The major factors lashing the development of sensor fusion market includes increasing adoption of sensor fusion in consumer electronics such as smartphones, and wearable devices, rising home automation applications, and growing advanced driver assistance system in automotive industry. However, the large initial rate of disposition and the lack of standards in memory devices and automotive sensor fusion systems are expected to hinder the growth of sensor fusion market during the forecast period. The need for estimable driving automation, and increasing demand for internet of things, is expected to create plentiful opportunities for automotive manufacturers across the world. Further, the use of sensors in the design of advanced airplanes and high-tech drones is expected to expand the growth opportunities for automotive sensor fusion market during the forecast period. People are relying on sensors for safety, entertainment, food production, transportation, and many more.
Automotive companies, consumer electronics companies, and upcoming tech start-ups are eager to participate in the autonomous future. Roadstar.AI provides an autonomous driving solution based on the power of multi-sensor fusion. The company focus on providing efficient autonomous driving solutions to address advanced transportation and logistics problems using unique and robust multi-sensor fusion framework.
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Major Key Players
NXP Semiconductor N.V. (Netherlands),
Kionix, Inc. (Japan),
Robert Bosch GmbH (Germany),
Cummins, Inc. (U.S.),
Renesas electronics Corporation (Japan),
MEMSIC, Inc. (U.S.),
Analog device, Inc. (U.S.),
Microchip technologies Inc. (U.S.),
Globally the Sensor Fusion Market is expected to grow at the rate of around ~19% from 2016 to 2022.
January 2018, Ainstein Introduces 79 GHz Automotive Short Range Radar T-79. Ainstein’s T-79 Short Range Radar is built on RF-CMOS IC technology, allowing for ultra-low power consumption and unit cost. The highly integrated hardware design paired with Ainstein’s proprietary advanced radar signal processing algorithms makes it capable of high resolution 360° detection when multiple units are configured on the vehicle. This allows for semi-autonomous or fully autonomous driving.
January 2018, Sensor Fusion Is the Next Step: AEye and Tetravue. Start-up AEye is planning to integrate both lidar and a traditional camera onto its sensor, adding enough intelligence that it can optimize the laser pattern it emits based on feedback from both the lidar and the camera. It expects the result to be as much as five times more efficient than a typical MEMS-based lidar solution, and provide a full RGB+depth image. It’s calling its new approach iDAR, and expects it to be 10 to 20 times more effective than traditional lidar when identifying objects.
January 2018. Roadstar.ai Introduces Precision into the Autonomous Vehicle Market. The company’s’ multi-sensor fusion adopts the use of sensors like millimetre wave radars, GPS, and Lidars, to perform high precision measurement and perception. These tools create an algorithm to produce 8-dimensional data that is spatiotemporally-synced on a high accuracy level. Their technology offers safe and powerful driverless solutions for commercial use and consumer vehicles. Currently, the Roadstar.ai team is focused on “on providing autonomous limousine services, and on the other hand, providing technical consultation and designing solutions to meet different scenarios and requirements in the automotive market.
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North America is dominating the global sensor fusion market with the largest market share in the region due to presence of automotive major players and growing technological advancement in the region and therefore is expected to have high market growth by the end of forecast period. Sensor fusion market in Asia Pacific region is expected to grow at high rate between the forecast periods due to high demand of sensor fusion from consumer electronics sector arising from emerging countries in this region including India, China, Singapore, and Malaysia among others.
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