Virtual Sensors Market - Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented, By Component (Solution, Services), By Deployment (Cloud, On-Premises), By End-User (Oil & Gas, Manufacturing & Utilities, Consumer Technology, Automotive, Aerospace & Defence, Healthcare, Chemical, and Others), By Region, By Competition, 2021-2031F

Forecast Period	2027-2031
Market Size (2025)	USD 13.63 Billion
CAGR (2026-2031)	5.46%
Fastest Growing Segment	On-Premises
Largest Market	North America
Market Size (2031)	USD 18.75 Billion

Market Overview

The Global Virtual Sensors Market will grow from USD 13.63 Billion in 2025 to USD 18.75 Billion by 2031 at a 5.46% CAGR. Virtual sensors, often referred to as soft sensors, are algorithmic software tools that estimate process variables by processing data from physical instrumentation through mathematical models rather than via direct measurement. The primary drivers supporting market growth include the significant reduction in hardware procurement costs and the rising demand for predictive maintenance to prevent system failures. Additionally, the integration of the Industrial Internet of Things is accelerating the adoption of these solutions, allowing operators to monitor parameters in environments where physical instrumentation is impractical or too costly to maintain.

According to the Manufacturing Leadership Council, in 2025, 89% of manufacturers planned to maintain or increase their smart factory investments, reflecting a sustained capital influx into digital diagnostic technologies. Despite this positive trajectory, the market encounters a substantial challenge regarding the complexity of model development, as ensuring consistent accuracy in dynamic industrial settings requires specialized expertise and frequent recalibration to prevent data drift.

Key Market Drivers

The surging demand for predictive maintenance and condition monitoring is a primary catalyst for the Global Virtual Sensors Market, as industrial operators increasingly replace expensive physical instrumentation with algorithmic alternatives to reduce downtime. Virtual sensors, which utilize machine learning to infer unmeasurable process variables, are becoming essential for cost-effective asset management. According to MaintainX, May 2025, in the 'State of Industrial Maintenance 2025' report, 65% of organizations expect to implement AI-powered maintenance solutions by 2026, reflecting a decisive shift toward software-defined reliability strategies. This transition allows manufacturers to adopt granular, data-driven monitoring tools that prevent failures without the logistical burden and expense of installing hardware across complex facility networks.

Simultaneously, the proliferation of Industry 4.0 and smart manufacturing initiatives is expanding the infrastructure required for soft sensor deployment. As factories digitize, the integration of artificial intelligence into control systems allows for the real-time generation of virtual data points without additional hardware. According to Rockwell Automation, June 2025, in the '10th Annual State of Smart Manufacturing Report', 95% of manufacturers have either invested in or plan to invest in AI and machine learning technologies over the next five years, creating a fertile ecosystem for virtual sensing adoption. This digital maturation also supports broader environmental goals; according to IFS, in 2025, 97% of manufacturers have established sustainability as a strategic priority, driving the use of virtual sensors for precise, non-invasive emissions and energy tracking.

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Key Market Challenges

The complexity inherent in model development stands as a formidable barrier restricting the expansion of the Global Virtual Sensors Market. Unlike physical instrumentation, virtual sensors rely on intricate algorithms that demand rigorous validation and frequent recalibration to maintain accuracy in dynamic environments. This dependency on continuous technical oversight increases the total cost of ownership, as manufacturers must dedicate substantial resources to prevent data drift. Consequently, the operational burden of maintaining these models often outweighs the initial hardware savings, causing hesitation among adopters who lack deep technical capabilities.

The integration of these tools is further hampered by a critical shortage of the specialized talent required to sustain them. Developing robust soft sensors necessitates a unique blend of data science and process engineering expertise which is currently in short supply. According to the National Association of Manufacturers, in 2024, there was a 75 percent increase in the demand for simulation and simulation software skills specifically required for such digital technologies. This acute skills gap limits the ability of industrial operators to scale virtual sensor deployments effectively.

Key Market Trends

The increasing deployment of virtual sensors within digital twin models is fundamentally reshaping market strategies, as operators utilize these algorithms to simulate physical assets and generate data for parameters that are otherwise impossible to measure. By embedding soft sensors into broader simulation ecosystems, manufacturers can create comprehensive virtual replicas that bridge data gaps and enhance diagnostic precision without deploying additional hardware. This structural shift is evidenced by significant capital allocation; according to Siemens, November 2024, in the 'State of the Industrial Metaverse' report, 62% of globally operating companies increased their spending on industrial metaverse technologies, reflecting a decisive commitment to the digital twin frameworks that support advanced virtual sensing.

