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市場調查報告書
商品編碼
2038313

智慧輪胎軟體市場機會、成長要素、產業趨勢分析及2026-2035年預測

Smart Tire Software Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2026 - 2035
出版日期: | 出版商: Global Market Insights Inc. | 英文 240 Pages | 商品交期: 2-3個工作天內

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簡介目錄

全球智慧輪胎軟體市場預計到 2025 年將達到 192 億美元，並以 10.4% 的複合年成長率成長，到 2035 年達到 512 億美元。

智慧輪胎軟體市場-IMG1

聯網汽車的快速普及正在加速市場成長。這是因為現代汽車擴大整合感測器和遠端資訊處理系統，這些系統能夠持續產生輪胎性能數據。這項變更使得即時監控和軟體分析成為可能，從而提升了車輛的效率和安全性。汽車製造商正將互聯功能作為標準配置，擴大了智慧輪胎軟體在乘用車和商用車領域的應用範圍。這些平台支援預測性維護和營運最佳化，使用戶能夠做出數據驅動的決策。隨著數位轉型在整個汽車生態系統中的推進，智慧輪胎解決方案的整合變得至關重要。對數據分析日益成長的依賴，以及對提升車輛性能和安全性的需求，正在增強全球對智慧輪胎軟體解決方案的長期需求。

市場範圍
開始年份 2025
預測期 2026-2035
上市時的市場規模 192億美元
預測金額 512億美元
複合年成長率 10.4%

車隊營運商和物流公司越來越注重透過減少停機時間、降低油耗和減少維護成本來提高營運效率。智慧輪胎軟體透過提供即時分析、性能最佳化和預測性維護功能，助力實現這些目標。利用數位化平台進行輪胎監控已成為車隊管理策略的關鍵要素，幫助營運商提高交付可靠性並減少意外中斷。隨著運輸網路日益複雜，數據驅動的決策在確保效率和成本控制方面發揮越來越重要的作用。

預計到2025年，胎壓監測系統（TPMS）市佔率將達到30%，並在2026年至2035年間以10%的複合年成長率成長。軟體持續監測輪胎氣壓水平，並在出現低胎壓等潛在問題時發出警報。這有助於保障車輛安全，確保符合法規標準，並提高燃油效率。此外，TPMS在更廣泛的智慧輪胎生態系統中變得越來越重要，因為它為更高級的分析和聯網汽車功能提供了基礎。

預計到2025年，雲端解決方案將佔據64.8%的市場佔有率，並在2035年之前以10.6%的複合年成長率成長。這些平台利用遠端基礎設施提供可擴展且靈活的軟體功能，從而實現跨多個地點的即時數據存取。對於管理大規模車隊的企業而言，採用雲端解決方案極具吸引力，因為它能夠降低初始投資成本並簡化系統更新。與遠端資訊處理系統的整合進一步提升了營運的可視性和效率，從而促進了雲端解決方案的廣泛應用。

美國智慧輪胎軟體市場預計到2025年將達到51億美元，並在2026年至2035年間以10.9%的複合年成長率成長。先進輪胎監測系統的日益普及主要受以下因素驅動：提高燃油效率、減少車輛停機時間以及滿足嚴格的安全要求。物流和電子商務活動的擴張也推動了長途運輸網路對預測性維護技術的需求。此外，強調安全標準和輪胎監測要求的法律規範也進一步加速了智慧輪胎軟體解決方案的大規模部署。

