Predictive Automobile Technology Market size is expected to grow significantly over the forecast period due to surging demand for improving vehicle effectiveness, growing necessity of on-time vehicle maintenance, and advancements in technologies & machines used. Additionally, predictive automobile technology assists in reducing operational costs as predictive maintenance is more sensible economically and logically compared to unplanned maintenance. The adoption of Internet of Things (IoT) and machine learning data techniques is largely contributing to innovation in the predictive automobile technology industry. For instance, IoT can pinpoint when vehicle maintenance is required very accurately and precisely with the help of sensors. The demand for predictive vehicle maintenance is growing as it avoids unexpected breakdowns with the help of component failure prediction in advance.
Predictive automobile technology helps in collision avoidance by giving timely inputs regarding vehicle proximity to other vehicles on the road. The demand for predictive maintenance is augmented as it assists in improving fleet productivity by avoiding vehicle downtime, helps in extending the lifespan of a vehicle, and ensures regulatory compliance. It alerts the owner regarding vehicle downtime and even provides usage patterns of the vehicle components. Additionally, it helps in maintaining connected car cybersecurity. The rapid penetration of Artificial Intelligence (AI) & machine learning technologies in the automotive industry is expected to enhance the predictive capabilities of these systems to provide more accurate and real-time vehicle-related data to the drivers.
North America is expected to dominate the predictive automobile technology market due to initiatives undertaken by the government and automotive industry players. For instance, the U.S. Department of Transportation has undertaken the ‘Smart City Challenge’ inviting organizations to work on smart mobility challenges in the country. The automotive industry is investing significantly in automotive technology in the U.S. For instance, according to the American Automotive Policy Council Report, in 2017, the U.S. automakers & suppliers spent more than USD 21 billion on the automotive R&D sector.
APAC predictive automobile technology market is expected to show rapid growth over the forecast period due to increasing investments by the companies to adopt advanced technologies such as IoT and AI. For instance, in September 2018, TPL Trakker launched in-app for vehicle analytics that provides data regarding fleet safety & productivity in Pakistan. In China, multiple industrial groups and the Field Device Tool (FDT) standards group are helping manufacturers to adopt new technologies to comply with the National standard FDT 2.0 for efficient system integration and interconnection. Additionally, surging government initiatives in fleet management and the growing e-commerce industry optimize the market growth in China. For instance, as the e-commerce industry is growing, the adoption of predictive automobile technology will grow, improving the supply chain and logistics efficiency by collecting & analyzing data accurately.
The companies operating in the predictive automobile technology market are focusing on new product developments and making advancements in existing products to gain market attention. For instance, in July 2018, SAP launched an application based on SAP HANA Cloud Platform used for data analytics of connected vehicles. In August 2017, Trimble Transportation introduced predictive maintenance analytics that helped it reduce fleet repair costs and increase vehicle uptime. The prominent players operating in the predictive automobile technology market are General Electric Company, Siemens AG, Microsoft Corporation, International Business Machines (IBM) Corporation, Thales Group, Robert Bosch GmbH, Honeywell International Inc., SAP SE, HARMAN International, and BMW Group.
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