Automotive Predictive Maintenance Sensor Market Size & Share 2025 - 2034

Automotive Predictive Maintenance Sensor Market Size

The global automotive predictive maintenance sensor market was estimated at USD 735.7 million in 2024. The market is expected to grow from USD 768.8 million in 2025 to USD 1.45 billion in 2034, at a CAGR of 7.3%, according to the latest report published by Global Market Insights Inc.

The automotive predictive maintenance sensors market is evolving rapidly mainly due to the increasing need for reliability, safety, and cost savings for vehicles. Predictive maintenance sensors can sense indications of critical vehicle parts and provide a live view of the health of the system and recognize indicators of impending failures before they happen.
 

This allows a vehicle owner to shift the maintenance paradigm from reactive or scheduled to proactive and improves whether the vehicle is operational (up-time) and reduces the operating cost of the vehicle.
 

One of the primary contributors to market growth is the intricacy of modern vehicles which contain significant number of automated mechanical and electrical systems. The more technology that is added to the vehicle the higher risk of part failure. Thus, continuous monitoring is needed.
 

In addition, there are government safety agencies that are implementing more severe standards of safety which are created more a source for the vehicle manufacturers to be developing and implementing increasingly more advanced diagnostic systems. Connected vehicles, which are maintained by IoT infrastructure, would support consolidated data collection and data analytics which would improve the efficacy and speed of the maintaining prediction service.
 

The market is also influenced by the changing trends in the industry toward data-driven maintenance strategies. Predictive maintenance is becoming more common across the lifecycle of a vehicle, from design, through production, and into normal operation.
 

The emergence of onboard diagnostics and telematics generates large amounts of data, and machine learning uses that data, to identify subtle trends that are a sign of upcoming wear and possible failure. Instead of maintaining a vehicle based on a time schedule, a vehicle can be maintained, when required, according to observable condition, putting the vehicle back into service rather than replacing components.
 

Technological advancements also allow improved performance of predictive maintenance systems. Emerging advancement associated with wireless sensing technology, vibration/thermal analysis, and AI driven digital twins all provide further opportunity for detailed understanding of vehicle condition.
 

Digital twins create virtual simulations of vehicle component behavior, to allow manufacturers and fleet managers to understand possible failure modes, and to enhance the predictive value associated with preventative maintenance or repair scheduling.
 

From a regional perspective, the Asia-Pacific market is leading in adopting predictive maintenance and sensor technologies in the automotive industry, owing to the growing automotive manufacturing base in the region, the rapid urbanization taking place, and the increased investments in smart mobility such as predictive maintenance.
 

Achieving connected vehicle ecosystems, as well as advanced analytics platforms are critical to deploy predictive maintenance, making the adoption in countries like China, Japan, and South Korea more notable as they major markets in the automotive sector.
 

Automotive Predictive Maintenance Sensor Market Trends

The market for automotive predictive maintenance sensors is witnessing advanced trends such as development of predictive maintenance systems that integrate with emerging vehicle-to-everything (V2X) communication technologies. These technologies allow vehicles to communicate with elements of the infrastructure, with each other, and cloud infrastructure in real time.
 

Predictive maintenance sensors can access this connected supply chain to obtain and transmit information about road conditions, traffic, and hazards that will enable timely, proactive maintenance decisions which improve safety and reduce breakdown risk.
 

Another trend is the integration of edge computing into predictive maintenance systems. Edge computing processes data in the vehicle's range, thereby improving speed and mitigating excessive data transfers to a central server. This is very useful when the consumer demands real time diagnostics, especially when analytics are needed in urgent situations like autonomous driving scenarios or critical safety situations like emergency braking.
 

Wireless sensor networks (WSNs) are also being used in automotive predictive maintenance. Wireless data can be gathered from several components with little to no wiring required, which reduces complexity and cost of installation, as well as allows for continuous and holistic tracking of critical systems (e.g. brakes, engines, transmissions). Data is gathered using WSNs and sent to a centralized data gathering and analysis platform with little friction to develop better predictive models and maintenance plans.
 