目錄

第1章：調查方法

第2章執行摘要

第3章業界考察

  • 生態系分析
    • 供應商情況
    • 利潤率
    • 成本結構
    • 每個階段增加的價值
    • 影響價值鏈的因素
    • 中斷
  • 影響產業的因素
    • 促進因素
      • 聯網汽車的全球普及
      • 對車輛效率的需求日益成長
      • 全球更嚴格的汽車安全法規
      • 預測性維護的擴展
    • 產業潛在風險與挑戰
      • 高階整合和實施複雜性
      • 資料隱私和網路安全問題
    • 市場機遇
      • 利用人工智慧拓展輪胎分析領域
      • SaaS經營模式的成長
      • 新興市場採用率的擴大
      • 與自動駕駛汽車生態系統的整合
  • 成長潛力分析
  • 科技與創新趨勢
    • 當前技術趨勢
    • 新興技術
  • 監理情勢
    • 北美洲
      • 美國國家公路交通安全管理局（NHTSA）
      • 加拿大運輸部
    • 歐洲
      • 歐盟委員會
      • 歐洲汽車製造商協會 (ACEA)
    • 亞太地區
      • 印度公路運輸與公路部
      • 日本國土交通省
    • 拉丁美洲
      • 巴西國家交通運輸局（SENATRAN）
      • 阿根廷運輸部
    • 中東和非洲
      • 阿拉伯聯合大公國運輸部
      • 沙烏地阿拉伯標準、計量和品質組織（SASO）
  • 波特五力分析
  • PESTEL 分析
  • 專利分析（基於初步研究）
  • 人工智慧和生成式人工智慧對市場的影響
    • 利用人工智慧改造現有經營模式
    • 按細分市場分類的生成式人工智慧用例和部署藍圖
    • 風險、限制和監管考量
  • 永續性和環境方面
    • 永續計劃
    • 減少廢棄物策略
    • 生產中的能源效率
    • 具有環保意識的舉措
    • 碳足跡考量
  • 預測假設和情境分析（基於初步研究）
    • 基本案例－驅動複合年成長率的關鍵宏觀經濟與產業變量
    • 樂觀情境－宏觀經濟與產業的順風
    • 悲觀情景－宏觀經濟放緩或產業逆風

第4章 競爭情勢

  • 介紹
  • 企業市佔率分析
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東和非洲（MEA）
  • 主要市場公司的競爭分析
  • 競爭定位矩陣
  • 主要進展
    • 併購
    • 夥伴關係與合作
    • 新產品發布
    • 業務拓展計劃及資金籌措

第5章 市場估計與預測：依軟體分類，2022-2035年

  • 胎壓監測系統（TPMS）軟體
  • 輪胎性能分析與最佳化軟體
  • 預測性維護軟體
  • 車隊輪胎管理軟體
  • 負載容量和重量分佈監測軟體
  • 胎面深度監測軟體
  • 溫度監控軟體
  • 即時輪胎狀況儀錶板軟體

第6章 市場估算與預測：依部署類型分類，2022-2035年

  • 基於雲端的
  • 現場
  • 混合

第7章 市場估價與預測：依車輛類型分類，2022-2035年

  • 搭乘用車
    • 掀背車
    • SUV
    • 轎車
  • 商用車輛
    • LCV
    • MCV
    • 大型商用車輛

第8章 市場估算與預測：依最終用途分類，2022-2035年

  • OEM
    • 汽車製造商
    • 內建/工廠出貨時裝載的輪胎軟體系統
  • 售後市場
    • 車隊營運商
    • 輪胎零售商和服務中心
    • 私家車車主

第9章 市場估計與預測：依地區分類，2022-2035年

  • 北美洲
    • 美國
    • 加拿大
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 義大利
    • 西班牙
    • 北歐國家
    • 俄羅斯
    • 波蘭
    • 羅馬尼亞
  • 亞太地區
    • 中國
    • 印度
    • 日本
    • 韓國
    • ANZ
    • 越南
    • 印尼
    • 菲律賓
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 阿根廷
  • 中東和非洲（MEA）
    • 南非
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國

第10章：公司簡介

  • 世界公司
    • Bridgestone
    • Continental
    • Denso
    • Goodyear Tire & Rubber Company
    • Michelin
    • Pirelli
    • Robert Bosch
    • Sensata Technologies
    • ZF Friedrichshafen
  • 當地公司
    • Alps Alpine
    • Hankook Tire & Technology
    • Huf Hulsbeck & Furst
    • NIRA Dynamics
    • Nokian Tyres
    • Pacific Industrial
    • STMicroelectronics
    • Sumitomo Rubber Industries
    • Yokohama Rubber Company
  • 新興企業
    • Dextera
    • Revvo Technologies
    • Tactile Mobility
    • Tyrata
簡介目錄
Product Code: 15805

The Global Smart Tire Software Market was valued at USD 19.2 billion in 2025 and is estimated to grow at a CAGR of 10.4% to reach USD 51.2 billion by 2035.

