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市场调查报告书
商品编码
1377256

基础设施监控市场 - 全球产业规模、份额、趋势、机会和预测，按组件、技术、按应用、垂直、地区、竞争细分，2018-2028

Infrastructure Monitoring Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Component, By Technology, By Application, By Vertical, By Region, By Competition, 2018-2028
出版日期: | 出版商: TechSci Research | 英文 180 Pages | 商品交期: 2-3个工作天内

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简介目录

2022 年全球基础设施监控市场价值为 43 亿美元，预计在预测期内将强劲增长，到 2028 年复合CAGR为12%。由于监控关键基础设施的重要性日益增加，全球基础设施监控市场正在经历大幅成长资产。随着世界各国投资基础设施的开发和维护，确保这些资产的可靠性、安全性和效率的需求日益增长。基础设施监测涉及使用先进的感测器技术、资料分析和遥感技术对桥樑、大坝、道路、管道和建筑物等各种要素进行即时评估。这种数据驱动的方法可以及早发现结构问题、潜在故障或性能偏差，从而实现及时干预和预防性维护。此外，智慧城市的兴起以及物联网 (IoT) 在基础设施系统中的整合进一步推动了监控解决方案的需求。优化资产管理、减少停机时间和增强公共安全的能力是基础设施监控市场的关键驱动力。因此，专门从事基础设施监控技术和服务的公司将在未来几年内迎来重大机会。

主要市场驱动因素

提高基础设施监控效率

市场概况
预测期 2024-2028
2022 年市场规模 43亿美元
2028 年市场规模 85.6亿美元
2023-2028 年CAGR 12%
成长最快的细分市场 软体
最大的市场 北美洲

支援人工智慧的基础设施监控透过自动化劳力密集任务，正在彻底改变关键资产和基础设施的管理方式，使专家能够专注于更复杂和任务关键的方面。利用人工智慧演算法，可以快速分析来自各种感测器的大量资料、识别模式并产生早期警报，从而减少监控和维护任务中人工干预的需要。这项突破显着提高了基础设施监控流程的效率，并加快了重要资产的整体维护和管理。支援人工智慧的基础设施监控的一个典型优势是其自动异常检测的能力。人工智慧演算法审查历史资料、识别模式并及时识别异常情况，从而减少人为干预识别异常情况的必要性。此外，这些演算法旨在随着时间的推移调整和完善其异常检测标准，确保监控过程保持现代化和有效。

目录

第 1 章：产品概述

  • 市场定义
  • 市场范围
    • 涵盖的市场
    • 考虑学习的年份
    • 主要市场区隔

第 2 章：研究方法

  • 研究目的
  • 基线方法
  • 范围的製定
  • 假设和限制
  • 研究来源
    • 二次研究
    • 初步研究
  • 市场研究方法
    • 自下而上的方法
    • 自上而下的方法
  • 计算市场规模和市场份额所遵循的方法
  • 预测方法
    • 数据三角测量与验证

第 3 章：执行摘要

第 4 章：COVID-19 对全球基础设施监控市场的影响

第 5 章：客户之声

第 6 章：全球基础设施监控市场概述

第 7 章：全球基础设施监控市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按组件（硬体、软体、服务）
    • 依技术（有线、无线）
    • 按应用（腐蚀监测、裂纹检测、损坏检测、振动监测、热监测、多模态感测、应变监测等）
    • 按垂直产业（石油和天然气、製造业、航太和国防、建筑、汽车、发电、其他）
    • 按地区（北美、欧洲、南美、中东和非洲、亚太地区）
  • 按公司划分 (2022)
  • 市场地图

第 8 章：北美基础设施监控市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按组件
    • 依技术
    • 按应用
    • 按垂直方向
    • 按国家/地区
  • 北美：国家分析
    • 美国
    • 加拿大
    • 墨西哥

第 9 章：欧洲基础设施监控市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按组件
    • 依技术
    • 按应用
    • 按垂直方向
    • 按国家/地区
  • 欧洲：国家分析
    • 德国
    • 法国
    • 英国
    • 义大利
    • 西班牙
    • 比利时

第 10 章：南美洲基础设施监控市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按组件
    • 依技术
    • 按应用
    • 按垂直方向
    • 按国家/地区
  • 南美洲：国家分析
    • 巴西
    • 哥伦比亚
    • 阿根廷
    • 智利
    • 秘鲁

第 11 章：中东和非洲基础设施监控市场展望

  • 市场规模及预测
    • 按价值
  • 市占率及预测
    • 按组件
    • 依技术
    • 按应用
    • 按垂直方向
    • 按国家/地区
  • 中东和非洲：国家分析
    • 沙乌地阿拉伯
    • 阿联酋
    • 南非
    • 土耳其
    • 以色列

第 12 章：亚太基础设施监控市场展望

  • 市场规模及预测
    • 按组件
    • 依技术
    • 按应用
    • 按垂直方向
    • 按国家/地区
  • 亚太地区：国家分析
    • 中国基础建设监控
    • 印度基础设施监控
    • 日本基础建设监控
    • 韩国基础建设监控
    • 澳洲基础设施监控
    • 印尼基础设施监控
    • 越南基础建设监控

第 13 章：市场动态

  • 司机
  • 挑战

第 14 章：市场趋势与发展

第 15 章：公司简介

  • Acellent 科技公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 派克·汉尼汾
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 西门子公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 艾默生电气
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 数码克斯系统
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 通用电气
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 坎贝尔科学公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 美国国家仪器公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 霍尼韦尔
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 罗克韦尔自动化
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • AVT 可靠性有限公司
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 布里奇诊断公司 (BDI)
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered
  • 横河电机株式会社
    • Business Overview
    • Key Revenue and Financials
    • Recent Developments
    • Key Personnel/Key Contact Person
    • Key Product/Services Offered

