Automotive Smart tires market - share, Overview, Dynamics, Key Players, size ,

Smart tires made for the automotive industry make the use of sensors for gauging the tire pressure, driving behavior, and other vehicle dynamics.

Market overview 

Smart tires made for the automotive industry make the use of sensors for gauging the tire pressure, driving behavior, and other vehicle dynamics. The changing tire industry and evolution in connected vehicles can pave forth the way for smart tires. The global automotive smart tire market report by Market Research Future (MRFR) comprises drivers and challenges for the period of 2019 to 2025 (forecast period) which can shape the future of the automotive industry. The COVID-19 pandemic and its impact on the production and value chain are included in the report.

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Market Scope

The global automotive smart tire market is estimated to reach USD 2254.49 million by 2025 registering a CAGR of 16.10% during the forecast period. This is influenced by the focus of automotive manufacturers to leverage on data and analytics to improve their tires. Metrics such as load detection, tread wear & depth, pressure & temperature, and road conditions can be used in gleaning useful insights and start new trends in tire development.

Investments in internet of things (IoT) sensors for extending tire shelf life and fuel efficiency can spur the global automotive smart tire industry. The need to protect fleet drivers and improve logistical inconsistencies can drive the smart tire demand over the forecast period. 

Segmentation

The global automotive smart tire market is segmented on the basis of technology, vehicle type, sales channel. 

On the basis of sales channel, the market has been segmented into original equipment manufacturer (OEM) and aftermarket.

On the basis of technology, the market has been segmented into pneumatic tires and non-pneumatic tires. 

On the basis of vehicle type, the market has been segmented into battery electric vehicles, hybrid electric vehicles, passenger cars, commercial vehicles, and plug-in hybrid vehicle. 

Regional Analysis

Considerable sales of commercial vehicles (light commercial and heavy commercial) in the U.S. is expected to augment the growth of global smart tire market in North America during the forecast period. Rise of 5G and integration of wireless sensors in fleets can influence the regional automotive smart tire market over the forecast period. Investments by governments and self-driving technology providers can bode well for the market.

Geographically, the global automotive smart tire market has been segmented into four major regions namely North America, Europe, Asia Pacific (APAC), and Rest-of-the-World (RoW). Europe is estimated to account for a significant market share in the automotive smart tire market owing to relatively high adoption of sensor integrated tires and substantial investments by software giants to incorporate IoT platforms. Sales of connected and passenger vehicles and presence of ride-sharing platforms to improve security of passengers can bode well for the market.  

Stringent emission norms, government measures to reduce accidental rates, and significant automotive production are some of the drivers which are expected to propel the demand for smart tires in the Asia Pacific region. Lax regulations pertaining to safety and emissions can drive the regional market growth over the forecast period.

Competitive Outlook  

The Goodyear Tire & Rubber Co, Bridgestone Corporation, Continental AG, NEXEN TIRE Corporation, Michelin Group, Pirelli & C. S.p.A., and Sumitomo Rubber Industries, Ltd. are key players of the global automotive smart tire industry. Joint ventures and collaborations are prime strategies of players sustaining in the market.

Table Of Contents

  1. Executive Summary
  2. Scope Of The Report

2.1. Market Definition

2.2. Scope Of The Study

2.2.1. Definition

2.2.2. Research Objective

2.2.3. Assumptions

2.2.4. Limitations

2.3. Research Process

2.3.1. Primary Research

2.3.2. Secondary Research

2.4. Market Size Estimation

2.5. Forecast Model

 

Continued………

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