According to Market Research Future (MRFR)’s latest report, the global Automotive Data Logger Market is expected to thrive at 7.2% CAGR during the forecast period 2017 to 2023. The valuation of the market is likely to surpass USD 4 Bn by the end of 2023. The growth trajectory of the market is guided by technological innovations and developments in the automotive industry for monitoring and analyzing real-time vehicle data. Additionally, the drive towards the production of efficient and smart vehicles has catalyzed the growth of the market.
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The developed regions have witnessed an inclination towards the adoption of electric cars. The developing regions are following the same trend. This, in turn, is forecasted to augment the global Automotive Data Logger Market over the next couple of years. Furthermore, industry leaders have shifted their focus towards the deployment of electronic architectures in modern vehicles for optimum efficiency. It is likely to favour the proliferation of the market through the projection period. Nevertheless, the high cost of data acquisition systems and lack of skilled personnel remain an impediment to the market expansion.
Top Companies Analysed in Report are:
Some of the key players operating in the market are Robert Bosch GmbH (Germany), Continental Automotive GmbH (Germany), Delphi Technologies (UK), Vector Informatik GmbH (Germany), Racelogic (UK), National Instruments (US), TTTech Computertechnik AG (Austria), Harman International (US), Xilinx (US), Intrepid Control Systems, Inc. (US), HEM Data Corporation (US), Danlaw Technologies India Limited (India), Dewesoft d.o.o. (Slovenia), MEN Micro Inc. (US), MadgeTech, Inc (US), Influx Technology (UK), NSM Solutions (India), myCarma (Canada), Ipetronik GmbH & Co. KG. (Germany), and Transtron Inc. (Japan).
Global Market for Automotive Data Logger – Segmental Analysis:
This MRFR’s report offers a comprehensive segmental analysis of the market based on application, channels, and connection type. By application, the market has been segmented into pre-sales and post-sales. The post-sales segment has been further sub-segmented into ADAS & safety, automotive insurance, fleet management, and OBD.
By channels, the market is segmented into CAN & CAN FD, ethernet, FlexRay, and LIN. The ethernet segment is projected to expand at a relatively higher CAGR in the upcoming years owing to its rapid data transfer speed. The growing penetration of autonomous vehicles is another factor that is likely to favor the growth of the segment through the review period.
By connection type, the market has been segmented into Bluetooth / Wi-Fi, SD card, and USB. Among these, the Bluetooth / Wi-Fi segment is currently leading the market. Meanwhile, the SD card segment is expected to witness a steep rise in the growth of the market as it is inexpensive, convenient, and avoids data loss.
The global automotive data logger market, by region, has been segmented into Americas, Europe, Asia Pacific, and the Middle East & Africa. Americas currently accounts for a dominant share of the global market. It is expected to retain its dominance towards the end of the forecast period. The factors such as technological innovations and its early adoption are expected fuel demand for automotive data loggers in the region. The rapid inclination witnessed towards the adoption of electric cars is likely to work in favor of the regional market. Furthermore, the presence of key players in the significant country-level markets is prognosticated to boost the expansion of the market further.
Europe is a highly lucrative market and is estimated to emerge as the fastest growing region by the end of 2023. The region has adopted electronic architectures for automobiles. Also, it has witnessed a rise in the demand for electric vehicles which is likely to exhibit a similar trend in the foreseeable future. These factors are projected to jointly contribute towards the proliferation of the automotive data logger market over the assessment period.
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Table Of Contents
1 Executive Summary
2 Market Introduction
2.2 Scope Of The Study
2.3 Market Structure
2.4 Key Takeaways
2.5 Macro Factor Indicators Analysis
2.5.1 GDP (USD Million)
2.5.2 GNI Per Capita, Atlas Method (USD)
2.5.3 GDP Per Capita PPP (USD)
2.5.4 Macro Indicators Influencing The Automotive Data Logger Market For Top 5 Countries
2.5.4. 5 U.K
2.6 Market Insights
2.7 List Of Assumptions
3 Research Methodology
3.1 Research Application
3.2 Primary Research
3.3 Secondary Research
3.4 Market Size Estimation
3.5 Forecast Model
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