虛擬感測器市場－全球產業規模、佔有率、趨勢、機會、預測：按組件、部署方式、最終用戶、地區和競爭對手分類，2021-2031年

全球虛擬感測器市場預計將從 2025 年的 136.3 億美元成長到 2031 年的 187.5 億美元，複合年成長率達到 5.46%。

這些演算法軟體解決方案，也稱為軟感測器，透過將數學模型應用於現有物理測量設備的數據來估算製程變量，而不是依賴直接測量。推動這一成長的關鍵因素包括硬體採購成本的大幅降低以及對預測性維護以避免系統故障日益成長的需求。此外，工業物聯網 (IIoT) 的普及也加速了這些解決方案的推廣，使操作人員能夠在維護物理感測器不切實際或極高成本的環境中追蹤參數。

根據製造業領導委員會的數據，89%的製造商計劃在2025年維持或擴大對智慧工廠的投資，這表明數位診斷技術領域的資金將持續流入。儘管前景樂觀，但市場仍面臨與模型開發複雜性相關的重大障礙。在動態的工業環境中保持穩定的精度需要專業技能和定期調整，並且必須避免資料漂移。

市場促進因素

對預測性維護和狀態監控日益成長的需求是全球虛擬感測器市場的主要驅動力，促使工業運營商用演算法替代方案取代昂貴的實體測量設備，以最大限度地減少停機時間。虛擬感測器利用機器學習來推斷無法直接測量的製程變量，正成為高效資產管理的關鍵要素。根據MaintainX於2025年5月發布的報告《2025年工業維護現況》，65%的企業計劃在2026年前實施人工智慧驅動的維護解決方案，顯示企業正明顯轉向軟體定義的可靠性策略。這種轉變將使製造商能夠部署精準的、以數據為中心的監控工具，從而在無需承擔在龐大的設施網路中安裝硬體所帶來的物流複雜性和成本的情況下，預防故障。

同時，工業4.0和智慧製造計畫的擴展也增加了部署軟感測器所需的基礎設施。隨著工廠數位化，人工智慧與控制系統的整合使得即時產生虛擬資料點成為可能，而無需額外的硬體。根據羅克韋爾自動化於2025年6月發布的第十份年度智慧製造報告，95%的製造商已投資或計劃在未來五年內投資人工智慧和機器學習技術，為虛擬感測的部署創造了有利環境。這種數位化演進也與更廣泛的環境目標相契合。根據IFS在2025年發布的報告顯示，97%的製造商已將永續性列為優先事項，這推動了虛擬感測器在精確、非侵入性的能源和排放追蹤方面的應用。

市場挑戰

模型開發的固有複雜性對全球虛擬感測器市場的成長構成了重大障礙。與實體測量儀器不同，虛擬感測器依賴複雜的演算法，需要嚴格的檢驗和定期重新校準才能在不斷變化的環境中保持精度。這種對持續技術監控的依賴增加了整體擁有成本，並迫使製造商投入大量資源來防止資料漂移。因此，維護這些模型所需的營運成本往往會抵消硬體的初始成本節省，導致潛在用戶因缺乏充足的技術資源而猶豫不決。

此外，這些工具的整合也受到必要專業人才嚴重短缺的阻礙。建構可靠的軟感測器需要程式工程和資料科學知識的特定組合，但目前很難找到同時具備這兩種技能的人才。根據美國全國製造商協會（NAFM）預測，到2024年，對這些數位技術至關重要的模擬和模擬軟體技能的需求將激增75%。這種巨大的技能缺口限制了工業運營商有效推廣虛擬感測器應用的能力。

市場趨勢

虛擬感測器與數位雙胞胎模型的日益融合正在深刻地改變市場策略。這使得營運商能夠利用這些演算法來模擬物理資產，並產生以前無法測量的參數數據。透過將軟感測器整合到更廣泛的模擬生態系統中，製造商可以建立全面的虛擬副本，從而填補資料空白並提高診斷精度，而無需額外的硬體。這種結構性變革得到了大量投資的支持。根據西門子2024年11月發布的報告《工業元宇宙現狀》，全球62%的企業正在增加對工業元宇宙技術的投資，這顯示他們對支撐先進虛擬感測的數位雙胞胎框架有著堅定的承諾。

同時，虛擬感測演算法與邊緣運算架構的融合，使得即時資料估計能夠顯著降低延遲並減少頻寬的依賴。從集中式雲端處理到邊緣原生執行的轉變，使得工業系統能夠即時處理複雜的非線性變量，這對於遠端或頻寬受限環境下的封閉回路型控制應用至關重要。這種向分散式智慧的轉變正在加速發展。根據IEB Media於2025年1月發布的《2024年工業網路報告》，31%的製造業將人工智慧設備列為首要投資重點，凸顯了對承載先進邊緣感測模型的基礎設施日益成長的需求。

目錄

第1章概述

第2章：調查方法

第3章執行摘要

第4章：客戶心聲

第5章：全球虛擬感測器市場展望

• 市場規模及預測
  • 按金額
• 市佔率及預測
  • 按組件（解決方案、服務）
  • 部署方式（雲端/本地）
  • 按最終用戶（石油和天然氣、製造業和公共產業、消費技術、汽車、航太和國防、醫療保健、化學等）
  • 按地區
  • 按公司（2025 年）
• 市場地圖

第6章：北美虛擬感測器市場展望

• 市場規模及預測
• 市佔率及預測
• 北美洲：國別分析
  • 美國
  • 加拿大
  • 墨西哥

第7章：歐洲虛擬感測器市場展望

• 市場規模及預測
• 市佔率及預測
• 歐洲：國別分析
  • 德國
  • 法國
  • 英國
  • 義大利
  • 西班牙

第8章：亞太地區虛擬感測器市場展望

• 市場規模及預測
• 市佔率及預測
• 亞太地區：國別分析
  • 中國
  • 印度
  • 日本
  • 韓國
  • 澳洲

第9章：中東和非洲虛擬感測器市場展望

• 市場規模及預測
• 市佔率及預測
• 中東與非洲：國別分析
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國
  • 南非

第10章：南美洲虛擬感測器市場展望

• 市場規模及預測
• 市佔率及預測
• 南美洲：國別分析
  • 巴西
  • 哥倫比亞
  • 阿根廷

第11章 市場動態

• 促進因素
• 任務

第12章 市場趨勢與發展

• 併購
• 產品發布
• 近期趨勢

第13章：全球虛擬感測器市場：SWOT分析

第14章：波特五力分析

• 產業競爭
• 新進入者的潛力
• 供應商的議價能力
• 顧客權力
• 替代品的威脅

第15章 競爭格局

• 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16章 策略建議

第17章：關於研究公司及免責聲明

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