全球汽車用地理空間分析市場 - 預測與趨勢 (2015 - 2020年)
Global Automotive Geospatial Analytics Market - Forecasts and Trends (2016-2021)
|出版商||Mordor Intelligence LLP||商品編碼||356557|
|全球汽車用地理空間分析市場 - 預測與趨勢 (2015 - 2020年) Global Automotive Geospatial Analytics Market - Forecasts and Trends (2016-2021)|
|出版日期: 2016年04月01日||內容資訊: 英文||
Organizations are turning to new data types and new form of analysis to remain competitive. Geospatial data, also referred to as location data or spatial data, enables to add the context of time and location to traditional data, so as to analyse the changes over time and exactly where those changes are taking place. The availability of real-time location data from vehicles opens up endless possibilities for creating value, provided that there is adequate infrastructure to collect and keep up with all that data. Due to the increasing capabilities of mobile devices, geospatial computing in automotive is a fast-growing trend. The portable nature of these devices, as well as the presence of useful sensors, such as Global Navigation Satellite System (GNSS) receivers make them useful for capturing and processing geospatial information in the field.
Connected cars help in generating a huge database from a vast array of sources. Cars would interact with other vehicles and other smart devices, exchanging real-time data and alerting drivers to potential collisions, traffic updates and alerts. The connected cars have telematics, mechatronics, and artificial intelligence to interact and connect with the environment to offer more comfort; safety and security; entertainment; and connected experience. They are equipped with WLAN hotspot, social media applications, internet facilities, and entertainment devices. The growing ability of the cloud to store and process huge amount of data would help to drive and facilitate the concept of deriving automotive geospatial data, significantly in the future.
Around 245-255 million connected cars are expected to be on the road, globally by 2020. The market for connected cars would help to drive the geospatial analytics market proportionately and significantly. Organizations can use geospatial data to fuel analytics in the real world in a number of ways. One of the most common use is the dynamic insurance pricing, where an extensive catalogue of geospatial data is maintained, and geospatial encoding engines are run through to maintain high-performance databases where various historical and real time data are coupled together. Asset-based Intelligence are adopted by the transportation companies which operates in a large networks of assets and must constantly seek to maximize the use of those assets. The mobile asset tracking systems provide transportation companies with geo-spatial information which gives a tremendous source of real time information which are harnessed to optimize networks.
The automotive geospatial analytics market is expected to grow at a CAGR of 23% by the end of the forecast period. Pitney Bowes, IBM, Space-Time are some of the leading names in providing solutions based out geospatial data.