第 16 章：策略建议

第 17 章：关于我们与免责声明

简介目录
Product Code: 16844

Global Infrastructure Monitoring Market has valued at USD 4.3 Billion in 2022 and is anticipated to project robust growth in the forecast period with a CAGR of 12% through 2028. The Global Infrastructure Monitoring Market is experiencing substantial growth driven by the increasing importance of monitoring critical infrastructure assets. As nations around the world invest in the development and maintenance of their infrastructure, there is a growing need to ensure the reliability, safety, and efficiency of these assets. Infrastructure monitoring involves the real-time assessment of various elements such as bridges, dams, roads, pipelines, and buildings using advanced sensor technologies, data analytics, and remote sensing techniques. This data-driven approach allows for early detection of structural issues, potential failures, or performance deviations, enabling timely intervention and preventive maintenance. Additionally, the rise of smart cities and the integration of the Internet of Things (IoT) in infrastructure systems further fuels the demand for monitoring solutions. The ability to optimize asset management, reduce downtime, and enhance public safety are key drivers of the Infrastructure Monitoring Market. As a result, companies specializing in infrastructure monitoring technologies and services are poised for significant opportunities in the coming years.

Key Market Drivers

Enhanced Infrastructure Monitoring Efficiency

Market Overview
Forecast Period2024-2028
Market Size 2022USD 4.3 Billion
Market Size 2028USD 8.56 billion
CAGR 2023-202812%
Fastest Growing SegmentSoftware
Largest MarketNorth America

AI-enabled infrastructure monitoring is revolutionizing the way critical assets and infrastructure are managed by automating labor-intensive tasks, enabling experts to focus on more intricate and mission-critical aspects. Leveraging AI algorithms, copious amounts of data from various sensors can be swiftly analyzed, patterns discerned, and early alerts generated, mitigating the need for manual intervention in monitoring and maintenance tasks. This breakthrough significantly enhances the efficiency of infrastructure monitoring processes and expedites the overall maintenance and management of vital assets. An exemplar advantage of AI-enabled infrastructure monitoring is its capacity to automate anomaly detection. AI algorithms scrutinize historical data, recognize patterns, and promptly identify anomalies, thereby reducing the necessity for human intervention in identifying irregularities. Furthermore, these algorithms are designed to adapt and refine their anomaly detection criteria over time, ensuring that the monitoring process remains contemporary and effective.

In addition to anomaly detection, AI-enabled infrastructure monitoring improves overall asset performance management. AI algorithms can gauge real-time data, pinpoint irregularities, and prioritize critical issues, empowering professionals to concentrate their efforts on resolving high-priority concerns and bolstering asset performance and reliability. Moreover, these algorithms are equipped to discern deviations from anticipated behaviors, facilitating early detection of potential issues and diminishing the likelihood of unexpected disruptions. The incorporation of AI into infrastructure monitoring also enhances data analysis and reporting. AI algorithms dissect monitoring data, decipher trends, and provide valuable insights into the condition of assets. This aids stakeholders in making informed decisions regarding maintenance and investment strategies. Furthermore, AI algorithms generate comprehensive reports, spotlighting areas requiring immediate attention and furnishing recommendations for optimization.

However, it is imperative to underscore that AI-enabled infrastructure monitoring is not intended to supplant human expertise. Human professionals still play an indispensable role in the interpretation of data, strategic analysis, and decision-making. AI serves as an indispensable tool that augments the capabilities of experts, allowing them to channel their expertise toward more intricate aspects of infrastructure management.

Augmented Asset Surveillance

AI-enabled infrastructure monitoring harnesses the capabilities of AI algorithms to scrutinize voluminous data and pinpoint potential risks and vulnerabilities in critical infrastructure assets. By leveraging AI algorithms, organizations can expand their asset surveillance scope, ensuring comprehensive monitoring of all essential functionalities and potential risk scenarios. This inclusive approach reduces the likelihood of asset failures, augmenting the overall reliability and longevity of the infrastructure. AI algorithms are adept at comprehending intricate infrastructure structures, identifying potential flaws, and even predicting areas prone to deterioration. This facilitates proactive maintenance measures, effectively addressing issues before they escalate and impact operations. Additionally, AI-enabled infrastructure monitoring can simulate real-world scenarios and user interactions, enabling organizations to validate asset performance and durability under diverse conditions. By preemptively identifying and resolving potential issues in the development phase, organizations can save resources and mitigate challenges that may become more onerous and costly to rectify in the future. AI algorithms are also programmed to evolve their monitoring strategies through continuous learning from monitoring results, thereby optimizing infrastructure surveillance efforts.

Intelligent Anomaly Detection

AI-enabled infrastructure monitoring capitalizes on machine learning algorithms to identify irregularities in asset behavior based on historical data, user interactions, and usage patterns. By scrutinizing past monitoring data, these algorithms can identify areas necessitating additional surveillance, allowing experts to focus their attention on high-risk zones. This intelligent anomaly detection augments the overall monitoring process and aids in early defect detection during the infrastructure development phase.

The incorporation of AI algorithms in infrastructure monitoring engenders a multitude of advantages throughout the asset lifecycle. Firstly, it mitigates the manual effort required for anomaly detection. Traditionally, experts had to manually monitor and identify irregularities, a time-consuming and potentially error-prone process. With AI-enabled infrastructure monitoring, machine learning algorithms autonomously assess historical data and promptly alert operators to anomalies. This not only saves time but also guarantees comprehensive coverage and scrutiny of critical functionalities. Secondly, AI-enabled anomaly detection amplifies asset surveillance. Through analysis of past monitoring data, machine learning algorithms discern infrastructure areas that have not been vigilantly examined or bear a higher likelihood of harboring defects. Operators can then allocate resources judiciously to these high-risk zones, guaranteeing the early identification and resolution of potential problems. This targeted approach enhances overall infrastructure quality and diminishes the probability of deploying faulty assets.

