Technology innovation, bringing more hope for the future. With the popularity of the concept of universal Internet, as one of the quite compelling car interconnection has also been a lot of industry discussions and study. Interconnected vehicles can not be separated from the sensor's auxiliary function, regardless of what level of automatic driving or look forward Sensor to the future of unmanned, sensors have played a first-class important role. Some people compared the car is a car as a collection of various types of data in the mobile center on different roads to achieve unimpeded 'flight.'

  Mentor Graphics, a leading provider of electronic design automation (EDA) software for Mentor Graphics, acquired by Siemens as part of Siemens PLM Software, a division of Siemens, has become the world's leading product design, simulation, validation, testing and manufacturing Industrial software provider. Mentor has introduced a complete automated driving solution DRS360 platform. The platform uses breakthrough technology to capture, fuse and utilize raw data in real time with a variety of sensing tools (including radar, LIDAR, images, and other sensors). DRS360 platform not only greatly improved the delay, but also significantly improve the accuracy of the sensor and the overall system efficiency, which can meet the requirements of SAE 5 automatic driving vehicles. As a leader in the autopilot platform, the DRS360 transfers unselected information directly from all system sensors to a central processing unit, where the raw data will be streamlined at different levels. By working with industry-leading sensor suppliers, the platform Suction Control Valve is able to use innovative 'raw data sensors', thereby reducing the power, cost and size of the processing of microcontrollers and sensor nodes. Dealing with pre-processing microcontrollers at all system sensor nodes can bring a number of benefits, including improved real-time performance, significantly reducing system cost and complexity, and access to all captured sensor data to create high ambient and driving conditions around the vehicle Resolution model. The architecture also utilizes centralized and unselected sensor data to achieve redundancy and dynamic resolution of the environment, ensuring greater accuracy and reliability. The solution has optimized signal processing software, advanced algorithms, and neural networks that are optimized for calculation and can be used for machine learning, all of which can be run on a seamless integrated automotive platform.

   With the decline in the cost of sensors and other equipment, industrial enterprises in the field of investment there is a big turning point, it found that industrial users for advanced automation, mobile application technology Fuel Rail Pressure Sensor and data analysis capabilities more and more attention. There is a better understanding of the value and effectiveness of the data.