Furthermore, multi-modal sensor fusion is harnessing to address predictive mechanic’s breadth and accuracy. This includes combining data from different sensor types such as acoustic sensors, thermal sensors, and vibration sensors into a composite approach that can identify a broader fault potential than could an individual sensor type measure.
 

Operators of commercial fleets are adopting predictive maintenance systems to assist in their metrics of vehicle uptime efficiency. Many leading logistics companies are using WSNs to monitor the health of their delivery trucks in transport, to schedule maintenance cycles based on a truck's condition versus pre-set intervals. This general approach to vehicle maintenance extends the life of the vehicle, enhances vehicle uptime, and improves service quality leading to greater customer satisfaction.
 

Automotive Predictive Maintenance Sensor Market Analysis

Based on sensor, the market is divided among vibration sensor, temperature sensor, pressure sensor, humidity sensor, acoustic sensor, and others. The temperature sensor segment dominated around 35% market share in 2024 and is expected to grow at a CAGR of over 9.14% through 2034.
 

• The automotive predictive maintenance sensor market is experiencing strong growth, with temperature sensor technology being the most prevalent. Temperature sensors are essential for monitoring vital systems in the vehicle, such as the engine, battery management unit, and HVAC systems, which all can lead to possible mechanical failure due to temperature variances, from overheating to component fatigue.
   
• Temperature sensors support predictive maintenance by providing real-time data, allowing repairs to be carried out at the optimal time. This helps reduce repair costs and enhance vehicle reliability.
   
• The growing popularity of electric vehicles has led to an increased need for temperature sensors. Electric vehicles require accurate thermal management systems to ensure battery safety and battery life.
   
• Temperature sensors are used to monitor battery temperature as a means of preventing thermal runaway while also providing additional support for the normal charging cycle. Enhanced battery life with temperature sensors results in better performance and greater safety. As demand for electric vehicles continues to grow, the importance of temperature sensing technology becomes crucial.
   
• Aside from electric vehicles, temperature sensors are vital in traditional internal combustion (IC) engine vehicles. Temperature sensors keep track of the engine coolant temperatures to ensure that the engine runs at the ideal thermal conditions.
   
• Temperature management is essential for improving fuel efficiency, reducing emissions, and avoiding damage to engine components caused by overheating. The use of temperature sensors indicates their relevance and universality across vehicle types.
   
• Furthermore, temperature sensors have been enhanced through the power of internet of things (IoT) technology. Temperature sensors equipped with IoT functionality can measure and monitor vehicle temperatures and connect to the Internet for enhanced data collection, reporting and advanced analysis capabilities.
   
• Other sensors, including vibration, pressure, humidity, and acoustic sensors, also play a crucial role in the predictive maintenance ecosystem. Vibration sensors help spot mechanical issues at their early stages, pressure sensors check for the integrity of systems, humidity sensors help what can cause corrosion, and acoustic sensors can help identify minor anomalies by examining sound signals.
   
• Understanding the overall operational environment is possible by combining temperature sensors with other sensors for a well-designed vehicle monitoring suite.

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Based on application, the automotive predictive maintenance sensor market is segmented into engine health monitoring, transmission & gearbox monitoring, battery & electrical system monitoring, tire & wheel monitoring, cooling system monitoring, and others. The engine health monitoring segment dominated the market with around 34% share in 2024 and is expected to grow at a CAGR of 7.04% from 2025 to 2034.
 

• The engine health monitoring segment occupies the largest share of the automotive predictive maintenance sensor market, as the engine is a critical component in vehicle performance. Additionally, it can be expensive to replace or repair an engine in case of failure. Sensors in this segment monitor various engine parameters, including fuel efficiency, temperature, and vibration patterns.
   