Furthermore, AI algorithms are perpetually learning and adapting based on monitoring outcomes. With fresh monitoring data at their disposal, these algorithms recalibrate the anomaly detection parameters, ameliorating accuracy and effectiveness over time, and resulting in more efficient and effective anomaly detection.

Predictive Analytics for Preventive Maintenance

AI algorithms possess the capacity to analyze historical data to pinpoint patterns indicative of potential infrastructure issues. By harnessing predictive analytics, organizations can proactively detect potential defects and implement preventive measures, reducing the incidence of failures and ameliorating infrastructure reliability. This proactive approach is pivotal in minimizing the number of infrastructure issues and enhancing overall infrastructure quality. The aptitude of AI algorithms to scrutinize historical data is pivotal in recognizing patterns correlated with infrastructure defects. By delving into past monitoring results, AI algorithms can unearth correlations and trends that foreshadow defects. This in-depth analysis affords organizations valuable insights into the root causes of infrastructure issues and the factors contributing to their occurrence. By leveraging predictive analytics, organizations progress from merely identifying defects to implementing proactive measures to prevent their manifestation. AI algorithms employ patterns derived from historical data to forecast the likelihood of future defects, empowering organizations to preempt potential issues and institute preventive measures before they materialize as actual defects. By addressing underlying causes and mitigating risks proactively, organizations can significantly curtail the incidence of defects during the infrastructure development process.

The implementation of preventive measures based on predictive analytics bolsters overall infrastructure quality. By identifying and rectifying potential defects at an early stage, organizations evade costly rework, delays, and client dissatisfaction. Moreover, this proactive approach enables organizations to optimize resource allocation by directing efforts towards defect prevention, rather than reactive defect resolution. In addition to diminishing the number of defects, the deployment of predictive analytics augments the efficiency of the infrastructure development process. By proactively identifying potential defects, organizations streamline monitoring efforts, prioritize critical areas, and allocate resources more efficiently. This translates to expedited development cycles, improved time-to-market, and heightened customer satisfaction.

Test Automation and Continuous Monitoring

AI-enabled infrastructure monitoring plays an instrumental role in automating various facets of the monitoring process, encompassing data analysis, anomaly detection, and performance evaluation. This automation empowers organizations to embrace continuous monitoring practices, where infrastructure assets are vigilantly observed throughout their lifecycle. Continuous monitoring engenders several benefits, including prompt issue identification, early defect detection, and accelerated asset deployment.

One of the salient advantages of AI-enabled infrastructure monitoring is the automation of anomaly detection. AI algorithms evaluate historical data, user interactions, and usage patterns to autonomously detect anomalies, circumventing the necessity for manual intervention. This automation ensures that assets are perpetually under scrutiny and irregularities are promptly identified. Moreover, AI algorithms are equipped to continuously learn from monitoring results and fine-tune their anomaly detection protocols over time, guaranteeing that the monitoring process remains contemporary and effective. Alongside anomaly detection, AI-enabled infrastructure monitoring streamlines asset performance evaluation. Through real-time data analysis, AI algorithms discern irregularities, facilitating the prompt identification of critical issues. This enables experts to concentrate their efforts on resolving high-priority concerns, thereby enhancing asset reliability and performance. Additionally, AI algorithms are adept at identifying deviations from expected behavior, allowing for early detection of potential defects and reducing the risk of deploying faulty assets. Infrastructure monitoring fortified by AI also aids in data analysis and reporting. AI algorithms scrutiny.

Key Market Challenges

Lack of Awareness and Understanding

The global infrastructure monitoring market faces a significant challenge in terms of limited awareness and understanding among organizations regarding the importance and benefits of adopting infrastructure monitoring solutions. Many businesses, particularly smaller enterprises, may not fully comprehend the potential risks and vulnerabilities associated with inadequate infrastructure monitoring practices. This lack of awareness can result in hesitation to invest in advanced monitoring solutions, leaving organizations exposed to infrastructure failures, downtime, and potential financial losses. Addressing this challenge requires comprehensive educational initiatives to highlight the critical role that infrastructure monitoring plays in ensuring the reliability, performance, and security of complex infrastructure systems. Organizations need to recognize that insufficient monitoring can lead to costly disruptions, compromised data integrity, and reputational damage. Real-world examples and case studies showcasing the tangible benefits of infrastructure monitoring can help foster a deeper understanding of its significance.

Complexity and Integration Issues

Implementing and managing infrastructure monitoring solutions can pose complex challenges for organizations, particularly those with limited IT resources or expertise. Configuring monitoring systems effectively and integrating them with existing infrastructure components and tools can be technically demanding. Compatibility issues may arise during integration, leading to delays and suboptimal performance. To address these challenges, it is crucial to simplify the deployment and management of infrastructure monitoring solutions. User-friendly interfaces and intuitive configuration options should be provided to streamline setup and customization. Additionally, organizations should have access to comprehensive support and guidance, including documentation, tutorials, and technical experts who can assist with integration and troubleshoot any issues. Simplifying these aspects of infrastructure monitoring implementation can lead to more efficient processes and improved infrastructure performance.

Data Overload and Actionable Insights

Infrastructure monitoring generates vast amounts of data, which can overwhelm organizations and make it challenging to extract actionable insights. The sheer volume and variety of data can hinder decision-making processes and delay the identification of critical issues. To overcome this challenge, organizations need advanced analytics capabilities that can process and analyze data in real-time, providing meaningful insights and actionable recommendations. Machine learning and AI technologies can play a crucial role in automating data analysis, anomaly detection, and predictive maintenance, enabling organizations to proactively address potential infrastructure issues. By leveraging these technologies, organizations can transform raw data into valuable insights, facilitating informed decision-making and efficient infrastructure management.

