Intelligent-Technology-Empowered Active Emergency Command Strategy for Urban Hazardous Chemical Disaster Management

Abstract

Urban safety production is a core component of social safety and is associated with the production, storage and transport of hazardous chemicals, which are potential sources of disaster in an urban area. Chemicals’ locations in a city present a hidden site of danger, which can easily become disaster sites if supervision is inadequate. Aiming to improve the processes and typical scenarios of the production, storage, transportation and use of hazardous chemicals, this paper proposes an intelligent-technology-empowered active emergency command strategy (ITAECS) for urban hazardous chemical disaster management (UHCDM) in smart–safe cities. This paper aims to provide a strategy for active emergency command that takes into account the disaster source; hidden danger site; or disaster site of hazardous chemicals such as natural gas, gasoline and hydrogen energy based on five aspects: intelligent perception technology and equipment, a dynamically perceived IoT system, the accurate deduction of disaster posture, virtual reality emergency rescue rehearsal and an immersive emergency command platform. This research is conducive to the safety, efficiency and greenness of the whole industrial chain, such as the production, storage, transportation, operation and use of hazardous chemicals. There are difficulties and challenges in introducing ITAECS to urban hazardous chemical production safety and emergency management, such as the need for joint promotion of enterprises, industries and governments; uneven technological development; and several scientific–technological issues to be solved, as well as non-uniform standards. Overall, this paper helps improve the emergency management of urban hazardous chemical safety production.

1. Introduction

With the development of urbanization, the problem of urban public safety is becoming increasingly prominent, and disasters frequently occur [1]. Adopting safety measures is essential in high-hazard industries to reduce risks and environmental impacts [2]. Hazardous chemical safety production is an issue of great concern to countries worldwide [3]. Natural gas, gasoline, hydrogen energy and other hazardous chemicals have flammable, explosive and toxic characteristics in production, storage, transportation and use [4,5,6]. Their leakage, overpressure, high temperature, collision and other abnormal conditions are elementary to malignant disasters such as fires, explosions and environmental pollution [7]. Such disasters often have the characteristics of rapid development, complexity, diversity, a broad range of harm and great destructiveness and can easily cause chain-derived disasters [8]. At the same time, the hidden disaster scenes of hazardous chemical disasters are distributed throughout urban space. Therefore, hazardous chemical disasters seriously endanger urban public safety. Such hazardous chemical disasters include port container explosions, gas station fires, petrochemical transport vehicle collisions and industrial oil and gas pipeline leaks. With the acceleration of industrialization, the worldwide demand for hazardous chemicals has increased and the production and transportation of hazardous chemicals are increasing sharply [9,10]. The security of hazardous chemicals production and transportation is becoming increasingly under pressure and all kinds of malignant accidents frequently occur, resulting in huge losses and adverse effects [11,12,13,14,15]. For example, the container explosion disaster in Tianjin Port caused incalculable economic, social and ecological losses [16,17,18]. Similar disasters include the explosion at Beirut port in Lebanon [19,20,21], the large-scale explosion at a chemical factory in Texas and the ‘3·21‘ tanker explosion at a chemical factory in Jiangsu Province. Yang et al. [22] reviewed standardization construction status, future tasks, problems and sustainable development pathways of smart chemical industry parks in China. There are several concepts related to these events that are important to introduce, as shown in Figure 1. The disaster source refers to the hazardous materials’ source media, storage containers, transport vehicles, transportation pipelines, etc. The hidden danger scene refers to all kinds of scenes throughout the supply chain in which disasters have not yet been developed, such as the production, storage, transportation, operation and use of hazardous goods. The disaster scene refers to the scenes in which disasters have occurred. The production, storage, transportation and use of hazardous chemicals can be seen all over the city and there is uncertainty regarding the owners and participants of each link, which leads to the extensive distribution of disaster information data and use by different organizations. The task of urban hazardous chemical disaster management (UHCDM) is arduous.

Urban emergency management is a complex and multifaceted task involving various management activities from managers and stakeholders to prevent unexpected events, control social damage and eliminate the impacts caused by emergency events [23]. Disaster emergency management is essential to urban governance capacity [24,25]. The requirements of urban safety include strengthening the governance of urban safety, strengthening the urban safety guarantee, perfecting urban safety prevention and control mechanisms, and improving the efficiency of urban safety supervision. When a disaster occurs, due to the lack of timely and comprehensive information on the situation at the source of the disaster, rescuers cannot immediately know what caused the accident and the information pertinent to the scene of the accident, which leads to a blind and passive rescue at the initial stage of the accident. This is not conducive to practical rescue response work. A prompt and accurate prediction of the whereabouts of the hazardous material and a forecast of its dispersion and deposition are essential to enable responders to undertake appropriate mitigation strategies and extract people from affected regions [26]. Huang et al. [27] reviewed prediction methods for emergency management and pointed out that the prediction system for the occurrence of emergency events and resulting impacts are widely recognized, the accuracy of which significantly impacts the efficiency of resource allocation, dispatching and evacuation.

Facing the process and typical scenarios of the production, storage, transportation and use of urban hazardous chemicals, this paper focuses on ITAECS for UHCDM in smart–safe cities to promote their urban emergency management service capacity. ITAECS is the abbreviation of intelligent-technology-empowered active emergency command strategy and is the output of this paper. ITAECS is a theoretical framework with five components: intelligent perception technology and equipment, a dynamically perceived IoT system, an intelligent, accurate deduction of disaster posture, virtual reality emergency rescue rehearsal and an immersive emergency command platform.

2. Literature Review

2.1. UHCDM

Hou et al. [28] reviewed the hazardous chemical leakage accidents and emergency evacuation responses from 2009 to 2018 in China and concluded that the characteristics and the trend of development of the emergency evacuation level in China indicate more cases of hazardous chemical leakage accidents in the coastal areas and suggest that the safety management system and emergency protection actions for hazardous chemical disasters should be discussed and analyzed. Ba et al. [29] point out that the investigations of disaster scenarios rarely systematically address the entire development and response process of multi-hazards, including the coupling mechanisms, evolution dynamics, scenario assessment and emergency response. Emergency rescue for hazardous chemical disasters mainly focuses on post-disaster recovery, disposal and aftermath, focusing on the response and recovery after disasters in the middle and later stages. There needs to be more research on the active emergency management and control of hazardous chemical disasters, especially those that cause significant damage to urban safety. There are also some shortcomings. First, there is a lack of dynamic perception and real-time state control of disaster sources and hidden dangers, as well as a lack of knowledge about what happened and how serious the accident was in its early stage, resulting in weakness regarding the quickness and accuracy of the response and supportability in the early stage [30,31]. Especially in the early stage of disasters, how to efficiently organize and share this disaster information and better assist the emergency rescue is vital. Second, there is a lack of simulation ability to develop disaster situations and on-site rescue. It is unclear how to fully allocate the emergency response force and emergency supplies and whether it is scientific and reasonable, resulting in a passive emergency response and blind rescue after the accident [32,33]. Successful emergency rehearsal can provide ideas for the prevention of safety accidents. Timely emergency disposal must be carried out after a disaster accident to eliminate and minimize the damage as much as possible [34]. Chaudhuri et al. [35] pointed out that disaster management operations are information-intensive due to the high uncertainty and complex information needs; emergency response planners need to effectively plan response activities with limited resources and assign rescue teams swiftly to specific disaster sites with a high probability of surviving. Third, there is a lack of emergency command and decision-making platforms to support cross-regional and inter-departmental coordination, making it challenging to achieve collaborative rescue and emergency command scientifically and efficiently [36]. Given the shortcomings in the disaster prevention and control of urban hazardous chemicals, there is an urgent need for further study to solve these issues.