Smart Tire Software Market - IMG1

Rapid expansion in connected vehicle adoption is a factor accelerating market growth, as modern vehicles increasingly integrate sensors and telematics systems that continuously generate tire performance data. This shift is enabling real-time monitoring and software-driven insights that enhance vehicle efficiency and safety. Automotive manufacturers are embedding connectivity features as standard, which is widening the scope for smart tire software across both passenger and commercial vehicle segments. These platforms support predictive maintenance and operational optimization, allowing users to make data-informed decisions. As digital transformation continues across the automotive ecosystem, the integration of intelligent tire solutions is becoming essential. The growing reliance on data analytics, combined with the need for improved vehicle performance and safety, is reinforcing long-term demand for smart tire software solutions worldwide.

Market Scope
Start Year2025
Forecast Year2026-2035
Start Value$19.2 Billion
Forecast Value$51.2 Billion
CAGR10.4%

Fleet operators and logistics providers are increasingly prioritizing operational efficiency by minimizing downtime, lowering fuel consumption, and reducing maintenance costs. Smart tire software enables these goals by offering real-time analytics, performance optimization, and predictive maintenance capabilities. The use of digital platforms for tire monitoring has become a critical component of fleet management strategies, helping operators improve delivery reliability and reduce unexpected disruptions. As transportation networks become more complex, data-driven decision-making plays a larger role in ensuring efficiency and cost control.

The TPMS segment accounted for 30% share in 2025 and is projected to grow at a CAGR of 10% from 2026 to 2035. This software continuously tracks tire pressure levels and provides alerts related to potential issues such as underinflation. It supports vehicle safety, ensures compliance with regulatory standards, and enhances fuel efficiency. In addition, TPMS serves as a foundational layer for more advanced analytics and connected vehicle functionalities, strengthening its importance within the broader smart tire ecosystem.

The cloud-based segment held a 64.8% share in 2025 and is expected to grow at a CAGR of 10.6% through 2035. These platforms rely on remote infrastructure to deliver scalable and flexible software capabilities, enabling access to real-time data across multiple locations. Cloud deployment reduces upfront investment requirements and simplifies system updates, making it an attractive option for organizations managing large fleets. Integration with telematics systems further enhances operational visibility and efficiency, contributing to widespread adoption.

U.S. Smart Tire Software Market generated USD 5.1 billion in 2025 and is anticipated to grow at a CAGR of 10.9% between 2026 and 2035. Increasing adoption of advanced tire monitoring systems is being driven by the need to improve fuel efficiency, reduce vehicle downtime, and meet stringent safety requirements. The expansion of logistics and e-commerce activities is also fueling demand for predictive maintenance technologies across long-haul transportation networks. Regulatory frameworks emphasizing safety standards and tire monitoring requirements are further encouraging large-scale deployment of smart tire software solutions.

Key companies operating in the Global Smart Tire Software Market include Bridgestone, Continental, Denso, Goodyear Tire & Rubber Company, Michelin, NIRA Dynamics, Nokian Tyres, Pirelli, Robert Bosch, Sensata Technologies, Valeo, and ZF Friedrichshafen. Companies in the smart tire software market are enhancing their competitive position through continuous innovation, strategic collaborations, and digital ecosystem expansion. Industry players are investing in advanced analytics, artificial intelligence, and cloud-based platforms to deliver more accurate and actionable insights. Partnerships with automotive manufacturers and fleet operators are helping companies integrate their solutions more effectively into connected vehicle systems. Many firms are also focusing on expanding their global footprint and strengthening distribution networks to reach a wider customer base.