• By identifying potential signs of wear and tear, or an engine malfunction, predictive maintenance initiated by these sensors reduce unexpected engine breakdowns, which extends the life of the engine, sustains adequate vehicle performance, and lowers maintenance costs for owners and fleet administrators.
   
• Transmissions and gearboxes is the second highest segment by value. Sensors in this application area diagnose transmission fluid quality, gear shifting workload, and torque problems. The emergence of smart gearboxes with integrated sensors for tracking real-time data allows for quick diagnosis and decision-making about maintenance opportunities to prevent repair costs from unexpected transmission road failures while increasing vehicle efficiencies.
   
• As electric and hybrid vehicles demand is increasing, battery and electric systems monitoring is becoming important. Sensors, in particular electronic battery monitoring systems, provide advanced and hardened data regarding the battery state of health.
   
• This data can be used with energy management systems to optimize overall battery performance, enhance fuel economy and develop advanced solutions which may include firmware updates and predictive diagnostics to support reliability for the latest vehicles.
   
• Monitoring tire and wheel condition has also been important for vehicle safety. Advanced sensor systems monitor tire pressure, temperature, and tread wear, for example, to notify vehicle occupants of potentially unsafe events, such as tire being under-inflated, or tread uneven wear. Monitoring tire condition can create safer vehicles and increase fuel economy.
   
• Monitoring the cooling system including operating temperature and coolant flow rates is crucial for preventing engine overheating. By keeping these parameters within optimal ranges, the risk of engine failure can be significantly reduced. Any faults in the cooling system can be identified or detected to allow for servicing and to eliminate expensive repairs.
   

Based on vehicle, the automotive predictive maintenance sensor market is segmented into passenger cars, and commercial vehicles. The passenger cars segment dominate the market with around 75% of revenue share in 2024.
 

• Passenger vehicles have the largest share of the market, and this is driven largely by the growing incorporation of advanced safety features and predictive technology in contemporary passenger vehicles. Manufacturers continue to enhance their driving experience and safety system, increasingly through the incorporation of artificial intelligence and machine learning.
   
• Collision mitigation braking, forward collision warning, and lane departure warnings have become common in many passenger cars. Furthermore, the rising consumer interest in connected car technology and autonomous driving has strengthened this segment of the market.
   
• The commercial vehicle market comprised of trucks, buses, and delivery vans is an important and growing segment of the market. Fleet operators in logistics, transportation, and public transit use predictive maintenance to optimize fleet utilization, minimize unplanned downtime, and ensure compliance with regulatory standards. As high operating costs and growing global competition become the norm, predictive maintenance has emerged as a vital strategy for enhancing profitability and service reliability in commercial fleets.
   
• In terms of technology, advanced driver assistance systems (ADAS) and telematics allow for real-time visibility into the vehicle, for passenger, fleet, and commercial automotive operators. Ease of use provides better safety and security, along with proactive alerts for alerts and advanced diagnostics.
   

Based on sales channel, the automotive predictive maintenance sensor market is segmented into OEMs, and aftermarket. The OEMs segment dominated the market with share of around 78% in 2024.
 

• There is a significant importance of original equipment manufacturer (OEM) in the automotive predictive maintenance sector. OEMs install sensors onboard during the vehicle assembly to have an optimal configuration, calibration and integration with the vehicle diagnostic and telematics.
   
• The sensor is onboard as part of the vehicle assembly process, data will be continuously collected for the entire lifetime of the vehicle and will provide a complete data set for predictive analytics. Automotive manufacturers are adding and integrating highly sophisticated sensor networks and AI-based systems to monitor new vehicles for reliability, warranty cost management, and customer satisfaction.
   
• Some of the OEM predictive maintenance sensor drivers are also regulatory and warranty based. Emission and safety regulations in the largest markets generally require onboard diagnostics and continuous monitoring by manufacturers and thus pushing OEMs to develop and integrate higher-level sensors and sensor monitoring strategies.
   
