The Automotive Iot Market Is Seeing A Rise In The Adoption Of Predictive Diagnostic Solutions To Stay Up-To-Date With Vehicle Function Metrics As Per The Business Research Company's Automotive Iot Global Market Report 2022


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LONDON, May 19, 2022 (GLOBE NEWSWIRE) -- According to The Business Research Company's research report on the automotive IoT market , automotive predictive diagnostics solutions are a key trend gaining popularity in the automotive IoT market. Automotive companies are partnering with technology players for the integration of predictive diagnostics solutions into their existing models, which allows the upkeep frequency to be as low as possible to prevent unplanned reactive maintenance without incurring costs related to doing an excessive amount of preventive maintenance. The predictive maintenance systems within the vehicle continuously monitor, collect, record, transfer, and evaluate data from in-vehicle sensors to keep track of vehicle functional metrics. For instance, in February 2022, Ashok Leyland, an India-based automotive manufacturer, partnered with Syncron, a Sweden-based after-sales service provider, to integrate predictive vehicle maintenance solutions into Ashok Leyland Condition Monitoring Systems (CMS).

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The global automotive IoT market s hare is expected to grow from $115.06 billion in 2021 to $125.59 billion in 2022 at a compound annual growth rate (CAGR) of 9.2%. The global automotive IoT market growth is expected to lead to $219.61 billion in 2026 at a CAGR of 15.0%.

In February 2021, Harman International, an automotive infotainment company, acquired Savari for an undisclosed amount. With this acquisition, Harman wants to expand their company's portfolio in automotive telematics and advanced driving assistance systems (ADAS) capabilities and enhance 5G Edge, multi-access edge computing (MEC), and smart infrastructure solutions. Savari is an automotive infotainment company with V2X sensor solutions and also includes Vehicle-to-Phone for pedestrians and bicyclists, Vehicle-to-Infrastructure, Vehicle-to-Vehicle, and Infrastructure-to-Phone.

Major players in the automotive IoT market are Texas Instruments, NXP Semiconductors, Intel Corporation, TomTom, Cisco Systems, Microsoft Corporation, IBM Corporation, Google, AT & T, Apple, and Robert Bosch.

The global automotive IoT market analysis report is segmented by offering into hardware, software, services; by connectivity into embedded, tethered, integrated; by application into infotainment, fleet management, predictive maintenance, vehicle security, automatic driver assistance system, others; by end-user into original equipment manufacturers, aftermarket.

North America was the largest region in the automotive IoT market in 2021. Asia-Pacific is expected to be the fastest-growing region in the global automotive IoT market during the forecast period. The regions covered in the global automotive IoT market are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa.

Automotive IoT Global Market Report 2022 – Market Size, Trends, And Global Forecast 2022-2026 is one of a series of new reports from The Business Research Company that provide automotive IoT market overviews, automotive IoT market analyze and forecast market size and growth for the whole market, automotive IoT market segments and geographies, automotive IoT market trends, automotive IoT market drivers, automotive IoT market restraints, automotive IoT market leading competitors' revenues, profiles and market shares in over 1,000 industry reports, covering over 2,500 market segments and 60 geographies.

The report also gives in-depth analysis of the impact of COVID-19 on the market. The reports draw on 150,000 datasets, extensive secondary research, and exclusive insights from interviews with industry leaders. A highly experienced and expert team of analysts and modelers provides market analysis and forecasts. The reports identify top countries and segments for opportunities and strategies based on market trends and leading competitors' approaches.

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