Ensuring Scalability and Flexibility

As organizations expand their infrastructure and adopt new technologies, scalability and flexibility become crucial challenges in infrastructure monitoring. Monitoring solutions need to accommodate the growing complexity and diversity of infrastructure components, including on-premises, cloud-based, and hybrid environments. Additionally, organizations require the flexibility to customize monitoring parameters and adapt to evolving infrastructure requirements. To address these challenges, monitoring solutions should offer scalability options that can handle increasing data volumes and support the monitoring of diverse infrastructure components. Furthermore, flexible configuration options and integration capabilities should be provided to ensure seamless monitoring across different environments. By addressing scalability and flexibility challenges, organizations can effectively monitor their expanding infrastructure and adapt to changing business needs.

Cybersecurity and Threat Detection

The global infrastructure monitoring market faces the ongoing challenge of cybersecurity threats and the need for robust threat detection capabilities. As infrastructure systems become more interconnected and reliant on digital technologies, they become attractive targets for cybercriminals. Organizations need to implement monitoring solutions that can detect and mitigate potential security breaches, unauthorized access attempts, and other malicious activities. Advanced threat detection algorithms, anomaly detection techniques, and real-time monitoring capabilities are essential to identify and respond to cybersecurity threats promptly. By prioritizing cybersecurity in infrastructure monitoring, organizations can safeguard their critical assets, protect sensitive data, and maintain the trust of their stakeholders.

Key Market Trends

Elevation in Advanced Infrastructure Monitoring

The global infrastructure monitoring market is witnessing a surge in demand due to the escalating complexity of modern infrastructure systems and the need for real-time oversight. Organizations are increasingly turning to advanced infrastructure monitoring solutions to manage the intricate web of assets, from bridges and pipelines to data centers and IoT networks. This shift is prompted by a growing recognition of the importance of proactive infrastructure maintenance and risk mitigation. To address this demand, infrastructure monitoring providers are focusing on developing sophisticated, AI-powered solutions that can efficiently collect and analyze data from various sensors and devices. These advanced solutions enable predictive maintenance, early fault detection, and informed decision-making, ultimately enhancing the resilience and longevity of critical infrastructure assets. By harnessing AI and machine learning technologies, these solutions can identify patterns and anomalies, paving the way for swift responses to potential issues and ensuring the uninterrupted functionality of vital infrastructure systems.

Transition to Cloud-based Infrastructure Monitoring

The global infrastructure monitoring landscape is undergoing a substantial transition towards cloud-based solutions, in alignment with the pervasive adoption of cloud computing and the need for scalable and flexible monitoring capabilities. Organizations are seeking infrastructure monitoring solutions that seamlessly integrate with their cloud environments, allowing for efficient and centralized oversight of distributed assets. Cloud-based infrastructure monitoring solutions offer scalability, enabling organizations to effortlessly allocate resources in response to evolving monitoring needs. This adaptability ensures the effective monitoring of infrastructure assets, even during periods of heightened demand or expansion. Additionally, the flexibility of cloud-based solutions enables their deployment across diverse cloud platforms, empowering organizations to select the most suitable cloud infrastructure for their unique requirements. This adaptability facilitates seamless integration with existing cloud environments, streamlining infrastructure monitoring and offering enhanced agility.

Incorporation of Artificial Intelligence and Machine Learning

The integration of artificial intelligence (AI) and machine learning (ML) technologies into infrastructure monitoring solutions represents a prominent trend in the market. AI and ML algorithms can process vast volumes of monitoring data, discern patterns, and detect anomalies in real-time, empowering infrastructure monitoring solutions to efficiently adapt to evolving challenges. These advanced technologies significantly enhance the precision and effectiveness of infrastructure monitoring, resulting in a reduction of false alarms and missed issues. Infrastructure monitoring providers are making substantial investments in AI and ML capabilities to bolster fault detection, automate maintenance processes, and proactively safeguard against emerging risks. By leveraging AI and ML, organizations can elevate their infrastructure monitoring to a predictive and proactive level, averting potential disruptions and ensuring the integrity of critical assets.

Segmental Insights

Component Insights

Based on components, the market is classified into hardware, software, and services. The hardware segment dominated with a market share of 58.8% in 2022. It is expected to grow at a CAGR of 9.8% throughout the forecast period. The hardware components are essential for collecting data, enabling communication, and facilitating the monitoring process. Adopting these hardware components in infrastructure monitoring allows for real-time data collection, analysis, and decision-making. By utilizing reliable and advanced hardware, operators can ensure the monitored infrastructure's optimal performance, safety, and longevity.

The services segment is expected to grow at a CAGR of 11.9% during the forecast period. The services component plays a vital role in infrastructure monitoring. The services encompass a range of activities that support monitoring systems' implementation, operation, and maintenance. Service providers offer expertise in installing and commissioning monitoring systems. This involves physically installing sensors, data acquisition units, communication devices, and other hardware components.

Service professionals ensure the system is appropriately set up, calibrated, and integrated for accurate data collection. The services component is crucial for maximizing the benefits of the systems. Service providers bring the expertise, technical knowledge, and experience to ensure the proper installation, integration, operation, and maintenance of the overall system. Through these services, the operators can leverage the full potential of infrastructure monitoring for enhanced safety, efficiency, and asset management.

Technology Insights

In terms of technology, the market is classified into wired technology & wireless technology. The wired technology segment held the largest revenue share of 56.8% in 2022. It is expected to grow at a CAGR of 8.1% throughout the forecast period. Wired systems play a significant role in the market as they utilize physical cables and wired connections to transmit data between various monitoring system components.