2.2. Intelligent Technologies for Disaster Management

Intelligent technologies are critical in improving disaster management and control. In recent years, intelligent technologies such as sensors, wireless sensor networks, IoT, Industrial Internet, artificial intelligence, Big Data, machine learning (ML), three-dimensional (3D) simulation, digital twin (DT), unmanned aerial vehicles (UAVs), drones, GIS, 5G, BeiDou positioning and satellite communication have seen rapid development [37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59]. Research on realizing the source governance of urban safety, improving supervision efficiency and guaranteeing capability through intelligent technologies is in its infancy. Zhang et al. [60] studied popular articles published in recent years related to artificial intelligence. They highlighted that the technological and industrial revolution is accelerating via the widespread application of new-generation information and communication technologies. Yigitcanlar et al. [61] proposed the concept of green artificial intelligence towards an efficient, sustainable and equitable technology for smart cities and futures. Abid et al. [62] pointed out that artificial intelligence applications are the technological components of societal change, with significant implications for research on the societal response to hazards and disasters. Chen et al. [63] reviewed the application of computational intelligence technologies in emergency management. They concluded that timely and effective emergency management relies on utilizing observable information and integrating available resources and pointed out that computation intelligence technologies play a vital role during the lifecycle of emergency management in the context of Big Data. Jung et al. [64] designed a conceptual framework of an intelligent decision support system for smart city disaster management to predict and respond to natural disasters in advance by using Big Data collected from an open application programming interface and artificial intelligence algorithms. Lu et al. [65] reviewed the indexed literature on artificial intelligence technologies and machine learning algorithms for disasters and public health emergencies. They concluded that the development and use of AI and ML have increased dramatically over the past few years. Ghaffarian S [66,67] proposed using Google Maps to monitor disaster recovery and combined it with an agent model to model disaster recovery. Although sensors and sensor networks are used to realize hazard source monitoring at the site of disaster sources and hidden dangers, once a disaster occurs, some or all of the sensors on the site will fail and thus compromise the effectiveness of communications. Maraveas et al. [68] indicated that AI offers unlimited potential to prevent fire hazards in farms, but the existing body of knowledge is inadequate. Anbarasan et al. [69] proposed ideas and methods for detecting flood disasters based on the IoT, Big Data and convolutional deep neural networks. Almalawi et al. [70] designed an IoT-based system to magnify air pollution monitoring and prognoses using a hybrid artificial intelligence technique. Rangra et al. [71] aimed to establish an early warning system by integrating the Internet of Things with Social Networks to prevent human causality by issuing early warnings of natural disasters such as rain floods, earthquakes and landslides. Liu et al. [72] designed an IoT-based intelligent geological disaster application using an open-source software framework for collecting and storing geological disaster data, which has specific practical significance.

In terms of disaster sensing, detecting toxic and harmful gases mainly focuses on the realization of highly selective gas-sensing materials for a single gas sensor, which has the problems of cross-sensitivity and poor selectivity [73]. The joint detection of multi-principal gas sensors can make up for this deficiency. Li et al. [74] pointed out that the rapid and accurate determination of the component content of multicomponent mixed gases is of great significance and designed a precise concentration measurement model of multicomponent mixed gases during a disaster. Lyu et al. [75] provided a satellite-based edge computing dynamic warning terminal for hazardous chemical storage and transportation safety. The location of the leakage source is mainly carried out by arranging many fixed sensors. Chen et al. [76] proposed using a multi-robot active olfaction method to locate time-varying contaminant sources and pointed out that quickly finding disaster sources is a prerequisite for effective source control and a fundamental basis for further evacuation and emergency rescue guidance. Edge-intelligence-assisted detection methods based on deep convolutional neural networks can be used for hazardous chemical disaster smoke detection [77]. Location accuracy cannot be guaranteed in a disaster environment. Fire inspection mainly includes fire source identification and location through UAVs with thermal imagers or remote sensing cameras, which are vulnerable to environmental interference. The trend of the future is to carry a variety of sensors and use various mobile platforms to sense and monitor the scene.

In terms of monitoring urban disaster sources and hidden dangers, the application of intelligent and visual means needs to be improved. An early warning system is a core IoT information system for disaster risk and effect management [78]. Some scholars have addressed this problem and proposed some solutions [79,80,81,82]. There are still critical technical problems in active emergency rescue. The first problem is realizing the coordinated operation of smart sensor terminals and mobile robots for urban hazardous chemical disaster site detection, positioning and data transmission with the integration of heaven and Earth [83]. The second problem is the need for more aggregation of the whole industrial chain and the whole scene of disaster sources. Li et al. [84] aimed to apply DT technology to the entire process of handling and transportation of hazardous chemicals to help improve the anti-risk ability of road networks at all levels. Khan et al. [85] indicated that a focused and comprehensive solution is needed, encompassing all aspects, including the early detection, prevention, recovery and management of disaster scenarios to minimize losses. They presented a critical analysis of the existing methods and technologies relevant to a disaster scenario, such as WSN, remote sensing techniques, artificial intelligence, IoT, UAV and satellite imagery, to resolve the issues associated with disaster monitoring, detection and management. Thus, more is needed to visualize the location, status and safety of disaster sources in the entire urban area and support the requirements of urban emergency management. Building a dynamic monitoring and real-time sensing IoT system is necessary to meet the public safety management requirements of the hazardous chemical industrial chain and the whole scene in urban areas.

Regarding intelligent deduction technology for hazardous chemical disasters, some disaster scenario deduction models and high-tech monitoring schemes for disaster state dynamic monitoring, have been proposed and used. However, the models and schemes rarely consider the environment’s multi-parameter and multi-constraint boundary conditions. Event scenarios serve as the basis for making emergency decisions after sudden disasters and the accuracy of scenario deduction directly determines the effectiveness of emergency management implementation. Xie et al. [86] indicated an efficient and effective scenario deduction model integrated with a dynamic Bayesian network, evidence theory and emotion update mechanism for an exceptionally heavy rainstorm disaster in Zhengzhou. Men et al. [87] developed an event-driven disaster chain evolution system, of which a Markov decision process and a temporal-difference learning algorithm formulate the system state transition. Xu et al. [88] proposed a disaster chain model to analyze the evolution process from a gas leak to an explosion. Men et al. [89] reviewed multi-hazard coupling effects in the chemical process industry in which the existing methodologies on different topics related to multi-hazard coupling effects are especially concerned and indicated that the related research is still in its infancy and that it is a fertile field for future research.

