and opportunities for urban operating coordination at present, and takes IBM Intelligent Operation Center as example to illustrate the typical solutions with the detailed case study of the Intelligent Operation Center in Rio de Janerio.

Decision support model for effects estimation and proportionality assessment for targeting in cyber operations

Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under secrecy.As a consequence,limited data(sets)regarding these incidents are available.Although various academic and practitioner public communities addressed some of the key points and dilemmas that surround cyber operations(such as attack,target identification and selection,and collateral damage),still methodologies and models are needed in order to plan,execute,and assess them in a responsibly and legally compliant way.Based on these facts,it is the aim of this article to propose a model that i))estimates and classifies the effects of cyber operations,and ii)assesses proportionality in order to support targeting decisions in cyber operations.In order to do that,a multi-layered fuzzy model was designed and implemented by analysing real and virtual realistic cyber operations combined with interviews and focus groups with technical e military experts.The proposed model was evaluated on two cyber operations use cases in a focus group with four technical e military experts.Both the design and the results of the evaluation are revealed in this article.

Application of Mobile Intelligent Inspection System in Substation Equipment Management

Intelligent inspection is more and more widely applied in all walks of life. This paper introduces the application of the intelligent inspection system in substation equipment management based on mobile phone terminal. It can make the power supply enterprise have more effective means to ensure the safe operation of equipment, improve equipment management level, and improve the economic benefits of power supply.

Intelligent Interfaces: Pedagogical Agents and Virtual Humans

Little by little, we are entering the new era, intelligent interfaces are absorbing us more and more every day, and artificial intelligence makes its presence in a stealthy way. Virtual humans that represent an evolution of autonomous virtual agents;they are computer programs and in the future capable of carrying out different activities in certain environments. They will give the illusion of being human;they will have a body, and they will be immersed in an environment. They will have a set of senses that will allow them: 1) Sensations and therefore associated expressions;2) Communication;3) Learning;4) Remembering events, among others. By integrating the above, they will have a personality and autonomy, so they will be able to plan with respect to objectives;allowing them to decide and take actions with their body, in other words, they will count on awareness. The applications will be focused on environments that they will inhabit, or as interfaces that will interact with other systems. The application domains will be multiple;one of them being education. This article shows the design of OANNA like an avatar with the role of pedagogical agent. It was modeled as an affective-cognitive structure related to the teaching-learning process linked to a pedagogical agent that represents the interface of an artilect. OANNA, has the necessary animations for intervention within the teaching-learning process.

Probabilistic Rationale of Actions for Artificial Intelligence Systems Operating in Uncertainty Conditions

The approach for probabilistic rationale of artificial intelligence systems actions is proposed.It is based on an implementation of the proposed interconnected ideas 1-7 about system analysis and optimization focused on prognostic modeling.The ideas may be applied also by using another probabilistic models which supported by software tools and can predict successfulness or risks on a level of probability distribution functions.The approach includes description of the proposed probabilistic models,optimization methods for rationale actions and incremental algorithms for solving the problems of supporting decision-making on the base of monitored data and rationale robot actions in uncertainty conditions.The approach means practically a proactive commitment to excellence in uncertainty conditions.A suitability of the proposed models and methods is demonstrated by examples which cover wide applications of artificial intelligence systems.

基于数字孪生的智能运维理论体系与实现方法

在建筑行业转型升级的背景下,针对大型建筑运维过程管理效率低、各类运维事件决策分析精度不足、智能化程度有待提高等问题,提出基于数字孪生的智能运维理论体系与实现方法。总结归纳大型建筑智能运维需要采集的信息,分析智能运维亟待解决的问题,融合智能感知与数字孪生技术,给出智能运维运行机理,建立针对大型建筑的智能运维架构体系与多维多尺度的孪生模型。研究建筑智能运维的实现方法,其中包含智能运维全要素信息的采集与传输、智能运维孪生体的构建与运行、智能运维孪生数据的管理机制及智能运维平台的架构。在智能运维理论体系和实现方法的指导下,搭建了智能运维平台,并应用于某大型建筑工程的运维管理。考虑运维管理过程中的虚实交互与时空演化,初步验证了数字孪生在提高运维管理智能化程度方面的有效性。

我国金属矿山智能化现状与问题探讨

我国金属矿山智能化在经历了前期的探索性研究后,已进入了规模化、常态化应用的新阶段。为了系统评价已形成的研究成果、保证前期积累得以顺利移植和推广,以智能生产和集成平台两类代表性应用为主要内容,总结了金属矿山智能化发展现状和应用效果。结果表明:我国金属矿山在智能开采领域取得了长足的进步,露天矿山的遥控铲装运输、地下矿山的电机车自动化、固定设施的无人值守等项目已开始常态化应用;在集成平台建设上具有鲜明的特色,技术平台、安全平台、集控平台和决策平台已在多个矿山的生产管控中发挥作用。最后,结合现状分析着重探讨了矿山在建设内容选择、关键技术确定、数字化转型路径、管理模式转变、运维与应用效果等方面出现的问题,指出了容易产生的误区,为矿山企业扩大建设成果、保证建设实效、规避建设风险提供参考。

基于“一中心四平台”的公立医院后勤运营管理实践研究

目的探讨基于“一中心四平台”的医院后勤运营管理模式成效。方法以医院智慧管理分级评估标准为依据,依托大数据、物联网、互联网+、人工智能等技术运用,打造后勤智慧运维管理中心以及设备管控信息化平台、安全防范信息化平台、能耗监测信息化平台、运营管理信息化平台的“一中心四平台”运营管理模式。结果经过样本医院的管理实践证明:基于“智慧联动”的设备故障处置能力得到显著提升,2022年故障报警次数同比2021年下降28.63%,其中高级、普通报警次数同比2021年分别下降69.53%、33.15%;基于“一站式”的后勤服务保障能力得到显著提升,2022年同比2021年维修次数下降2.92%,维修质量有所提高,反复维修频次降低;基于“数据挖掘”的能耗管控能力得到显著提升,2022年万元收入能耗支出同比2021年下降8.71%。结论“一中心四平台”可以显著提高后勤运维管理水平。