• The aftermarket doesn't produce circumstances OEMs face, consistently utilizing a range of vehicle models, not having standard data architecture, and not having nearly the integration possibilities. This structural and other realities put OEMs in a distinctly different position than the aftermarket.
   
• For example, Toyota Motor Corporation has deployed an IoT-based predictive maintenance system in its Blue Springs location in North America. The predictive maintenance system utilizes real-time monitoring of equipment health to repair mechanically, thereby increasing time of production efficiency.
   
• OEMs are prevalent in the current state of predictive maintenance sensors, the aftermarket portion of the market is also critical and has been growing rapidly. As such, aftermarket players offer kits to retrofit these vehicles, along with supplemental plug-and-play sensors and connectivity modules to allow predictive diagnostics for older vehicles or lower-tier models.
   
• This is an important segment of the market for fleet operators, and owners of older vehicles who want to enhance efficiency, safety, and scheduling of existing maintenance without overhauling their entire fleets.

Asia Pacific dominated the automotive predictive maintenance sensor market with around 44% share and generated around USD 323.7 million revenue in 2024.
 

• The Asia Pacific dominates the market owing to combination of structural, economic, and technological factors. The Asia Pacific region is the largest automotive manufacturing hub, contributing to more than half of the world's vehicles produced, thus yielding significant demand for modern sensor technologies.
   
• The immense growth of electrification, connectivity and autonomous driving technologies in the region solidify the Asia Pacific market position. Automotive manufacturers in the Asia Pacific region are investing heavily into smart vehicle architectures that utilize real-time data supplied from predictive maintenance sensors.
   
• Connected vehicle technologies are being embedded into passenger cars and commercial vehicles in China, Japan, and India to monitor performance, safety, and reliability. This concentrated effort on next generation mobility solutions is effectively translating into deployments of advanced sensor systems for condition monitoring and predictive diagnostics systems.
   
• Government programs around the Asia Pacific have also supported the overall market landscape. Government initiatives such as China’s “Made in China 2025,” Japan’s “Society 5.0,” and India’s “Make in India” also support the digital transformation of manufacturing and the adoption of smart factory technologies.
   
• Specifically, these programs promote the adoption of Internet of Things (IoT) and AI driven predictive maintenance systems in the automotive supply chain, which promotes increased use of sensors to monitor health on components, reduce downtime, and reduce maintenance cycles.
   
• In addition to these government programs, there are several concrete examples of implementation, which only reinforce the Asia Pacific's leadership. For instance, Japan has several automotive component manufacturers, who have adopted AI systems for predictive maintenance to monitor failure on gearbox and powertrain components and reduce unintended failure.
   

North America automotive predictive maintenance sensor market accounted for USD 163.9 million in 2024 and is anticipated to show lucrative growth over the forecast period.
 

• The North American demand for automotive predictive maintenance sensors is forecasted to achieve solid, sustained growth during the forecast period driven by the advanced production of vehicles and proper regulatory compliance coupled with the early uptake of connected and electric vehicles.
   
• In the US the growth is primarily driven by the continued integration of smart sensors and analytics into vehicle systems and the automation of production facilities. The movement to electric and hybrid vehicles has quickly accelerated the adoption of predictive maintenance sensors, due to the needs for dual and real-time monitoring of battery performance, electronic components, and driveline systems.
   
• Demand is also supported by government programs and regulatory agencies, such as the Environmental Protection Agency (EPA) and Department of Energy (DOE), assisting demand through regulations which encourage OEMs to offer advanced sensing for emissions reduction, improved efficiency and longevity through predictive maintenance systems in vehicles.
   
• Manufacturing facilities throughout North America are tapping into sensor-based predictive maintenance technologies to improve operational effectiveness. Multiple automotive suppliers located in the US have installed vibration and pressure sensors within cloud-based monitoring platforms to ensure the health of their equipment is monitored in a timely manner.
   
• Similarly, in Canada, automotive manufacturers are adopting AI-enabled condition monitoring systems for their machines and equipment. Magna International, for example, has significantly reduced unplanned equipment downtime.
   