Regarding emergency rescue virtual reality simulation rehearsals, emergency rehearsals based on a 3D virtual environment have attracted more and more attention. There have been some research results or commercial products, but they must be more mature. Li et al. [90] pointed out that there is an increasing demand for simulation training systems that use virtual reality, augmented reality and mixed reality visualization technologies, and the simulation training system provides a new method for popular emergency avoidance science education and emergency rescue personnel to master work responsibilities and improve emergency response capabilities. Yu et al. [91] pointed out that many studies have applied intelligence technologies to solve rescue and recovery; however, systematic construction still needs to be improved. DT is one of the most promising technologies for multi-stage management, which has great potential to solve the above challenges. Yu et al. [92] indicated that integrating virtual reality and building information modeling can improve highway tunnel emergency response training. Tian et al. [93] provide a new multi-objective scheduling model for extinguishing forest fires, which considers rescue priority with limited rescue resources. Ahmadi et al. [94] introduced a new robust decision support framework for planning search and rescue resource deployment in post-disaster districts. Zhou et al. [95] proposed a timed colored hybrid Petri net approach to solve multi-department collaborative emergency response problems in chemical industry accidents. Chen et al. [96] indicated a multi-agent simulation approach in which chemical plants are modeled as a multi-agent system with three kinds of agents—hazardous installations, ignition sources and humans—while considering the uncertainties and interdependencies among the agents.

Regarding emergency command platforms, researchers attach great importance to constructing digital emergency plans and improving emergency management. Zhang et al. [97] presented a survey of emergency planning technologies based on AI, discussed their applications in making emergency planning robust and efficient and indicated that AI provides advanced analytics tools for processing and analyzing Big Data for emergency management. Lee et al. [98] expanded on the practicality and effectiveness of utilizing AI as an advisory platform for disaster response based on Big Data and designed an AI advisor platform for disaster response with Big Data-based algorithms. Aboualola et al. [99] indicated that the emergency management platform should use social media data as a data source of the platform and combine it with the data perceived by the edge-aware IoT system. Liu et al. [100] presented UrbanKG, an urban knowledge graph system incorporating a knowledge graph with urban computing. Bai et al. [101] proposed a novel risk assessment model integrating a knowledge graph, decision-making trial and evaluation laboratory. Liu et al. [102] proposed a novel method to help detect marine oil spills by constructing a multi-source knowledge graph. However, the process and mechanism of dynamic, collaborative disposal and multi-functional departments are still being explored. Digital emergency plans need to be improved to realize structural representation and multi-category storage of text emergency plans, intelligent retrieval and browsing of emergency plans, perfect preparation template and emergency knowledge base, and manage the plan with relevant institutions and personnel. Realization of the emergency plan’s structure, digitalization and intelligence is urgent.

It is the inherent necessity of disaster emergency management that it promotes the modernization of the emergency management capacity with intelligent information technology, enhances early risk identification and early warning from the source, and effectively uses innovative technologies to prevent and resolve serious security risks at any or all stages of the disaster cycle. How to formulate effective management strategies and practices through the integration and innovation of these emerging intelligent technologies, how to achieve the source governance of urban safety and how to improve regulatory efficiency and guarantee capacity are the current problems that need to be solved.

3. ITAECS Theoretical Framework for UHCDM

The theoretical framework of ITAECS is shown in Figure 2. ITAECS aims at fire, explosion, leakage and other urban disasters that can occur in producing and storing hazardous chemicals. It can make up for the current situation, wherein emergency rescue services for disasters are mainly focused on post-disaster recovery and disposal. Its primary function is to provide scientific, reasonable and feasible solutions to problems. These problems include a lack of control over the state of disaster sources, a lack of data control over disaster sites, a lack of accurate detection and location of accident sources, a lack of scientific means of disaster chain analysis, insufficient ability to predict and deduce the development situation after disasters, inadequate data governance and digital emergency plans and a lack of coordination and synthetic intelligence.

ITAECS is conducive to constructing an intelligent, active emergency management and command system for urban hazardous chemicals with the characteristics of perception, connection, knowledge mining, application and integration. These components in ITAECS are introduced as follows: First, intelligent perception technology and equipment refers to intelligent sensor monitoring terminals (ISMT), core sensors and mobile intelligent security sensing equipment (ISSE) for IoT data acquisition. Second, the dynamically perceived IoT system is a system that integrates intelligent sensing technology and equipment, information platforms and visualization systems and has the capacity for information collection, analysis and processing, early warning and visual presentation. Third, the intelligent–accurate deduction of disaster posture refers to the ability to deduce and predict the expected situation of disaster development effectively in the gestation period or the initial stage of disasters to provide data support for emergency rescue personnel to make effective emergency rescue plans. Fourth, virtual reality emergency rescue rehearsal means a series of work, including simulating disaster accidents, designing virtual reality disaster scenes and emergency rescue plans, testing the emergency rescue effect of disasters and accidents and constantly optimizing emergency rescue schemes under different disaster and accident scenarios. Therefore, in the case of hazardous chemical disasters, emergency rescue personnel can better and more quickly take effective emergency rescue measures. Finally, the immersive emergency command platform means that emergency commanders can understand the disaster and accurately grasp the emergency rescue resources through the information platform as if they are at the disaster scene. In this way, they can command rescue personnel to mobilize emergency rescue resources, achieve active emergency command and resolve disasters fully and effectively. The detailed design is as follows.

3.1. Strategy of Intelligent Perception Technology and Equipment for UHCDM

To provide equipment and technical support for the panoramic sensing monitoring and emergency response of hazardous chemical disasters, critical technologies such as the reliable identification of harmful gases, the tracing and positioning of toxic gases, an ad hoc network and a coordinated group operation need to be established [103]. Intelligent safety sensing devices with specific environmental adaptability need to be developed. These devices support ad hoc networks and group-coordinated operations to realize multi-point decentralized delivery to identify harmful gases [104]. The ISMT is used to perceive various statuses of hazardous chemicals in disaster scenes and hidden danger scenes, including leakage, pressure, liquid level, smoke, temperature, image, video and location. The sketch map of intelligent perception technology and equipment strategy is shown in Figure 3.

3.1.1. Core Sensors

The quality of sensitive materials directly affects the sensor’s sensitivity, selectivity and reliability [105]. The design, preparation, synthesis and screening of sensitive materials must study the interaction mechanism between the target object and sensitive materials [106]. For the physical and structural design of the sensor, it is necessary to perform certain actions. The first is researching the sensor body’s structural design and optimization technology with different detection principles [107]. The second is to break through the on-chip array integration technology of multi-principal sensors and the controllable loading technology of sensitive materials [108]. The third is to realize the consistency of sensitive performance, process compatibility and batch manufacturing capacity of the sensor. The software design of sensors needs to study the joint detection mechanism and intelligent algorithm of sensors with different principles to realize the reliable identification of target objects [109]. The appearance of the sensor requires research on the sensor’s packaging protection and reliability technology to meet the application requirements of different disaster scenarios [110].

3.1.2. Intelligent Sensor Monitoring Terminals (ISMT)

The ISMT requires the study of several aspects. The first is the standardization and personalization of the sensor interface of intelligent sensor terminals for 4G, 5G, LTE-Cat1, NB-IoT, satellite communication and other transmission layer technologies [111]. The second is data communication mechanisms to realize the adaptive transmission of a multi-mode communication network and ensure communication reliability with the data platform [112,113]. The third is system integration technology to realize the positioning and communication between intelligent terminals and UAVs [114]. Data security communication technology between the communication terminal, sensor monitoring terminal and Big Data platform supports urban public safety needs. The working mechanism and power supply configuration of the intelligent terminal can realize the low-power design of the intelligent terminal to meet the requirements of being waterproof, explosion-proof and having intrinsic safety in disaster application scenarios. The working mechanism of the communication terminal and communication ad hoc network ensures that the ad hoc network of the communication terminal can still work normally in cases of abnormal single-point communication.

