虚拟感测器市场－全球产业规模、份额、趋势、机会、预测：按组件、部署方式、最终用户、地区和竞争对手划分，2021-2031年

全球虚拟感测器市场预计将从 2025 年的 136.3 亿美元成长到 2031 年的 187.5 亿美元，复合年增长率达到 5.46%。

这些演算法软体解决方案，也称为软感测器，透过将数学模型应用于现有物理测量设备的数据来估算製程变量，而不是依赖直接测量。推动这一成长的关键因素包括硬体采购成本的大幅降低以及对预测性维护以避免系统故障日益增长的需求。此外，工业物联网 (IIoT) 的普及也加速了这些解决方案的推广，使操作人员能够在维护物理感测器不切实际或极高成本的环境中追踪参数。

根据製造业领导委员会的数据，89%的製造商计划在2025年维持或扩大对智慧工厂的投资，这表明数位诊断技术领域的资金将持续流入。儘管前景乐观，但市场仍面临与模型开发复杂性相关的重大障碍。在动态的工业环境中保持稳定的精度需要专业技能和定期调整，并且必须避免资料漂移。

市场驱动因素

对预测性维护和状态监控日益增长的需求是全球虚拟感测器市场的主要驱动力，促使工业运营商用演算法替代方案取代昂贵的实体测量设备，以最大限度地减少停机时间。虚拟感测器利用机器学习来推断无法直接测量的製程变量，正成为高效资产管理的关键要素。根据MaintainX于2025年5月发布的报告《2025年工业维护现况》，65%的企业计划在2026年前实施人工智慧驱动的维护解决方案，显示企业正明显转向软体定义的可靠性策略。这种转变将使製造商能够部署精准的、以数据为中心的监控工具，从而在无需承担在庞大的设施网路中安装硬体所带来的物流复杂性和成本的情况下，预防故障。

同时，工业4.0和智慧製造计画的扩展也增加了部署软感测器所需的基础设施。随着工厂数位化，人工智慧与控制系统的整合使得即时产生虚拟资料点成为可能，而无需额外的硬体。根据罗克韦尔自动化于2025年6月发布的第十份年度智慧製造报告，95%的製造商已投资或计划在未来五年内投资人工智慧和机器学习技术，为虚拟感测的部署创造了有利环境。这种数位化演进也与更广泛的环境目标相契合。根据IFS在2025年发布的报告显示，97%的製造商已将永续性列为优先事项，这推动了虚拟感测器在精确、非侵入性的能源和排放追踪方面的应用。

市场挑战

模型开发的固有复杂性对全球虚拟感测器市场的成长构成了重大障碍。与实体测量仪器不同，虚拟感测器依赖复杂的演算法，需要严格的检验和定期重新校准才能在不断变化的环境中保持精度。这种对持续技术监控的依赖增加了整体拥有成本，并迫使製造商投入大量资源来防止资料漂移。因此，维护这些模型所需的营运成本往往会抵消硬体的初始成本节省，导致潜在用户因缺乏充足的技术资源而犹豫不决。

此外，这些工具的整合也受到必要专业人才严重短缺的阻碍。建构可靠的软感测器需要程式工程和资料科学知识的特定组合，但目前很难找到同时具备这两种技能的人才。根据美国全国製造商协会（NAFM）预测，到2024年，对这些数位技术至关重要的模拟和模拟软体技能的需求将激增75%。这种巨大的技能缺口限制了工业运营商有效推广虚拟感测器应用的能力。

市场趋势

虚拟感测器与数位双胞胎模型的日益融合正在深刻地改变市场策略。这使得营运商能够利用这些演算法来模拟物理资产，并产生以前无法测量的参数数据。透过将软感测器整合到更广泛的模拟生态系统中，製造商可以建立全面的虚拟副本，从而填补资料空白并提高诊断精度，而无需额外的硬体。这种结构性变革得到了大量投资的支持。根据西门子2024年11月发布的报告《工业元宇宙现状》，全球62%的企业正在增加对工业元宇宙技术的投资，这显示他们对支撑先进虚拟感测的数位双胞胎框架有着坚定的承诺。