Wired systems provide a robust and stable means of data transmission and communication. It is specifically suited for applications that require reliable and continuous monitoring, such as critical equipment and pipeline systems. The use of wired connections ensures secure and high-quality data transfer, supporting the integrity and efficiency of the monitoring process.

The wireless technology segment is expected to grow at the fastest CAGR of 13.9% during the forecast period. Wireless technology systems have emerged as a valuable solution for infrastructure monitoring systems. These systems utilize wireless communication methods to transmit data between various system components. The growth is attributed to the use of wireless sensors, remote monitoring, real-time data transmission, and cost-effectiveness compared to wired systems.

This technology is particularly suitable for applications with impractical or expensive wired connections. The adoption of wireless systems enhances the efficiency and effectiveness of monitoring practices, enabling timely decision-making, proactive maintenance, and improved overall asset management.

For instance, in May 2023, Scientists at Drexel University's College of Engineering created a wireless sensor system powered by solar energy. This innovative system is designed to monitor the deformation of bridges in real-time, providing ongoing surveillance of their structural integrity. In the event of a significant deterioration in bridge performance, the system can promptly notify relevant authorities, enabling timely intervention and maintenance measures.

Application Insights

Based on application, the market is classified into corrosion monitoring, crack detection, damage detection, vibration monitoring, thermal monitoring, multimodal sensing, strain monitoring, and others. The vibration monitoring segment gained the largest share of 22.9% in 2022 and is expected to witness a CAGR of 10.4% during the forecast period. Vibration monitoring allows for the assessment of structural dynamics, identification of potential issues related to stability, and evaluation of the impact of vibrations on overall infrastructure performance. It is extensively applied in various industries, including construction and other industrial facilities, to ensure the structural health and integrity of the infrastructure.

The damage detection segment is anticipated to witness a CAGR of 12.3% throughout the forecast period. Damage detection is a crucial application within the market. The growing emphasis on developing advanced sensor technologies & integration of machine learning & artificial intelligence is creating a significant opportunity for the damage detection application in the market. These sensors will offer higher sensitivity, improved accuracy, and increased durability, allowing for more precise and reliable detection of damages. For instance, integrating smart materials, such as carbon nanotubes or self-healing polymers, into sensors can enhance their capabilities and enable self-monitoring capabilities.

Regional Insights

North America dominated the overall infrastructure monitoring market in 2022, with a revenue share of 29.7%. It is expected to grow at a CAGR of 10.4% throughout the forecast period. Industries across various sectors in North America have recognized the importance of ensuring the efficient operation and integrity of the infrastructure. This has increased demand for solutions to enhance safety, optimize maintenance practices, and improve overall operational performance.

Companies across the region are investing in new product launches to stay ahead in the market. For instance, in October 2022, Doosan Infracore introduced a new and improved telematics monitoring service named Smart X-care. This subscription-based service provides enhanced capabilities for Doosan equipment. To support Smart X-Care, a dedicated machine center has been established at the Doosan Infracore headquarters. This proactive approach ensures that equipment issues are promptly addressed, helping to maximize the performance and efficiency of Doosan machinery.

Asia Pacific is expected to grow at the fastest CAGR of 12.3% during the forecast period. Significant investments are being made in the region to enhance the infrastructure devices' performance, security, and economic stability. As one of the leading emerging economies, China has taken substantial steps to implement real-time equipment monitoring systems, aiming to improve operational efficiency and boost productivity. The utility sector, in particular, has witnessed rapid adoption of technology due to its ability to provide effective solutions for critical asset management.

Key Market Players

Acellent Technologies, Inc.

Parker Hannifin

Siemens AG

Emerson Electric

Digitex Systems

General Electric

Campbell Scientific, Inc.

National Instruments

Honeywell

Rockwell Automation

AVT Reliability Ltd.

Bridge Diagnostics, Inc. (BDI)

Yokogawa Electric Corporation

Report Scope:

In this report, the Global Infrastructure Monitoring Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Infrastructure Monitoring Market, By Component:

  • Solution
  • Services

Infrastructure Monitoring Market, By Vertical:

  • Oil & Gas
  • Manufacturing
  • Aerospace and Defense
  • Construction
  • Automotive
  • Power Generation
  • Others

Infrastructure Monitoring Market, By Application:

  • Corrosion Monitoring
  • Crack Detection
  • Damage Detection
  • Vibration Monitoring
  • Thermal Monitoring
  • Multimodal Sensing
  • Strain Monitoring
  • Others

Infrastructure Monitoring Market, By Technology:

  • Wired
  • Wireless

Infrastructure Monitoring Market, By Region:

  • North America
  • United States
  • Canada
  • Mexico
  • Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
  • Belgium
  • Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • Indonesia
  • Vietnam
  • South America
  • Brazil
  • Argentina
  • Colombia
  • Chile
  • Peru
  • Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE
  • Turkey
  • Israel

Competitive Landscape

  • Company Profiles: Detailed analysis of the major companies present in the Global Infrastructure Monitoring Market.