• In this instance, in process-based manufacturing, advanced sensors and analytics were incorporated into the company's production line, illustrating how Canadian manufacturers are embracing data-driven strategies as part of their operations. This commitment to agile manufacturing and maintenance aligns with trends observed in Industry 4.0. and smart manufacturing found throughout the world.
   

Europe automotive predictive maintenance sensor market accounted for USD 184.7 million in 2024 and is anticipated to show lucrative growth over the forecast period.
 

• The European market is poised for substantial growth during the projected time frame, supported by the region's robust automotive manufacturing ecosystem, tightened regulatory requirements, and growing adoption of digital and connected technologies.
   
• In Germany, the automotive hub of Europe, many major OEMs and suppliers have begun using predictive maintenance technologies within the context of Industry 4.0. For example, several tier-1 suppliers providing components to automakers such as BMW and Volkswagen have installed vibration, pressure, and temperature sensors throughout their production lines to determine when a piece of equipment is likely to fail before it fails.
   
• In one of these cases with a robotic assembly arm, following the introduction of the predictive system, the company reduced its unplanned downtime significantly and improved production efficiency, indicating how predictive sensor systems currently have a central role in German automotive manufacturing.
   
• France and the UK are also making solid progress in this domain. In France, automotive electronics firms are developing high-fidelity thermal and pressure sensors that can be integrated into electric powertrains and battery management systems providing predictive insights to enhance performance and safety.
   
• In the UK, leading automotive plants and engineering companies are moving from time-based servicing to condition-based maintenance, supported by AI and Internet of Things (IoT)-enabled sensors. This shift increases reliability, reduces maintenance costs, and strengthens sustainability throughout the vehicle lifecycle.
   
• At the policy level, the European Union and the European Automobile Manufacturers Association (ACEA), have developed regulations, standards and frameworks to improve vehicle safety and emissions legislation and monitor digital data to support these aims.
   

Latin America automotive predictive maintenance sensor market accounted for around USD 34.7 million in 2024 and is anticipated to show robust growth over the forecast period.
 

• The Latin American automotive predictive maintenance sensor industry is positioned for significant expansion during the estimation period, fueled by rising automotive production, new Industry 4.0 initiatives, and an expanding fleet size of aging vehicles requiring predictive maintenance solutions.
   
• In some key countries like Brazil and Mexico, advances toward smarter vehicle space architectures, similar architectures for connected vehicle components, and improved condition monitoring with sensors have created a solid base for adoption of predictive maintenance sensors.
   
• Mexico is also becoming an important player, particularly in view of its solid automotive export base and its advances in smart manufacturing. While there is a deficit of explicit sensor-for-vehicles data, general regional undertakings in predictive maintenance suggest that Mexico will have one of the highest projected growth rates in Latin America.
   
• In industrial settings, organizations in Latin America report that through the application of sensor-enabled predictive platforms there has been an approximately 25% reduction in unplanned downtime and an 18% decrease in maintenance costs. This serves as proxy for broader uptake that includes automotive.
   
• A concrete example from Brazil is informative. In Pernambuco, and in association with a local research center and a large global packaging company, sensor-based predictive analytics were deployed to determine machinery health and optimize scheduling of maintenance at a manufacturing facility.
   
• Additionally, a Brazil-based study in the automotive space has shown an IoT-edge platform which proves its usefulness for monitoring industrial machines and executing predictive maintenance in the context of vehicle-component manufacturing.
   

Middle East and Africa market accounted for USD 28.6 million in 2024 and is anticipated to show lucrative growth over the forecast period.
 

• The automotive predictive maintenance sensor market in the Middle East and Africa (MEA) region is anticipated to undergo a notable increase during the forecast period, part of the continuous growth trend powered by a rising number of vehicles and fleets, increased digitalization of maintenance processes, the increasing use and maturity of automation in manufacturing and services infrastructures.
   