同时，虚拟感测演算法与边缘运算架构的融合，使得即时资料估计能够显着降低延迟并减少频宽的依赖。从集中式云端处理到边缘原生执行的转变，使得工业系统能够即时处理复杂的非线性变量，这对于远端或频宽受限环境下的封闭回路型控制应用至关重要。这种向分散式智慧的转变正在加速发展。根据IEB Media于2025年1月发布的《2024年工业网路报告》，31%的製造业将人工智慧设备列为首要投资重点，凸显了对承载先进边缘感测模型的基础设施日益增长的需求。

目录

第一章概述

第二章：调查方法

第三章执行摘要

第四章：客户心声

第五章：全球虚拟感测器市场展望

• 市场规模及预测
  • 按金额
• 市占率及预测
  • 按组件（解决方案、服务）
  • 部署方式（云端/本地）
  • 按最终用户（石油和天然气、製造业和公共产业、消费技术、汽车、航太和国防、医疗保健、化学等）
  • 按地区
  • 按公司（2025 年）
• 市场地图

第六章：北美虚拟感测器市场展望

• 市场规模及预测
• 市占率及预测
• 北美洲：国别分析
  • 我们
  • 加拿大
  • 墨西哥

第七章：欧洲虚拟感测器市场展望

• 市场规模及预测
• 市占率及预测
• 欧洲：国别分析
  • 德国
  • 法国
  • 英国
  • 义大利
  • 西班牙

第八章：亚太地区虚拟感测器市场展望

• 市场规模及预测
• 市占率及预测
• 亚太地区：国别分析
  • 中国
  • 印度
  • 日本
  • 韩国
  • 澳洲

第九章：中东和非洲虚拟感测器市场展望

• 市场规模及预测
• 市占率及预测
• 中东与非洲：国别分析
  • 沙乌地阿拉伯
  • 阿拉伯聯合大公国
  • 南非

第十章：南美洲虚拟感测器市场展望

• 市场规模及预测
• 市占率及预测
• 南美洲：国别分析
  • 巴西
  • 哥伦比亚
  • 阿根廷

第十一章 市场动态

• 促进因素
• 任务

第十二章 市场趋势与发展

• 併购
• 产品发布
• 近期趋势

第十三章：全球虚拟感测器市场：SWOT分析

第十四章：波特五力分析

• 产业竞争
• 新进入者的潜力
• 供应商的议价能力
• 顾客权力
• 替代品的威胁

第十五章 竞争格局

• Siemens AG
• Schneider Electric SE
• General Electric Company
• Honeywell International Inc
• ABB Ltd
• Rockwell Automation Inc
• Emerson Electric Co
• Cisco Systems, Inc
• Elliptic Labs A/S
• Aspen Technology, Inc

第十六章 策略建议

第十七章：关于研究公司及免责声明

The Global Virtual Sensors Market is projected to expand from a valuation of USD 13.63 Billion in 2025 to USD 18.75 Billion by 2031, achieving a CAGR of 5.46%. Also known as soft sensors, these algorithmic software solutions estimate process variables by applying mathematical models to data from existing physical instrumentation rather than relying on direct measurement. Key factors propelling this growth include substantial savings on hardware procurement costs and increasing requirements for predictive maintenance to avert system failures. Furthermore, the incorporation of the Industrial Internet of Things is hastening the uptake of these solutions, enabling operators to track parameters in settings where maintaining physical sensors is either impractical or prohibitively expensive.

Data from the Manufacturing Leadership Council indicates that in 2025, 89% of manufacturers intended to sustain or boost their investments in smart factories, signaling a continued flow of capital toward digital diagnostic technologies. Despite this favorable outlook, the market faces a significant hurdle related to the intricacies of model development, as maintaining consistent accuracy within dynamic industrial environments demands specialized skills and regular recalibration to avoid data drift.

Market Driver

The escalating need for predictive maintenance and condition monitoring serves as a major impetus for the Global Virtual Sensors Market, prompting industrial operators to substitute costly physical instrumentation with algorithmic alternatives to minimize downtime. Utilizing machine learning to deduce unmeasurable process variables, virtual sensors are becoming indispensable for efficient asset management. A May 2025 report by MaintainX, titled 'State of Industrial Maintenance 2025', reveals that 65% of organizations plan to deploy AI-driven maintenance solutions by 2026, marking a clear pivot toward software-defined reliability strategies. This shift enables manufacturers to implement precise, data-centric monitoring tools that avert failures without the logistical complexities and costs associated with installing hardware throughout extensive facility networks.