Table of Contents

Chapter 1 Methodology

  • 1.1 Research approach
  • 1.2 Quality Commitments
    • 1.2.1 GMI AI policy & data integrity commitment
      • 1.2.1.1 Source consistency protocol
  • 1.3 Research Trail & Confidence Scoring
    • 1.3.1 Research Trail Components
    • 1.3.2 Scoring Components
  • 1.4 Data Collection
    • 1.4.1 Partial list of primary sources
  • 1.5 Data mining sources
    • 1.5.1 Paid sources
      • 1.5.1.1 Sources, by region
  • 1.6 Base estimates and calculations
    • 1.6.1 Base year calculation
  • 1.7 Forecast model
    • 1.7.1 Quantified market impact analysis
      • 1.7.1.1 Mathematical impact of growth parameters on forecast
  • 1.8 Research transparency addendum
    • 1.8.1 Source attribution framework
    • 1.8.2 Quality assurance metrics
    • 1.8.3 Our commitment to trust

Chapter 2 Executive Summary

  • 2.1 Industry 360° synopsis
  • 2.2 Key market trends
    • 2.2.1 Regional
    • 2.2.2 Software
    • 2.2.3 Deployment mode
    • 2.2.4 Vehicle
    • 2.2.5 End use
  • 2.3 TAM analysis, 2026-2035
  • 2.4 CXO perspectives: Strategic imperatives

Chapter 3 Industry Insights

  • 3.1 Industry ecosystem analysis
    • 3.1.1 Supplier landscape
    • 3.1.2 Profit margin
    • 3.1.3 Cost structure
    • 3.1.4 Value addition at each stage
    • 3.1.5 Factor affecting the value chain
    • 3.1.6 Disruptions
  • 3.2 Industry impact forces
    • 3.2.1 Growth drivers
      • 3.2.1.1 Rising connected vehicle adoption globally
      • 3.2.1.2 Increasing demand for fleet efficiency
      • 3.2.1.3 Stringent vehicle safety regulations worldwide
      • 3.2.1.4 Growth in predictive maintenance adoption
    • 3.2.2 Industry pitfalls and challenges
      • 3.2.2.1 High integration and implementation complexity
      • 3.2.2.2 Data privacy and cybersecurity concerns
    • 3.2.3 Market opportunities
      • 3.2.3.1 Expansion of AI-driven tire analytics
      • 3.2.3.2 Growth in SaaS-based business models
      • 3.2.3.3 Increasing adoption in emerging markets
      • 3.2.3.4 Integration with autonomous vehicle ecosystems
  • 3.3 Growth potential analysis
  • 3.4 Technology and innovation landscape
    • 3.4.1 Current technological trends
    • 3.4.2 Emerging technologies
  • 3.5 Regulatory landscape
    • 3.5.1 North America
      • 3.5.1.1 National Highway Traffic Safety Administration (NHTSA) - USA
      • 3.5.1.2 Transport Canada
    • 3.5.2 Europe
      • 3.5.2.1 European Commission (EC)
      • 3.5.2.2 European Automobile Manufacturers' Association (ACEA)
    • 3.5.3 Asia Pacific
      • 3.5.3.1 Ministry of Road Transport and Highways (India)
      • 3.5.3.2 Ministry of Land, Infrastructure, Transport and Tourism (Japan)
    • 3.5.4 Latin America
      • 3.5.4.1 National Traffic Secretariat (SENATRAN, Brazil)
      • 3.5.4.2 Ministry of Transport (Argentina)
    • 3.5.5 Middle East & Africa
      • 3.5.5.1 Ministry of Transport (UAE)
      • 3.5.5.2 Saudi Standards, Metrology and Quality Organization (SASO)
  • 3.6 Porter's analysis
  • 3.7 PESTEL analysis
  • 3.8 Patent analysis (Driven by primary research)
  • 3.9 Impact of AI & Generative AI on the Market
    • 3.9.1 AI-driven disruption of existing business models
    • 3.9.2 Gen AI use cases & adoption roadmap by segment
    • 3.9.3 Risks, limitations & regulatory considerations
  • 3.10 Sustainability and environmental aspects
    • 3.10.1 Sustainable practices
    • 3.10.2 Waste reduction strategies
    • 3.10.3 Energy efficiency in production
    • 3.10.4 Eco-friendly initiatives
    • 3.10.5 Carbon footprint considerations
  • 3.11 Forecast assumptions & scenario analysis (Driven by primary research)
    • 3.11.1 Base Case - key macro & industry variables driving CAGR
    • 3.11.2 Optimistic Scenarios - Favorable Macro and Industry Tailwinds
    • 3.11.3 Pessimistic Scenario - Macroeconomic slowdown or industry headwinds