3.1.3. Mobile Intelligent Security Sensing Equipment

Mobile intelligent security sensing equipment integration mainly aims to develop and integrate ISSE, such as UAVs, with sensing, detection and wireless networking functions for different hazardous chemical disaster scenarios. This equipment has the characteristics of a variable structure, portable belts, flexibility, etc. [115]. For the daily patrol inspection of the potential hazards of hazardous chemical disasters, mobile intelligent sensing equipment is required to conduct patrol inspection in the task area and pass through the areas to be inspected [116]. The process involves constraints such as hazardous chemical consumption and task balance. At the same time, it is necessary to meet the timeliness requirements of task completion and eliminate the interference of uncertain factors on the patrol inspection task. Therefore, building an inspection mixed-integer programming model with both economy and security is necessary [117]; designing an efficient–intelligent algorithm and combining it with GNSS is essential to realizing the inspection and location of autonomous mobile fire sources in hazardous areas [118]. Disaster scope assessment and emergency rescue teams must find the gas leakage source quickly and accurately at the disaster site to detect and locate toxic gas leakage sources. The mobile sensing of ISSE via multi-point delivery, self-networking and group coordination with fixed intelligent sensing monitoring terminals is needed. It is feasible to detect and accurately position a toxic gas leakage source using concentration data acquisition, a gas olfactory algorithm and multi-sensor data fusion technology to trace the source of toxic gas leakage [119,120,121].

3.2. Strategy of the Dynamically Perceived IoT System for UHCDM

The dynamically perceived IoT system of urban disaster sources and hidden dangers is the essential technical guarantee for source governance, emergency command and decision making of hazardous chemical disasters. It is suitable for real-time visualization of dynamic monitoring and sensing of disaster sources, hidden danger sites or disaster sites. At the same time, it provides services for the safe production and precise operation of enterprises with potential hazards. The system is used to access various sensing and monitoring equipment for disaster sources, hidden danger sites and disaster sites to obtain the status, location and environmental information of urban disaster sources, hidden dangers and disaster sites [122]. Moreover, tilt photogrammetry real-3D map visualization and DT technology can realize the visualization and transparency of hazardous chemical disaster sources and disaster sites [123]. The system comprises sensors, ISMT, mobile sensing equipment, communication networks, middleware, significant data platform architecture and service interfaces. The sketch map of the dynamically perceived IoT system strategy is shown in Figure 4.

3.2.1. Multi-Source Heterogeneous Security-Aware Data Integration and Fusion

The information integration and fusion technology of multi-source heterogeneous data collection, analysis, processing and release need to be researched to obtain the real-time monitoring data of intelligent sensing terminals such as gas, temperature, pressure and liquid levels of hazardous chemical disaster sources and hidden danger sites in an accurate and timely manner. Then, this tool can provide data support for adaptive identification and early warning of hazardous chemical disasters and subsequent post-disaster disposal. Since the collected, dynamic monitoring data may come from sensors with different locations, times, types and accuracies, the integrated data processing includes four steps: first, the wrong or abnormal data need to be cleaned; second, spatial and temporal correlation based on multi-sensor data must be performed; third, multi-sensor data can be processed using statistical and probability-based methods and reasoning and learning algorithms to obtain perceptual data with a unified spatiotemporal reference and unified quality standard; finally, the processed results can be stored in the Big Data platform for disaster disposal or the safe operation of enterprises [124]. Because the distributed multi-source heterogeneous monitoring terminal usually completes the field data collection, it is necessary to build modular and portable middleware to solve the critical problems and ensure the flexible, reliable and efficient integration of multi-source heterogeneous data [125]. These problems include data security verification, quality inspection, conversion of data and message queue processing. The IoT middleware technology based on service quality control is a software layer in the system [126]. It can provide standard data services to the upper application through service, management and control functions to shield the differences between perceived devices. When the quality-of-service middleware cannot meet the quality requirements, the dynamic negotiation mechanism will control the sensing device to meet a certain quality of service.

3.2.2. Real-Time Monitoring Digital Map of Disaster Source and Hidden Danger Site

The dynamically perceived IoT system must aggregate the monitoring systems of various disaster sources and hidden danger sites in the city to form a dynamic real-time digital map of urban distributed disaster sources and hidden danger sites [127]. Through one map, emergency management personnel can obtain the IoT data of all security sensing terminals in the concerned area to provide an intuitive human–computer interaction interface to master the on-site security situation anytime and anywhere. Realizing a digital map for dynamic real-time monitoring of hazardous chemical disasters requires the study of several aspects: constructing a disaster site database, 3D modeling of disaster sites based on tilt photogrammetry, dynamic monitoring perception data based on DT and visualization of a security situation [128,129]. The disaster source and hidden hazardous scenes of hazardous chemical disasters can be displayed in the dynamic real-time monitoring digital map through 3D visualization technology such as scene modeling based on a 3D geographic information system and tilt photography. The dynamic real-time monitoring digital map is connected to the real-time data of the IoT. Then, the real-time location, status data, security situation of various sensing devices (including fixed deployment sensing terminals and mobile safety sensing equipment), mobile disaster sources (such as hazardous chemical transport vehicles) and rescue devices are displayed in the 3D map. A 3D map display system based on a Web browser should be developed to facilitate access to real-time monitoring of digital maps from various terminal devices and reduce the dependence on large-scale professional GIS software and hardware equipment.

3.2.3. Safety Early Warning Model of the Hazardous Chemical Disaster Site

The safety early warning model collects data through sensors, compares the industry-agreed requirements, tests the difference between the experimental threshold data and determines whether it is abnormal based on the difference. Based on the multi-sensor acquisition terminal and different environmental conditions, different abnormal information thresholds are constructed to cover the disaster sources and real-time early warning information under varying working conditions. Due to seasons, environment and weather, the early warning threshold for hazardous chemical disasters changes dynamically. Therefore, it is necessary to conduct regression analysis on disaster risk factors and establish an adaptive risk identification and early warning model for different types of disasters to provide early warning information for emergency disposal in time [130,131]. In addition, the equipment performance will also change over time, so it is necessary to master the adaptive and self-correcting model method to dynamically adjust the early warning threshold of the system to have sufficient time to deal with possible risk problems in advance. The research contents include adaptive risk threshold evaluation of different hazardous chemical disasters, regression analysis of hazardous chemical disaster risk factors and a multi-parameter fusion security adaptive identification and early warning model algorithm [132]. Finally, the on-site dynamic monitoring, prediction and early warning of disaster sources and hidden dangers can be realized by sensing IoT systems and digital maps.

3.2.4. Data Connection and Linkage Mechanism between on-Site Enterprise and Government Command

Urban disaster management needs to change the traditional model, with the government as the single subject, and further integrate the on-site perception data of the society, especially the enterprise, to enable the government emergency management department to better allocate resources for disaster disposal and rescue. At the site of a hazardous chemical disaster, enterprises often assess the site’s disaster situation first. Therefore, the data linkage of disaster sources and hidden danger of the on-site enterprise and emergency management remote government is significant [133,134]. Thus, interface technology should be developed between the on-site enterprise and the command government, including the enterprise and government interfaces. The government interface sends the relevant data in the IoT system to the commanding government end, and the enterprise interface sends the relevant IoT perception data on the cloud platform to the enterprise end.