Available Customizations:

  • Global Infrastructure Monitoring market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

  • Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

  • 1.1. Market Definition
  • 1.2. Scope of the Market
    • 1.2.1. Markets Covered
    • 1.2.2. Years Considered for Study
    • 1.2.3. Key Market Segmentations

2. Research Methodology

  • 2.1. Objective of the Study
  • 2.2. Baseline Methodology
  • 2.3. Formulation of the Scope
  • 2.4. Assumptions and Limitations
  • 2.5. Sources of Research
    • 2.5.1. Secondary Research
    • 2.5.2. Primary Research
  • 2.6. Approach for the Market Study
    • 2.6.1. The Bottom-Up Approach
    • 2.6.2. The Top-Down Approach
  • 2.7. Methodology Followed for Calculation of Market Size & Market Shares
  • 2.8. Forecasting Methodology
    • 2.8.1. Data Triangulation & Validation

3. Executive Summary

4. Impact of COVID-19 on Global Infrastructure Monitoring Market

5. Voice of Customer

6. Global Infrastructure Monitoring Market Overview

7. Global Infrastructure Monitoring Market Outlook

  • 7.1. Market Size & Forecast
    • 7.1.1. By Value
  • 7.2. Market Share & Forecast
    • 7.2.1. By Component (Hardware, Software, Services)
    • 7.2.2. By Technology (Wired, Wireless)
    • 7.2.3. By Application (Corrosion Monitoring, Crack Detection, Damage Detection, Vibration Monitoring, Thermal Monitoring, Multimodal Sensing, Strain Monitoring, Others)
    • 7.2.4. By Vertical (Oil & Gas, Manufacturing, Aerospace and Defense, Construction, Automotive, Power Generation, Others)
    • 7.2.5. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
  • 7.3. By Company (2022)
  • 7.4. Market Map

8. North America Infrastructure Monitoring Market Outlook

  • 8.1. Market Size & Forecast
    • 8.1.1. By Value
  • 8.2. Market Share & Forecast
    • 8.2.1. By Component
    • 8.2.2. By Technology
    • 8.2.3. By Application
    • 8.2.4. By Vertical
    • 8.2.5. By Country
  • 8.3. North America: Country Analysis
    • 8.3.1. United States Infrastructure Monitoring Market Outlook
      • 8.3.1.1. Market Size & Forecast
        • 8.3.1.1.1. By Value
      • 8.3.1.2. Market Share & Forecast
        • 8.3.1.2.1. By Component
        • 8.3.1.2.2. By Technology
        • 8.3.1.2.3. By Application
        • 8.3.1.2.4. By Vertical
    • 8.3.2. Canada Infrastructure Monitoring Market Outlook
      • 8.3.2.1. Market Size & Forecast
        • 8.3.2.1.1. By Value
      • 8.3.2.2. Market Share & Forecast
        • 8.3.2.2.1. By Component
        • 8.3.2.2.2. By Technology
        • 8.3.2.2.3. By Application
        • 8.3.2.2.4. By Vertical
    • 8.3.3. Mexico Infrastructure Monitoring Market Outlook
      • 8.3.3.1. Market Size & Forecast
        • 8.3.3.1.1. By Value
      • 8.3.3.2. Market Share & Forecast
        • 8.3.3.2.1. By Component
        • 8.3.3.2.2. By Technology
        • 8.3.3.2.3. By Application
        • 8.3.3.2.4. By Vertical

9. Europe Infrastructure Monitoring Market Outlook

  • 9.1. Market Size & Forecast
    • 9.1.1. By Value
  • 9.2. Market Share & Forecast
    • 9.2.1. By Component
    • 9.2.2. By Technology
    • 9.2.3. By Application
    • 9.2.4. By Vertical
    • 9.2.5. By Country
  • 9.3. Europe: Country Analysis
    • 9.3.1. Germany Infrastructure Monitoring Market Outlook
      • 9.3.1.1. Market Size & Forecast
        • 9.3.1.1.1. By Value
      • 9.3.1.2. Market Share & Forecast
        • 9.3.1.2.1. By Component
        • 9.3.1.2.2. By Technology
        • 9.3.1.2.3. By Application
        • 9.3.1.2.4. By Vertical
    • 9.3.2. France Infrastructure Monitoring Market Outlook
      • 9.3.2.1. Market Size & Forecast
        • 9.3.2.1.1. By Value
      • 9.3.2.2. Market Share & Forecast
        • 9.3.2.2.1. By Component
        • 9.3.2.2.2. By Technology
        • 9.3.2.2.3. By Application
        • 9.3.2.2.4. By Vertical
    • 9.3.3. United Kingdom Infrastructure Monitoring Market Outlook
      • 9.3.3.1. Market Size & Forecast
        • 9.3.3.1.1. By Value
      • 9.3.3.2. Market Share & Forecast
        • 9.3.3.2.1. By Component
        • 9.3.3.2.2. By Technology
        • 9.3.3.2.3. By Application
        • 9.3.3.2.4. By Vertical
    • 9.3.4. Italy Infrastructure Monitoring Market Outlook
      • 9.3.4.1. Market Size & Forecast
        • 9.3.4.1.1. By Value
      • 9.3.4.2. Market Share & Forecast
        • 9.3.4.2.1. By Component
        • 9.3.4.2.2. By Technology
        • 9.3.4.2.3. By Application
        • 9.3.4.2.4. By Vertical
    • 9.3.5. Spain Infrastructure Monitoring Market Outlook
      • 9.3.5.1. Market Size & Forecast
        • 9.3.5.1.1. By Value
      • 9.3.5.2. Market Share & Forecast
        • 9.3.5.2.1. By Component
        • 9.3.5.2.2. By Technology
        • 9.3.5.2.3. By Application
        • 9.3.5.2.4. By Vertical
    • 9.3.6. Belgium Infrastructure Monitoring Market Outlook
      • 9.3.6.1. Market Size & Forecast
        • 9.3.6.1.1. By Value
      • 9.3.6.2. Market Share & Forecast
        • 9.3.6.2.1. By Component
        • 9.3.6.2.2. By Technology
        • 9.3.6.2.3. By Application
        • 9.3.6.2.4. By Vertical