Chapter 4 Competitive Landscape, 2025

  • 4.1 Introduction
  • 4.2 Company market share analysis
    • 4.2.1 North America
    • 4.2.2 Europe
    • 4.2.3 Asia Pacific
    • 4.2.4 LATAM
    • 4.2.5 MEA
  • 4.3 Competitive analysis of major market players
  • 4.4 Competitive positioning matrix
  • 4.5 Key developments
    • 4.5.1 Mergers & acquisitions
    • 4.5.2 Partnerships & collaborations
    • 4.5.3 New product launches
    • 4.5.4 Expansion plans and funding

Chapter 5 Market Estimates & Forecast, By Software, 2022 - 2035 ($Mn)

  • 5.1 Key trends
  • 5.2 TPMS (Tire Pressure Monitoring) software
  • 5.3 Tire performance analytics & optimization software
  • 5.4 Predictive maintenance software
  • 5.5 Fleet tire management software
  • 5.6 Load & weight distribution monitoring software
  • 5.7 Tread depth monitoring software
  • 5.8 Temperature monitoring software
  • 5.9 Real-time tire health dashboard software

Chapter 6 Market Estimates & Forecast, By Deployment mode, 2022 - 2035 ($Mn)

  • 6.1 Key trends
  • 6.2 Cloud-based
  • 6.3 On premises
  • 6.4 Hybrid

Chapter 7 Market Estimates & Forecast, By Vehicle, 2022 - 2035 ($Mn)

  • 7.1 Key trends
  • 7.2 Passenger cars
    • 7.2.1 Hatchback
    • 7.2.2 SUV
    • 7.2.3 Sedan
  • 7.3 Commercial vehicles
    • 7.3.1 LCV
    • 7.3.2 MCV
    • 7.3.3 HCV

Chapter 8 Market Estimates & Forecast, By End use, 2022 - 2035 ($Mn)

  • 8.1 Key trends
  • 8.2 OEM
    • 8.2.1 Automotive manufacturers
    • 8.2.2 Embedded / factory-installed tire software systems
  • 8.3 Aftermarket
    • 8.3.1 Fleet operators
    • 8.3.2 Tire retailers & service centers
    • 8.3.3 Individual vehicle owners

Chapter 9 Market Estimates & Forecast, By Region, 2022 - 2035 ($Mn)

  • 9.1 Key trends
  • 9.2 North America
    • 9.2.1 U.S.
    • 9.2.2 Canada
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 France
    • 9.3.4 Italy
    • 9.3.5 Spain
    • 9.3.6 Nordics
    • 9.3.7 Russia
    • 9.3.8 Poland
    • 9.3.9 Romania
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 India
    • 9.4.3 Japan
    • 9.4.4 South Korea
    • 9.4.5 ANZ
    • 9.4.6 Vietnam
    • 9.4.7 Indonesia
    • 9.4.8 Philippines
  • 9.5 Latin America
    • 9.5.1 Brazil
    • 9.5.2 Mexico
    • 9.5.3 Argentina
  • 9.6 MEA
    • 9.6.1 South Africa
    • 9.6.2 Saudi Arabia
    • 9.6.3 UAE

Chapter 10 Company Profiles

  • 10.1 Global players
    • 10.1.1 Bridgestone
    • 10.1.2 Continental
    • 10.1.3 Denso
    • 10.1.4 Goodyear Tire & Rubber Company
    • 10.1.5 Michelin
    • 10.1.6 Pirelli
    • 10.1.7 Robert Bosch
    • 10.1.8 Sensata Technologies
    • 10.1.9 ZF Friedrichshafen
  • 10.2 Regional players
    • 10.2.1 Alps Alpine
    • 10.2.2 Hankook Tire & Technology
    • 10.2.3 Huf Hulsbeck & Furst
    • 10.2.4 NIRA Dynamics
    • 10.2.5 Nokian Tyres
    • 10.2.6 Pacific Industrial
    • 10.2.7 STMicroelectronics
    • 10.2.8 Sumitomo Rubber Industries
    • 10.2.9 Yokohama Rubber Company
  • 10.3 Emerging players
    • 10.3.1 Dextera
    • 10.3.2 Revvo Technologies
    • 10.3.3 Tactile Mobility
    • 10.3.4 Tyrata