3.3. Strategy of the Accurate Posture Deduction for UHCDM

The accurate posture deduction of the disaster situation requires consideration of three aspects. First, the evolution law of disaster dynamics and its influencing factors, the characteristic identification and diagnosis methods of urban hazardous chemical disasters and the dynamic monitoring mechanism and monitoring perception scheme based on significant disaster sources and hierarchical supervision relying on the IoT system. Second, the deduction model and method of hazardous chemical disaster situations relate to the coupling law of accident and disaster scenario elements, multi-source heterogeneous Big Data and system state dynamic parameters [135]. Third, the disaster intelligent early warning strategy is based on the damage mechanism of disaster-carrying carriers in a hazardous chemical disaster scenario [136]. The sketch map of the accurate deduction strategy for hazardous chemical disaster posture is shown in Figure 5.

3.3.1. Life Cycle Dynamic Monitoring Perception Method of Hazardous Chemical Disasters’ Spatiotemporal Evolution Characteristics

The evolution of a disaster life cycle refers to the entire development process of the disaster, including gestation, occurrence, development and elimination. The dynamic monitoring and sensing methods of temporal and spatial evolution characteristics of hazardous chemical disasters in the life cycle include the scenario disaster chain model, dynamic evolution law and comprehensive monitoring and sensing scheme [137,138,139]. The construction of a hazardous chemical disaster chain model needs to be induced by scenario structural elements [140]. Its premise is establishing a hazardous chemical disaster scenario database by determining the initial and target scenarios. It is necessary to use scenario representation to express the characteristic scenario elements, structural elements, constraint elements and attribute elements of disaster chain scenarios to improve the disaster scenario accident chain [141]. The dynamic evolution law of hazardous chemical disasters includes establishing the key parameter system for disaster situation deduction and blocking the propagation of the disaster chain, establishing the sample database of crucial parameters of multi-disaster scenarios, obtaining the temporal and spatial evolution characteristics of key parameters under scenario constraints and forming the dynamic model of each scenario element on the disaster chain under environmental constraints. The design of a comprehensive monitoring and perception scheme for hazardous chemical disasters includes determining the hardware equipment of dynamic monitoring systems, such as data acquisition and transmission modules for monitoring key parameters, in combination with the development path and behavior model of the accident chain and putting forward selection method technical requirements. Then, users can use the evolution law and temporal and spatial characteristics of the occurrence and development of hazardous chemical disasters, couple the dynamic evolution characteristics of key parameters under different scenario constraints and explore the optimal spatial layout method of essential parameter dynamic monitoring devices based on the coverage of the wireless monitoring network and the connectivity of nodes. Moreover, a mathematical evaluation model of subjective and objective factors on the impact level of disasters should be constructed and a dynamic monitoring scheme for disaster sources and hierarchical supervision should be designed.

3.3.2. Deduction Model for Hazardous Chemical Disaster under Multi-Source Heterogeneous Big Data Fusion

The temporal and spatial evolution law of hazardous chemical disasters state parameters and the structured representation method of disaster scenarios are related to regional factors, system operation and maintenance, historical accidents and other data. Therefore, it is necessary to comprehensively consider disaster-pregnant environments, disaster-causing factors and disaster-bearing carriers. The transitivity and transferability between disaster scenario nodes can be analyzed using the event tree, interpretation structure model, etc. [142,143]. The scenario network structured model of a typical single disaster, coupled disaster and secondary derivative disaster can be generated based on the causal, derivative and coupling relationship between disaster potential risk factors. The feature extraction of disaster-causing factors of hazardous chemical disasters can be realized using principal component analysis, cluster analysis and other methods. The comprehensive situation deduction model of disaster scenario evolution is used to discover the dynamic analysis of the disaster transmission path under the influence of different emergency rescue scenarios and the spatiotemporal evolution prediction of the initial disaster outbreak point, secondary derivative disaster point, disaster calm point and disaster extinction point in the situation scenario evolution path. This requires the combination of single disaster, coupling disaster and secondary derivative disaster scenario probability quantitative models; the modeling and simulation of hazardous chemical disaster situation scenarios are achieved using system dynamics and dynamic Bayesian methods [144], as well as the disaster situation scenario network dynamic reasoning update method after integrating the on-site sensor data and the real-time data of emergency assistance.

3.3.3. Intelligent Early Warning Strategy of Hazardous Chemical Disasters Based on Damage Mechanism of Disaster Carrier

Due to the change from risk to disaster and the different critical conditions of disaster carrier damage under the action of disaster-causing factors of varying frequency and intensity, it is necessary to reveal the damage mechanism of disaster carriers in a hazardous chemical disaster scenario. Considering the damage mechanism, situation research judgment and critical nodes of the state deduction path of the disaster-bearing carrier in hazardous chemical disasters, early warning needs to be combined with the damage mechanism of the disaster-bearing carrier for hierarchical early warning. Realizing hierarchical early warning of hazardous chemical disasters based on multi-source heterogeneous dynamic monitoring data requires establishing a disaster carrier situation assessment and early warning model using a fuzzy comprehensive evaluation method [145]. Moreover, it also requires methods such as pair analysis, probabilistic neural networks and disaster security assessment [146]. Establishing an early disaster warning countermeasure database integrating the characteristics of early warning information, early warning form and early warning scope requires the basic paradigm of emergency management based on the scenario response. The early disaster warning information feedback to the government, enterprises and other disaster control subjects should consider efficiency, convenience and classification. Moreover, developers need to integrate the disaster events’ secondary and derivative characteristics. The release channels to organizations, individuals and other disaster-bearing objects are the same.

3.4. Strategy of Virtual Reality Emergency Rescue Rehearsal for UHCDM

Facing an urban hazardous chemical disaster based on the multi-level disaster simulation model, the modular rapid modeling technology of a 3D disaster scene needs to be developed. Additionally, emergency rescue decision-making simulation and optimization techniques, such as emergency evacuation and resource allocation, need to be developed to realize emergency decision evaluation and optimization under the constraints of resources and external conditions. Then, the immersive simulation rehearsal technology of multi-view emergency rescue needs to be developed based on multi-agent and artificial intelligence methods. Next, the 3D simulation rehearsal system of virtual reality emergency rescue needs to be constructed [147]. The system can provide emergency rescue simulation rehearsal of urban disasters for scenes of fires, explosions and leakage accidents. The system can improve the effectiveness and scientificness of emergency rescue rehearsal based on access to real-time disaster monitoring data or prediction data. The specific method adopted helps to realize the intelligent emergency rescue exercise and effect evaluation in the non-disaster state and the scheme deduction and decision support of emergency rescue and command in the disaster state. The sketch map of the virtual reality emergency rescue rehearsal strategy for UHCDM is shown in Figure 6.