Concurrently, the spread of Industry 4.0 and smart manufacturing initiatives is broadening the infrastructure necessary for soft sensor deployment. As factories undergo digitization, integrating artificial intelligence into control systems facilitates the real-time creation of virtual data points without requiring extra hardware. According to the '10th Annual State of Smart Manufacturing Report' published by Rockwell Automation in June 2025, 95% of manufacturers have either invested in or intend to invest in AI and machine learning technologies within the next five years, fostering a supportive environment for virtual sensing adoption. This digital evolution also aligns with wider environmental objectives; IFS reported in 2025 that 97% of manufacturers have prioritized sustainability, thereby driving the utilization of virtual sensors for accurate, non-invasive energy and emissions tracking.

Market Challenge

The inherent complexity involved in developing models constitutes a significant obstacle to the growth of the Global Virtual Sensors Market. In contrast to physical instrumentation, virtual sensors depend on sophisticated algorithms that require strict validation and regular recalibration to sustain accuracy within changing environments. This reliance on continuous technical supervision elevates the total cost of ownership, obliging manufacturers to allocate considerable resources to prevent data drift. As a result, the operational demands of maintaining these models often negate the initial savings on hardware, leading to hesitation among potential adopters who lack extensive technical resources.

Furthermore, the integration of these tools is impeded by a severe scarcity of the specialized talent needed to support them. Creating reliable soft sensors requires a specific combination of process engineering and data science expertise, which is currently difficult to find. The National Association of Manufacturers noted that in 2024, there was a 75 percent surge in demand for simulation and simulation software skills essential for these digital technologies. This distinct skills gap restricts the capacity of industrial operators to effectively expand their virtual sensor deployments.

Market Trends

The growing incorporation of virtual sensors into digital twin models is significantly transforming market strategies, enabling operators to use these algorithms for simulating physical assets and generating data for parameters that are otherwise unmeasurable. By integrating soft sensors into wider simulation ecosystems, manufacturers can construct holistic virtual replicas that fill data voids and improve diagnostic accuracy without the need for additional hardware. This structural evolution is supported by substantial financial commitment; the 'State of the Industrial Metaverse' report by Siemens in November 2024 notes that 62% of global companies have boosted their investment in industrial metaverse technologies, indicating a firm dedication to the digital twin frameworks that underpin advanced virtual sensing.

At the same time, the merging of virtual sensing algorithms with edge computing architectures is facilitating real-time data estimation with significantly lowered latency and bandwidth reliance. Moving from centralized cloud processing to edge-native execution permits industrial systems to instantly process complex non-linear variables, a capability essential for closed-loop control applications in remote or bandwidth-limited settings. This shift toward decentralized intelligence is gaining momentum; according to the '2024 Industrial Networking Report' by IEB Media in January 2025, 31% of manufacturing firms listed AI-enabled devices as their primary investment priority, underscoring the increasing infrastructural need for hosting advanced edge-based sensing models.

Key Market Players

• Siemens AG
• Schneider Electric SE
• General Electric Company
• Honeywell International Inc
• ABB Ltd
• Rockwell Automation Inc
• Emerson Electric Co
• Cisco Systems, Inc
• Elliptic Labs A/S
• Aspen Technology, Inc

Report Scope

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

Virtual Sensors Market, By Component

• Solution
• Services

Virtual Sensors Market, By Deployment

• Cloud
• On-Premises

Virtual Sensors Market, By End-User

• Oil & Gas
• Manufacturing & Utilities
• Consumer Technology
• Automotive
• Aerospace & Defence
• Healthcare
• Chemical
• Others

Virtual Sensors Market, By Region

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
• South America
  • Brazil
  • Argentina
  • Colombia
• Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Virtual Sensors Market.