Simultaneously, the convergence of virtual sensing algorithms with edge computing architectures is enabling real-time data estimation with dramatically reduced latency and bandwidth dependency. This movement from centralized cloud processing to edge-native execution allows industrial systems to process complex non-linear variables instantaneously, which is critical for closed-loop control applications in remote or bandwidth-constrained environments. This transition toward decentralized intelligence is rapidly accelerating; according to IEB Media, January 2025, in the '2024 Industrial Networking Report', 31% of manufacturing firms identified AI-enabled devices as their top investment priority, highlighting the growing infrastructure demand for hosting sophisticated edge-based sensing models.

Segmental Insights

Based on market analysis from trusted industry sources, the On-Premises deployment segment is emerging as the fastest-growing category in the Global Virtual Sensors Market. This rapid expansion is primarily driven by the escalating demand for enhanced data security and strict regulatory compliance within critical sectors such as defense, healthcare, and utilities. Organizations are increasingly prioritizing on-site infrastructure to maintain absolute sovereignty over sensitive operational data and to eliminate the latency issues associated with cloud transmission. Furthermore, the surge in edge computing adoption is accelerating the deployment of on-premises solutions, allowing enterprises to process complex sensor data locally with superior speed and reliability.

Regional Insights

North America holds the leading position in the Global Virtual Sensors Market due to the extensive adoption of cloud computing and the Internet of Things across industrial sectors. The region benefits from a dense concentration of technology developers and substantial investments in research and development for predictive maintenance. Furthermore, the established automotive and aerospace industries in the United States and Canada actively integrate software-based sensing solutions to enhance operational efficiency. This strong technological infrastructure and focus on digital transformation enable the region to sustain its dominance in the global landscape.

Recent Developments

• In May 2025, Aspen Technology launched version 15 of its software suite, which introduced significantly expanded industrial artificial intelligence capabilities suitable for the virtual sensors market. The update included new soft sensor features designed to enhance sustainability and operational efficiency for asset-intensive industries. The release focused on enabling users to utilize virtual sensors for real-time performance monitoring, emissions tracking, and digital facility layout creation. The company highlighted that these advancements allowed for superior decision-making and predictive modeling, helping organizations address power reliability and meet net-zero goals by optimizing resource usage across their global operations.
• In November 2024, Tactile Mobility announced the release of its Virtual Tire Wear Sensor software, a solution designed to monitor tire health without the need for additional hardware. The new offering utilized advanced algorithms to analyze existing vehicle signal data, providing real-time insights into tire conditions with high precision. The company stated that this virtual sensor technology could detect wear changes within a remarkably small margin of error, rivaling manual measurements. This development was aimed at enhancing road safety and reducing maintenance costs for fleet operators and autonomous vehicle manufacturers by enabling predictive maintenance and preventing potential tire-related accidents.
• In June 2024, Eatron Technologies collaborated with Syntiant to launch a new AI-powered Battery Management System-on-Chip. This partnership integrated Eatron’s Intelligent Software Layer, which utilizes virtual sensing technology for battery health monitoring, with Syntiant’s low-power neural decision processor. The joint solution was designed to operate on the edge, delivering real-time analysis and decision-making directly on the device without requiring complex cloud infrastructure. The companies claimed this innovation could extend battery lifespan by up to 25% and unlock additional capacity, effectively addressing performance and safety challenges in light mobility, industrial, and consumer electronics applications.
• In January 2024, Stellantis N.V. acquired the artificial intelligence framework and intellectual property of CloudMade, a developer of big data-driven automotive solutions. This strategic move aimed to accelerate the development of the STLA SmartCockpit and support the company's mid-term software strategy. The acquisition included machine learning models that function as virtual sensors, allowing the system to collect and analyze automotive data for personalized and predictive features. By integrating these AI-powered capabilities, the automotive manufacturer intended to enhance vehicle diagnostics and predictive maintenance while reducing reliance on physical hardware, ultimately improving the mobility experience for customers.

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

By Component	By Deployment	By End-User	By Region
Solution Services	Cloud On-Premises	Oil & Gas Manufacturing & Utilities Consumer Technology Automotive Aerospace & Defence Healthcare Chemical Others	North America Europe Asia Pacific South America Middle East & Africa

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