3.4.1. The 3D Dynamic Virtual Scene Modeling Strategy

Three-dimensional virtual reality scene research needs to be carried out with regard to several aspects. Historical data and data on urban hazardous chemical disasters need to be collected. Based on the accident cause theory, the boundary condition setting method of human, material, environment and system in the initial state of the accident needs to be studied so that the design of the initial state of the disaster scene is realized. The modular disaster scene editor needs to be developed and its function setting and architecture should be studied. Based on Unity3D and other platforms, functional modules such as terrain editing, entity editing, meteorological simulation and scene management need to be developed, which support the controllability and reusability of disaster scene modeling elements and have efficient scene editing functions for urban disasters [148]. Based on the multi-level simulation model, the 3D modeling and visualization of emergency elements of hazardous chemicals need to be carried out. Based on the disaster evolution law of urban hazardous chemicals, the 3D visual expression method of the action of disaster elements on the disaster-bearing carrier needs to be explored. Fluid, flame, explosion, smoke and special effects should be modeled and simulated using 3D modeling. The function of setting and adjusting key parameters needs to be developed. Finally, the dynamic 3D model construction and visualization of multi-level disaster scenes such as liquid and gas hazard source leakage, diffusion, fire and explosion should be realized. At the same time, it is necessary to study the evolution characteristics of the disaster behavior of vehicles, personnel, equipment, buildings and infrastructure under the influence of disasters and develop an adaptive 3D model expression method of dynamic behavior interaction in disaster environments.

3.4.2. Simulation and Optimization of Emergency Rescue Decisions

First is the emergency evacuation plan and resource scheduling optimization. Based on the medium and micro traffic simulation and pedestrian simulation model, it is necessary to study the emergency evacuation simulation and evacuation scheme optimization method of large-scale transportation systems under the influence of emergency rescue. The technique of crowd evacuation simulation and evacuation plan optimization should be studied for the affected area [149]. The demand prediction, allocation strategy, configuration optimization method and model method of different types of emergency rescue resources should be studied under various disaster scenarios [33,150]. The emergency resource scheduling path and resource allocation scheme generation should be checked with the emergency evacuation simulation model. Second, for the emergency rescue decision making multi-objective optimization and knowledge base construction, based on the historical disaster case data, it is necessary to construct the prototype of emergency rescue decision knowledge bases, put forward the evaluation index system method of the disaster risk emergency rescue effect and refine the decision variables and their function space of emergency rescue [151]. Based on the disaster situation deduction model, the rapid generation of emergency rescue decision-making objectives based on the disaster risk potential and spatiotemporal situation needs to be studied [152]. Considering the constraints of human resources, material resources, environmental conditions and social conditions, the optimization model of emergency rescue decision schemes needs to be constructed based on a simulated annealing algorithm, genetic algorithm and deeply enhanced artificial neural network [153,154,155]. The optimal value of emergency rescue decision variables under different conditions needs to be determined and the knowledge base of emergency rescue decision making needs to be optimized.

3.4.3. Multi-View Intelligent Simulation Rehearsal and Evaluation Strategy of Emergency Rescue

First is the multi-perspective disaster response and emergency rescue simulation rehearsal based on multi-agent scenarios. The differences and regularity of the decision-making behavior of subjects need to be studied from different perspectives in the process of typical urban disaster development and emergency rescue [28,156]. Learning the multi-level emergency command’s role and information transmission mechanism is particularly applicable [157]. Based on system dynamics, multi-agent simulation and artificial intelligence technology, a multi-view simulation rehearsal model for emergency rescue needs to be constructed to realize the intelligent interaction between actual personnel, virtual personnel and the emergency rescue command process. Second, verifying the scientific nature of the emergency decision knowledge base based on simulation deduction is necessary. The evaluation index system of emergency rescue effects must be supplemented and improved. Additionally, based on the results of the simulation rehearsal, it is essential to comprehensively evaluate the decision-making effect of decision makers at all levels in the emergency rescue process. Finally, the architecture and functional modules of the virtual reality simulation rehearsal system should be developed to improve the system’s functionality.

3.5. Strategy of Immersive, Active Emergency Command Platform for UHCDM

The strategy of the immersive, active emergency command platform includes the construction of a data center; the development of an immersive urban disaster emergency command and control platform; the realization of smooth man–machine cooperation; and the realization of four-level equipment linkage, communication linkage, data linkage, application linkage and the accompanying command of the city, district, street and enterprise. The application and demonstration of urban hazardous chemical disaster active emergency command throughout the supply chain scene require systematically integrating various technologies. These technologies include the immersive, active emergency command platform, IPTE, dynamically perceived IoT system, posture-accurate deduction system, virtual reality emergency rescue rehearsal and the formulation of effective application schemes and related technical standards and specifications. The integrated application sketch map of immersive, active emergency command for UHCDM is shown in Figure 7.

3.5.1. Integrated Emergency Management Linkage Coordination and Auxiliary Decision-Making Mechanism

First, the research on the linkage coordination mechanism and information-sharing mechanism includes studying the coordination and linkage mechanism of emergency management systems; establishing a dynamic, collaborative command and disposal mechanism across regions, departments and levels; solving the process mechanism of ‘when and how to interact with whom’; and studying the information-sharing mechanism of emergency management across regions and departments. Second, data governance research and AI data development include the development of an AI data center based on a knowledge graph, breaking through the defect of passive data collection, starting from emergency management expert knowledge, actively obtaining data from related systems through the structured knowledge model; forming effective data sources according to knowledge graph processing to solve the critical data quality problems in data governance; and studying the IT architecture and data governance interface standards to achieve effective and adequate comprehensive emergency data management, form effective sharing linkage of cross-departmental information and improve the efficiency of urban safety supervision. Third, emergency planning digital technology and decision knowledge include research on the emergency plan modeling method, the semantic data modeling method based on ontology, the construction of plan and knowledge base ontology and the formation of a digital emergency plan system to construct an emergency plan and decision knowledge base supported by a disposal plan, emergency care, emergency knowledge and laws and regulations to meet the emergency decision support service of an urban emergency. It is necessary to develop the emergency resource demand forecasting model and optimal scheduling model based on scheduling efficiency and to provide the optimal scheduling intelligent scheme of emergency resource demand and supply. This can meet the rapid scheduling and cross-domain coordination of emergency materials and rescue equipment relative to life, work and medical in urban disasters.

3.5.2. Development of Immersive, Active Emergency Command Platforms

First, with the goal of ‘comprehensive perception of one picture, one button to know the overall situation and integrated operation,’ it is necessary to develop an immersive urban disaster active emergency command and control platform to realize five functional modules: data service, emergency response, situation research and assessment, and rescue command and situation summary. It is necessary to construct the full-service and full-process application of emergency management, such as comprehensive gathering, rapid display, uploading and downloading, collaborative consultation, thorough research and judgment, command and dispatching, auxiliary decision making and accompanying command, and on-site information collection. It is necessary to realize the visualization of perception, monitoring, analysis, decision making, scheduling and emergency disposal on the map. Second, it is essential to study the AI engine technology driven by multi-task and multi-level linkage decisions and develop an AI engine driven by multi-task and multi-level linkage decisions that can achieve efficient and orderly transmission of rescue instructions and cooperative operation of the emergency management module. The AI-enabling engine ensures stable, reliable, safe, intelligent and smooth man–machine cooperation and supports active urban disaster prevention, control and emergency command. Third, it is necessary to study the data and equipment access middleware technology to realize the access and management of multi-source heterogeneous massive data and emergency rescue resource forces, achieve data linkage and equipment linkage and support smooth man–machine cooperation and accompanying command. Finally, it is necessary to study communication linkage, emergency watch, the accompanying command system and information linkage transmission and release mechanism through integrated communication. It is feasible to realize multi-task, cross-regional and cross-departmental information transmission and sharing based on manageable and controllable emergency information transmission mechanisms. Developing an intelligent emergency watch system and accompanying command App system is essential.