Available Customizations:

Global Virtual Sensors Market report with the given market data, TechSci 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. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, Trends

4. Voice of Customer

5. Global Virtual Sensors Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Component (Solution, Services)
  • 5.2.2. By Deployment (Cloud, On-Premises)
  • 5.2.3. By End-User (Oil & Gas, Manufacturing & Utilities, Consumer Technology, Automotive, Aerospace & Defence, Healthcare, Chemical, Others)
  • 5.2.4. By Region
  • 5.2.5. By Company (2025)
• 5.3. Market Map

6. North America Virtual Sensors Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Component
  • 6.2.2. By Deployment
  • 6.2.3. By End-User
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States Virtual Sensors Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Component
      • 6.3.1.2.2. By Deployment
      • 6.3.1.2.3. By End-User
  • 6.3.2. Canada Virtual Sensors Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Component
      • 6.3.2.2.2. By Deployment
      • 6.3.2.2.3. By End-User
  • 6.3.3. Mexico Virtual Sensors Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Component
      • 6.3.3.2.2. By Deployment
      • 6.3.3.2.3. By End-User

7. Europe Virtual Sensors Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Component
  • 7.2.2. By Deployment
  • 7.2.3. By End-User
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany Virtual Sensors Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Component
      • 7.3.1.2.2. By Deployment
      • 7.3.1.2.3. By End-User
  • 7.3.2. France Virtual Sensors Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Component
      • 7.3.2.2.2. By Deployment
      • 7.3.2.2.3. By End-User
  • 7.3.3. United Kingdom Virtual Sensors Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Component
      • 7.3.3.2.2. By Deployment
      • 7.3.3.2.3. By End-User
  • 7.3.4. Italy Virtual Sensors Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Component
      • 7.3.4.2.2. By Deployment
      • 7.3.4.2.3. By End-User
  • 7.3.5. Spain Virtual Sensors Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Component
      • 7.3.5.2.2. By Deployment
      • 7.3.5.2.3. By End-User

8. Asia Pacific Virtual Sensors 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 Deployment
  • 8.2.3. By End-User
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China Virtual Sensors 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 Deployment
      • 8.3.1.2.3. By End-User
  • 8.3.2. India Virtual Sensors 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 Deployment
      • 8.3.2.2.3. By End-User
  • 8.3.3. Japan Virtual Sensors 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 Deployment
      • 8.3.3.2.3. By End-User
  • 8.3.4. South Korea Virtual Sensors Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Component
      • 8.3.4.2.2. By Deployment
      • 8.3.4.2.3. By End-User
  • 8.3.5. Australia Virtual Sensors Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Component
      • 8.3.5.2.2. By Deployment
      • 8.3.5.2.3. By End-User

9. Middle East & Africa Virtual Sensors 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 Deployment
  • 9.2.3. By End-User
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia Virtual Sensors 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 Deployment
      • 9.3.1.2.3. By End-User
  • 9.3.2. UAE Virtual Sensors 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 Deployment
      • 9.3.2.2.3. By End-User
  • 9.3.3. South Africa Virtual Sensors 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 Deployment
      • 9.3.3.2.3. By End-User

10. South America Virtual Sensors 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 Deployment
  • 10.2.3. By End-User
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Virtual Sensors 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 Deployment
      • 10.3.1.2.3. By End-User
  • 10.3.2. Colombia Virtual Sensors 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 Deployment
      • 10.3.2.2.3. By End-User
  • 10.3.3. Argentina Virtual Sensors 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 Deployment
      • 10.3.3.2.3. By End-User

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends & Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Global Virtual Sensors Market: SWOT Analysis

14. Porter's Five Forces Analysis

• 14.1. Competition in the Industry
• 14.2. Potential of New Entrants
• 14.3. Power of Suppliers
• 14.4. Power of Customers
• 14.5. Threat of Substitute Products

15. Competitive Landscape

• 15.1. Siemens AG
  • 15.1.1. Business Overview
  • 15.1.2. Products & Services
  • 15.1.3. Recent Developments
  • 15.1.4. Key Personnel
  • 15.1.5. SWOT Analysis
• 15.2. Schneider Electric SE
• 15.3. General Electric Company
• 15.4. Honeywell International Inc
• 15.5. ABB Ltd
• 15.6. Rockwell Automation Inc
• 15.7. Emerson Electric Co
• 15.8. Cisco Systems, Inc
• 15.9. Elliptic Labs A/S
• 15.10. Aspen Technology, Inc

16. Strategic Recommendations

17. About Us & Disclaimer