• Countries such as Saudi Arabia and the UAE are at the forefront of this emerging space and supported by changing manufacturing goals in tandem with high car ownership and strong government backing for smart mobility and Industry 4.0 technologies.
   
• The government of Saudi Arabia’s Vision 2030 program emphasizes localizing manufacturing, deploying advanced sensor and IoT capabilities in production and vehicle systems, and advancing electric and connected vehicle strategies.
   
• According to research completed in the automotive space, these plans aim to implement Industry 4.0 strategies such as real-time monitoring, and predictive maintenance capabilities on production lines, to increase productivity and enhance sustainability.
   
• Localizing production with embedded sensors and advanced analytics and monitoring capabilities is a significant step to delivering in reduced downtime. Furthermore, the evolution of the heavy-duty automotive aftermarkets via digital technologies such as telematics and predictive maintenance solutions is driving transformation of services supporting commercial vehicles, thus creating a diverse basis for growth for predictive maintenance sensors across both OEM and aftermarket use cases.
   
• As the continent's largest automaker, South Africa and its well-established component manufacturing sector complements regional growth potential. While there are no figures on predictive maintenance sensors specifically, as the automotive ecosystems expand, the number of vehicles with advanced systems and predictable maintenance will continue to increase alongside their support networks.
   

Automotive Predictive Maintenance Sensor Market Share

• The top 7 companies in the automotive predictive maintenance sensor industry are Robert Bosch, Continental, Infineon Technologies, TE Connectivity, Valeo, STMicroelectronics, and Hella. These companies hold around 57% of the market share in 2024.
   
• Robert Bosch is a leading innovator in automotive sensor technology, providing advanced temperature, pressure, and vibration sensors for predictive maintenance. By integrating AI and IoT, Bosch enables real-time diagnostics and fault detection to improve vehicle reliability and efficiency. Its strong R&D capabilities and global partnerships with OEMs position the company as a major player in the automotive predictive maintenance sensor market.
   
• Continental develops innovative sensors that support predictive maintenance and vehicle safety. Its advanced temperature, pressure, and motion sensors enable real-time monitoring and early fault detection. With a focus on connected mobility and smart diagnostics, Continental enhances vehicle reliability and reduces maintenance costs.
   
• Infineon Technologies is a key semiconductor provider offering advanced automotive sensors for predictive maintenance. Its magnetic, pressure, and current sensors enable real-time system monitoring and diagnostics. Leveraging expertise in power electronics and system integration, Infineon enhances vehicle efficiency and safety.
   
• TE Connectivity delivers durable and high-performance sensing solutions for predictive maintenance in automotive systems. Its temperature, pressure, and position sensors ensure optimal vehicle operation and longevity. Combining robust sensor designs with advanced connectivity, TE enables early fault detection and proactive maintenance.
   
• Valeo designs intelligent sensor systems that enhance predictive maintenance and vehicle performance. Its sensors monitor temperature, pressure, and vibration to detect potential issues before failure. Supporting both electric and autonomous vehicles, Valeo’s innovations improve safety, efficiency, and sustainability.
   
• STMicroelectronics offers a broad range of automotive-grade MEMS sensors for predictive maintenance. Its precision temperature, pressure, and motion sensors enable real-time vehicle diagnostics and system optimization. By supporting data-driven maintenance and safety features, ST helps reduce downtime and extend vehicle life.
   
• Hella provides advanced sensor solutions that enable predictive maintenance and enhance vehicle safety. Its portfolio includes temperature, pressure, and position sensors designed for combustion and electric vehicles. Through intelligent data integration and real-time diagnostics, Hella supports early fault detection and operational efficiency.
   