4. Key Scientific and Technological Issues in ITAECS

In ITACES’ development and application, there will be difficulties or challenges from all sides. The following key scientific and technological issues should be overcome.

4.1. Group Coordinated Operation and Disaster Tracing Location Technology of Mobile Sensing Equipment under Complex Disaster Conditions

The highly reliable identification and accurate location of toxic gas leakage sources in the disaster environment of complex hazardous chemicals of mixed gases in the field is crucial for properly and rapidly disposing of disasters and accidents. At present, the key technical difficulties to be solved in this field include two points: on the one hand, how to form a 3D detection and sensing network through UAV, drones and ISMT equipped with gas sensors, wind speed sensors, thermal imagers, remote sensing cameras and other sensing devices. On the other hand, how to use olfactory algorithms to analyze, calculate and approach the leakage source through multi-point and multi-dimensional comprehensive data acquisition and finally realize the accurate location of the gas leakage source.

4.2. Intelligent Terminal and ISSE Multi-Point Delivery ad Hoc Network Technology

Dynamic networking at the disaster site is essential to understanding the situation on the spot. Considering the failure of the post-disaster communication terminal or intelligent sensing monitoring terminal, it is necessary to quickly dispatch mobile ISSE to realize multi-point delivery on the site to form a group-coordinated operation and data real-time communication ad hoc network. The optimal operation configuration model of multi-point equipment driven by tasks is conducive to developing a dynamic ad hoc network scheme. The communication ad hoc network can realize the rapid recovery and reconstruction of data transmission under the partial failure of the on-site sensing terminal and communication terminal in disaster scenarios and ensure the reliability and stability of on-site data transmission.

4.3. DT Modeling Technology for Urban Disaster Source and Hidden Danger Scene Dynamic Real-Time Perception

Dynamic visual monitoring and real-time early warning of urban disaster sources and hidden dangers are the necessary technical guarantees to resolve disaster sources. However, hazardous chemical disaster sources are diverse, the hidden risks are complex, and the information level of on-site enterprises is different. How to establish a set of standardized, modular and rapid reconfigurable DT structure models suitable for various disaster sources and hidden danger sites and how to quickly deploy a dynamic, intelligent, visual and transparent DT system for disaster sources and hidden danger sites are the key technologies that must be developed.

4.4. Situation Deduction and Intelligent Early Warning Technology Based on Damage Mechanism of Disaster Carrier and Real-Time Data of Disaster Site

Disaster situation deduction and intelligent early warning information based on spatiotemporal and environmental constraints are critical knowledge sources for emergency rescue and on-site decision making of hazardous chemical disasters. Three aspects need to be addressed. First, thoroughly combining the diversity of disaster-bearing carriers and the complexity of the disaster to establish the dynamic model system of each scenario element in the disaster chain under environmental constraints. Second, putting forward the scenario evolution updating method of hazardous chemical disasters to construct the comprehensive situation deduction model considering the scenario evolution of hazardous chemical disasters. Third, developing a visual analysis and processing method to establish a situation deduction and intelligent early warning technology integrating multi-source heterogeneous dynamic monitoring data and historical spatiotemporal Big Data.

4.5. A 3D Dynamic Scene Modeling and Virtual Reality Fusion Simulation Rehearsal Technology Based on Complex Disaster Characteristics and Disaster Scenes

Facing the complex and dynamic real-time transformation scene of urban hazardous chemical disasters, it is crucial to comprehensively improve scientific emergency command decision making and cooperative command. The method should be studied to expand on the traditional emergency rescue simulation rehearsal system based on the stylized deduction of a single established plan and establish a multi-perspective agent model and interactive linkage relationship. Based on the technologies of an expert knowledge base, decision algorithm with ML, dynamic simulation, virtual reality fusion, optimal decision making and intelligent interaction, it is feasible to realize emergency rescue simulation rehearsal and an emergency disposal effect evaluation by integrating disaster scene dynamic perception data and disaster situation deduction models.

4.6. AI Data Center Based on Knowledge Graph and Emergency Plan Digitization Technology

Facing massive data access concerning the immersive emergency command platform, how to achieve stable, reliable, safe and smooth man–machine coordination data support architecture; how to develop an AI-enabling engine driven by multi-task and multi-level intelligent decision making; how to support the efficient and orderly real-time linkage and dynamic interaction of highly concurrent data, information, instructions and operations; how to realize fast and sufficient multi-task inter-departmental dynamic coordination; and how to support the equipment linkage, communication linkage, data linkage, application linkage and accompanying command of the emergency command and control platform to improve active urban disaster prevention and control and emergency command are the key technologies to be developed.

5. Discussion

This section discusses the feasibility, innovation, limitation, future approach and practicability of ITAECS. The author’s team research results related to ITAECS are introduced.

Facing disasters involving urban hazardous chemicals such as fires, explosions and leaks and based on the principle of ‘based on the scene and solving the scene’, this paper aims to construct the ITAECS strategy of perception, connection, knowledge mining, application and integration in the intelligent management and control of urban hazardous chemical disasters. The proposed ITAECS is advanced and feasible and is part of the focus of current scientific research. Each part serves the overall goal and progresses layer by layer and various feasible and advanced technologies are effective.

This strategy can benefit the deep integration and innovation of the hazard source industry ecological chain, emergency rescue technology chain and intelligent city innovation chain. Aiming at the whole hazardous chemicals industry chain, it is proposed to fully grasp the location, state, environment and safety by realizing the digitization and visualization of disaster sources and hidden trouble sites through intelligent technology. The data linkage between the disaster source enterprise and the emergency management government should be strengthened to solve weaknesses in rapid disposal and accurate rescue in the initial stage of accidents caused by a lack of proper and adequate data on the disaster source and hidden trouble site. ITAECS revolves around the technological innovation chain, which can help uncover the technological industry chain, realize the industrialization of innovative technology and serve the industrial needs of urban hazard supervision and emergency management. ITAECS faces the entire hazardous chemical industry chain of production, warehousing, transportation and use. Starting from the industry requirements of both safety (production, storage, transportation and use) and high efficiency (operation, supervision and governance), it can be conducive to deploying the technological innovation chain to serve the industrial ecological chain. ITAECS proposes the whole-scene monitoring of DT visualization at the enterprise end of the disaster source and hidden trouble site; realizing the cross-regional immersive, active emergency command of the city, district, street and enterprise; and effectively preventing the occurrence of urban disasters and achieving urban disaster active emergency rescue.