10. South America Infrastructure Monitoring Market Outlook

  • 10.1. Market Size & Forecast
    • 10.1.1. By Value
  • 10.2. Market Share & Forecast
    • 10.2.1. By Component
    • 10.2.2. By Technology
    • 10.2.3. By Application
    • 10.2.4. By Vertical
    • 10.2.5. By Country
  • 10.3. South America: Country Analysis
    • 10.3.1. Brazil Infrastructure Monitoring Market Outlook
      • 10.3.1.1. Market Size & Forecast
        • 10.3.1.1.1. By Value
      • 10.3.1.2. Market Share & Forecast
        • 10.3.1.2.1. By Component
        • 10.3.1.2.2. By Technology
        • 10.3.1.2.3. By Application
        • 10.3.1.2.4. By Vertical
    • 10.3.2. Colombia Infrastructure Monitoring Market Outlook
      • 10.3.2.1. Market Size & Forecast
        • 10.3.2.1.1. By Value
      • 10.3.2.2. Market Share & Forecast
        • 10.3.2.2.1. By Component
        • 10.3.2.2.2. By Technology
        • 10.3.2.2.3. By Application
        • 10.3.2.2.4. By Vertical
    • 10.3.3. Argentina Infrastructure Monitoring Market Outlook
      • 10.3.3.1. Market Size & Forecast
        • 10.3.3.1.1. By Value
      • 10.3.3.2. Market Share & Forecast
        • 10.3.3.2.1. By Component
        • 10.3.3.2.2. By Technology
        • 10.3.3.2.3. By Application
        • 10.3.3.2.4. By Vertical
    • 10.3.4. Chile Infrastructure Monitoring Market Outlook
      • 10.3.4.1. Market Size & Forecast
        • 10.3.4.1.1. By Value
      • 10.3.4.2. Market Share & Forecast
        • 10.3.4.2.1. By Component
        • 10.3.4.2.2. By Technology
        • 10.3.4.2.3. By Application
        • 10.3.4.2.4. By Vertical
    • 10.3.5. Peru Infrastructure Monitoring Market Outlook
      • 10.3.5.1. Market Size & Forecast
        • 10.3.5.1.1. By Value
      • 10.3.5.2. Market Share & Forecast
        • 10.3.5.2.1. By Component
        • 10.3.5.2.2. By Technology
        • 10.3.5.2.3. By Application
        • 10.3.5.2.4. By Vertical

11. Middle East & Africa Infrastructure Monitoring Market Outlook

  • 11.1. Market Size & Forecast
    • 11.1.1. By Value
  • 11.2. Market Share & Forecast
    • 11.2.1. By Component
    • 11.2.2. By Technology
    • 11.2.3. By Application
    • 11.2.4. By Vertical
    • 11.2.5. By Country
  • 11.3. Middle East & Africa: Country Analysis
    • 11.3.1. Saudi Arabia Infrastructure Monitoring Market Outlook
      • 11.3.1.1. Market Size & Forecast
        • 11.3.1.1.1. By Value
      • 11.3.1.2. Market Share & Forecast
        • 11.3.1.2.1. By Component
        • 11.3.1.2.2. By Technology
        • 11.3.1.2.3. By Application
        • 11.3.1.2.4. By Vertical
    • 11.3.2. UAE Infrastructure Monitoring Market Outlook
      • 11.3.2.1. Market Size & Forecast
        • 11.3.2.1.1. By Value
      • 11.3.2.2. Market Share & Forecast
        • 11.3.2.2.1. By Component
        • 11.3.2.2.2. By Technology
        • 11.3.2.2.3. By Application
        • 11.3.2.2.4. By Vertical
    • 11.3.3. South Africa Infrastructure Monitoring Market Outlook
      • 11.3.3.1. Market Size & Forecast
        • 11.3.3.1.1. By Value
      • 11.3.3.2. Market Share & Forecast
        • 11.3.3.2.1. By Component
        • 11.3.3.2.2. By Technology
        • 11.3.3.2.3. By Application
        • 11.3.3.2.4. By Vertical
    • 11.3.4. Turkey Infrastructure Monitoring Market Outlook
      • 11.3.4.1. Market Size & Forecast
        • 11.3.4.1.1. By Value
      • 11.3.4.2. Market Share & Forecast
        • 11.3.4.2.1. By Component
        • 11.3.4.2.2. By Technology
        • 11.3.4.2.3. By Application
        • 11.3.4.2.4. By Vertical
    • 11.3.5. Israel Infrastructure Monitoring Market Outlook
      • 11.3.5.1. Market Size & Forecast
        • 11.3.5.1.1. By Value
      • 11.3.5.2. Market Share & Forecast
        • 11.3.5.2.1. By Component
        • 11.3.5.2.2. By Technology
        • 11.3.5.2.3. By Application
        • 11.3.5.2.4. By Vertical