Automotive Predictive Maintenance Sensor Market Companies

Major players operating in the automotive predictive maintenance sensor industry are:
 

• Continental
• Hella
• Infineon Technologies
• Murata
• Robert Bosch
• Sensata Technologies
• STMicroelectronics
• TE Connectivity
• Valeo
   
• The automotive predictive maintenance sensor industry is characterized by a blend of global technology leaders and specialized innovators, resulting in a highly competitive yet moderately consolidated landscape. Key players such as Robert Bosch, Continental, Infineon Technologies AG, Sensata Technologies, TE Connectivity, Valeo, STMicroelectronics, Murata, and Hella collectively account for a substantial share of the market, driven by strong technological capabilities and deep integration with major automotive OEMs.
   
• These companies maintain their dominance through continuous investment in sensor innovation, AI-based analytics, IoT connectivity, and edge computing technologies that enable real-time diagnostics and data-driven maintenance. Their strategies emphasize the development of smart, durable, and high-performance sensors for electric, autonomous, and connected vehicles, addressing the growing demand for reliability, safety, and operational efficiency.
   
• To reinforce their market positions, leading firms are pursuing multi-dimensional strategies including R&D collaborations, strategic partnerships with automakers, expansion of semiconductor manufacturing, and integration of predictive analytics software into sensor systems. These efforts are designed to enhance fleet management, optimize vehicle health monitoring, and reduce maintenance costs while meeting stringent regulatory and safety standards.
   
• Alongside these global giants, several emerging regional players and niche sensor manufacturers are contributing to market expansion by offering customized condition-monitoring solutions and cost-efficient sensor modules tailored to specific vehicle segments. Their growing presence across North America, Europe, and Asia-Pacific underscores the accelerating adoption of predictive maintenance technologies in the transition toward connected, sustainable, and intelligent mobility ecosystems.
   

Automotive Predictive Maintenance Sensor Industry News

• In October 2025, Robert Bosch partnered with NIRA Dynamics to integrate road surface condition data from tire sensors into Bosch’s connected vehicle platform, enabling advanced predictive safety and maintenance insights through vehicle-surface interaction.
   
• In July 2025, STMicroelectronics announced plans to acquire NXP Semiconductor’s MEMS sensors business for up to $950 million, aiming to strengthen its automotive predictive maintenance sensor portfolio focused on vehicle dynamics, TPMS, and engine monitoring.
   
• In April 2025, Infineon Technologies announced the acquisition of Marvell Technology’s Automotive Ethernet business for $2.5 billion, strengthening its sensor-network capabilities and advancing real-time diagnostics and predictive maintenance solutions in software-defined vehicles.
   
• In September 2024, TE Connectivity completed the acquisition of Brazil-based Sense Eletrônica Ltda, expanding its automotive sensor portfolio with enhanced position and photoelectric sensors, bolstering its connected vehicle and predictive maintenance offerings.
   
• In February 2024, Continental highlighted the integration of tire sensors with driver-assistance and chassis control systems, enabling real-time monitoring of tire pressure, temperature, and tread depth to support predictive maintenance and enhance fleet safety.
   

The automotive predictive maintenance sensor market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue ($ Mn) and volume (units) from 2021 to 2034, for the following segments:

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Market, By Sensor

• Vibration sensor
• Temperature sensor
• Pressure sensor
• Humidity sensor
• Acoustic sensor
• Others

Market, By Application

• Engine health monitoring
• Transmission & gearbox monitoring
• Battery & electrical system monitoring
• Tire & wheel monitoring
• Cooling system monitoring
• Others

Market, By Vehicle

• Passenger cars
  • Hatchback
  • Sedan
  • SUV 
• Commercial sales channels
  • Light commercial sales channels (LCV)
  • Medium commercial sales channels (MCV)
  • Heavy commercial sales channels (HCV)       

Market, By Sales channel

• OEMs
• Aftermarket               

The above information is provided for the following regions and countries:

• North America
  • US
  • Canada
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Nordics
  • Russia
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • Indonesia
  • Philippines
  • Thailand
  • South Korea
  • Singapore
• Latin America
  • Brazil
  • Mexico
  • Argentina
• Middle East and Africa
  • Saudi Arabia
  • South Africa
  • UAE