The limitations of ITAECS are also apparent as difficulties and challenges. In terms of technology, ITAECS involves the innovative research of technologies in many disciplines and the development of various technologies is uneven. The immediate and high-quality implementation of the whole set of strategies requires time and special funds. Regarding application, urban hazardous chemicals are distributed in every corner of the city and have a specific dynamic mobility; urban hazardous chemicals involve all aspects of the industrial chain. This strategy’s successful promotion and application need at least standardization from technology and management, but there is a lack of relevant standards. In terms of government supervision, the government’s support and the timely adoption and promotion of ITAECS also have a time lag and a certain degree of uncertainty. Future approaches must be carried out in several aspects to mitigate difficulties or challenges, such as theory, technology, application, standardization and policy. First, the critical scientific and technological issues need to be focused on. It is necessary to integrate the resources of many professional research institutions, experts and scholars to research and develop related technologies. Continuous financial support policies and coordinated organizational policies should be studied and formulated. Second, systematic experimental verification, application demonstration and industry promotion are required. Integrating all aspects of industrial chain resources to effectively organize resources to realize the advancement and application of ITAECS is needed. Effective standardization research combined with the industry needs to be carried out. Third, urban hazardous chemicals’ safe production involves many organizations and individuals in the government and industry. These organizations and individuals need to cooperate effectively to promote the development of ITAECS.

The practicability of ITACES has been reflected in the past and will be more evident in the future, although it is a theoretical framework with five components integrated with multiple technologies. In Section 2, we pointed to references that have created those components or are being developed in the expected direction. The current technical status has already made some progress in the direction of related ITAECS components. We reviewed intelligent technologies with regard to five aspects: disaster sensing, monitoring urban disaster sources and hidden dangers, intelligent deduction technology for hazardous chemical disasters, emergency rescue virtual reality simulation rehearsals and an emergency command platform. This literature review gave some cases or studies obtained in the directions of the five components put forward by ITAECS in Section 1 and Section 3, representing the practicability and foresight of ITAECS and proving the necessity of ITAECS. The digital transformation of the emergency management industry is a future direction. With the development of science and technology and the progress of society, ITACES will be more mature and will be reflected in the emergency management of hazardous chemicals in cities or other emergency management scenarios. Assuming that ITACES was very mature many years ago and was fully applied in Tianjin Port, Beirut Port and other scenarios before hazardous chemical disasters occurred there, we believe their level of emergency management would have been greatly improved, the degree of disaster losses would have been significantly reduced and human beings would be happier. We hope that ITACES can provide inspiration for future research and benefit humankind.

Focusing on the contents related to hazardous chemical safety production, the author’s team undertook several key national science and technology projects in the early stages and earned several achievements. For example, the national high-tech R&D program of China (863 Program), a ‘Networked microsystem for security monitoring and tracking’, developed sensors and networked microsystems for the safety monitoring and tracking of the production, storage, transportation and use of hazardous chemicals; solved critical technical problems such as testing, system simulation, reliability and industrialization; developed integrated products of networked microsystems for the monitoring and tracking of hazardous chemicals; and realized the industrialized popularization and application of research results. Additionally, the National Science and Technology support program, ‘R&D and application of the container supply-chain service platform’, developed intelligent container sensors and terminal products, built a whole process visual service platform for the container supply chain and conducted application demonstrations. An application pilot in cross-border customs, tobacco and hazardous chemicals transportation was carried out. The online capacity of terminals exceeded 50,000 at the same time. In 2022, the Ministry of Industry and Information Technology, the Development and Reform Commission, the Ministry of Science and Technology and the Ministry of Emergency Management announced the first batch of ‘pilot demonstration candidate projects for the application of safety emergency equipment’ and the ‘pilot demonstration project for the application of intelligent monitoring and early warning system for the safe production of hazardous chemicals’ led by CIMC Intelligent Technology Co., Ltd., was selected.

The author’s team developed the scene perception and monitoring IoT system and intelligent sensing terminal equipment for hazardous chemical disaster sources and hidden hazardous sites, developed IoT platforms for natural gas, hazardous chemicals and other matters, and realized the scene real-time perception and visual monitoring of disaster sources and hidden danger sites with containers as an important carrier. The results are helpful in scenes involving the production, transportation, storage and use of hazardous chemicals. Moreover, the results serve the participating business units in relevant links. Typical application customers include Petro China, China Gas and China Customs. The container IoT platform developed by the author’s research team solves the intelligent sensing and early warning of hazardous chemical storage and transportation equipment, such as containers, and improves safety management. Figure 8 shows the distribution of container storage and transportation equipment monitored by the container IoT platform in Shenzhen.

6. Conclusions

Emergency management is a vital part of urban governance capacity, and it is imperative to strengthen it. Intelligent technology is the key to improving early risk identification and warning, optimizing the emergency plan system, promoting the modernization of emergency management, and preventing and defusing security risks from the source. Hazardous chemicals are indispensable to humanity. While hazardous chemicals support human reproduction and development, their disasters cause irreparable societal losses. With the development of new-generation information technology, it is necessary to realize effective UHCDM with the help of the ITAECS. This paper adopts the concept of basing on the site, solving the site and strengthening source governance; it puts forward suggestions to realize the digitization and visualization of disaster sources and hidden danger sites through advanced sensing, IoT, DT technology, virtual reality emergency rescue rehearsal and immersive, active emergency command. For hazardous chemical disaster sources, especially hazardous chemical media such as hazardous hydrogen chemicals, natural gas and gasoline, storage containers, vehicles and transmission pipelines with more significant disasters, as well as entire industrial chain scenes such as the production, storage, transportation, operation and use of the disaster source, it is essential to realize the digitization and visualization of disaster sources and hidden danger sites. It is beneficial to realize a comprehensive grasp of the location, status, environment and safety, as well as the data linkage between the enterprise end of the disaster source and the government end of emergency management, to serve the government, enterprises, hazardous chemical parks and personnel involved in the hazardous chemicals industrial chain.

The smart city’s core technical elements are the underlying sensing technology, IoT connection display technology, intelligent deduction technology, virtual reality emergency rescue rehearsal and immersive, active emergency command. Based on the smart city concept, this paper studies and puts forward the ITAECS for UHCDM, which will help to improve the level of hazardous chemical safety production and disaster emergency management and serve the more effective and safe use of hazardous chemicals for humanity. This research is conducive to the safe, reliable, efficient and green scene of the entire industrial chain, such as the production, storage, transportation, operation and use of hazardous chemicals and will realize the transparency of information throughout the industrial chain and improve the benefits and efficiency of enterprises, industries, governments and society. ITAECS helps to solve the weaknesses in the rapid disposal and accurate rescue in the early stage of the accident due to the lack of proper and adequate data on the disaster sources and hidden danger sites of hazardous chemicals to improve digital, accurate and intelligent management and control. ITAECS aligns with the industrial paradigm discussed and evolving worldwide and is conducive to clarifying and improving the emergency command of urban hazardous chemical disaster safety. It is beneficial for governments of all countries to strengthen urban safety source governance, improve the urban safety prevention and control mechanism, strengthen the urban safety guarantee and enhance the efficiency of urban safety supervision. ITAECS is conducive to reducing the cost of government decision making, protecting the safety of people’s lives and property and promoting the steady and rapid development of the urban economy. ITAECS will have a good application prospect in urban safety production emergency management in the hazardous chemical industry and smart city construction.

As we mentioned, there are difficulties and challenges in developing ITAECS in urban hazardous chemical production safety and emergency management. In the future, researchers can study the fundamental theories, technologies, industrialization applications, standardization and policy to promote ITACES’s development.