12. Asia Pacific Infrastructure Monitoring Market Outlook

  • 12.1. Market Size & Forecast
    • 12.1.1. By Component
    • 12.1.2. By Technology
    • 12.1.3. By Application
    • 12.1.4. By Vertical
    • 12.1.5. By Country
  • 12.2. Asia-Pacific: Country Analysis
    • 12.2.1. China Infrastructure Monitoring Market Outlook
      • 12.2.1.1. Market Size & Forecast
        • 12.2.1.1.1. By Value
      • 12.2.1.2. Market Share & Forecast
        • 12.2.1.2.1. By Component
        • 12.2.1.2.2. By Technology
        • 12.2.1.2.3. By Application
        • 12.2.1.2.4. By Vertical
    • 12.2.2. India Infrastructure Monitoring Market Outlook
      • 12.2.2.1. Market Size & Forecast
        • 12.2.2.1.1. By Value
      • 12.2.2.2. Market Share & Forecast
        • 12.2.2.2.1. By Component
        • 12.2.2.2.2. By Technology
        • 12.2.2.2.3. By Application
        • 12.2.2.2.4. By Vertical
    • 12.2.3. Japan Infrastructure Monitoring Market Outlook
      • 12.2.3.1. Market Size & Forecast
        • 12.2.3.1.1. By Value
      • 12.2.3.2. Market Share & Forecast
        • 12.2.3.2.1. By Component
        • 12.2.3.2.2. By Technology
        • 12.2.3.2.3. By Application
        • 12.2.3.2.4. By Vertical
    • 12.2.4. South Korea Infrastructure Monitoring Market Outlook
      • 12.2.4.1. Market Size & Forecast
        • 12.2.4.1.1. By Value
      • 12.2.4.2. Market Share & Forecast
        • 12.2.4.2.1. By Component
        • 12.2.4.2.2. By Technology
        • 12.2.4.2.3. By Application
        • 12.2.4.2.4. By Vertical
    • 12.2.5. Australia Infrastructure Monitoring Market Outlook
      • 12.2.5.1. Market Size & Forecast
        • 12.2.5.1.1. By Value
      • 12.2.5.2. Market Share & Forecast
        • 12.2.5.2.1. By Component
        • 12.2.5.2.2. By Technology
        • 12.2.5.2.3. By Application
        • 12.2.5.2.4. By Vertical
    • 12.2.6. Indonesia Infrastructure Monitoring Market Outlook
      • 12.2.6.1. Market Size & Forecast
        • 12.2.6.1.1. By Value
      • 12.2.6.2. Market Share & Forecast
        • 12.2.6.2.1. By Component
        • 12.2.6.2.2. By Technology
        • 12.2.6.2.3. By Application
        • 12.2.6.2.4. By Vertical
    • 12.2.7. Vietnam Infrastructure Monitoring Market Outlook
      • 12.2.7.1. Market Size & Forecast
        • 12.2.7.1.1. By Value
      • 12.2.7.2. Market Share & Forecast
        • 12.2.7.2.1. By Component
        • 12.2.7.2.2. By Technology
        • 12.2.7.2.3. By Application
        • 12.2.7.2.4. By Vertical

13. Market Dynamics

  • 13.1. Drivers
  • 13.2. Challenges

14. Market Trends and Developments

15. Company Profiles

  • 15.1. Acellent Technologies, Inc.
    • 15.1.1. Business Overview
    • 15.1.2. Key Revenue and Financials
    • 15.1.3. Recent Developments
    • 15.1.4. Key Personnel/Key Contact Person
    • 15.1.5. Key Product/Services Offered
  • 15.2. Parker Hannifin
    • 15.2.1. Business Overview
    • 15.2.2. Key Revenue and Financials
    • 15.2.3. Recent Developments
    • 15.2.4. Key Personnel/Key Contact Person
    • 15.2.5. Key Product/Services Offered
  • 15.3. Siemens AG
    • 15.3.1. Business Overview
    • 15.3.2. Key Revenue and Financials
    • 15.3.3. Recent Developments
    • 15.3.4. Key Personnel/Key Contact Person
    • 15.3.5. Key Product/Services Offered
  • 15.4. Emerson Electric
    • 15.4.1. Business Overview
    • 15.4.2. Key Revenue and Financials
    • 15.4.3. Recent Developments
    • 15.4.4. Key Personnel/Key Contact Person
    • 15.4.5. Key Product/Services Offered
  • 15.5. Digitex Systems
    • 15.5.1. Business Overview
    • 15.5.2. Key Revenue and Financials
    • 15.5.3. Recent Developments
    • 15.5.4. Key Personnel/Key Contact Person
    • 15.5.5. Key Product/Services Offered
  • 15.6. General Electric
    • 15.6.1. Business Overview
    • 15.6.2. Key Revenue and Financials
    • 15.6.3. Recent Developments
    • 15.6.4. Key Personnel/Key Contact Person
    • 15.6.5. Key Product/Services Offered
  • 15.7. Campbell Scientific, Inc.
    • 15.7.1. Business Overview
    • 15.7.2. Key Revenue and Financials
    • 15.7.3. Recent Developments
    • 15.7.4. Key Personnel/Key Contact Person
    • 15.7.5. Key Product/Services Offered
  • 15.8. National Instruments
    • 15.8.1. Business Overview
    • 15.8.2. Key Revenue and Financials
    • 15.8.3. Recent Developments
    • 15.8.4. Key Personnel/Key Contact Person
    • 15.8.5. Key Product/Services Offered
  • 15.9. Honeywell
    • 15.9.1. Business Overview
    • 15.9.2. Key Revenue and Financials
    • 15.9.3. Recent Developments
    • 15.9.4. Key Personnel/Key Contact Person
    • 15.9.5. Key Product/Services Offered
  • 15.10. Rockwell Automation
    • 15.10.1. Business Overview
    • 15.10.2. Key Revenue and Financials
    • 15.10.3. Recent Developments
    • 15.10.4. Key Personnel/Key Contact Person
    • 15.10.5. Key Product/Services Offered
  • 15.11. AVT Reliability Ltd.
    • 15.11.1. Business Overview
    • 15.11.2. Key Revenue and Financials
    • 15.11.3. Recent Developments
    • 15.11.4. Key Personnel/Key Contact Person
    • 15.11.5. Key Product/Services Offered
  • 15.12. Bridge Diagnostics, Inc. (BDI)
    • 15.12.1. Business Overview
    • 15.12.2. Key Revenue and Financials
    • 15.12.3. Recent Developments
    • 15.12.4. Key Personnel/Key Contact Person
    • 15.12.5. Key Product/Services Offered
  • 15.13. Yokogawa Electric Corporation
    • 15.13.1. Business Overview
    • 15.13.2. Key Revenue and Financials
    • 15.13.3. Recent Developments
    • 15.13.4. Key Personnel/Key Contact Person
    • 15.13.5. Key Product/Services Offered

16. Strategic Recommendations

17. About Us & Disclaimer