 said, let me introduce myself at first. I am Hideo Nitsuzuki. I was executive director and president of the DT Data MSC from 2015. Prior to current position, I was engaged in the creation of cutting-edge service in telecom business field. And very important role in worldwide business development. In current position, I have promoted full-scale entry into automotive field. And now I'm reading the expansion of business field in automotive, IoT, and product. This is our company's belief profile. We at DT Data MSC located at Shin-Yokohama in Japan. We have two subsidiaries. They are at DT Data MSC in China as a offshore site and cats as a development tool supplier. Our main business is to develop embedded software for the field of automotive, IoT, and product. As you can see, in the video of shareholders, MSC was 100% subsidiary of Amazon Preview as a mobile embedded software company. And in 2018, we joined in DT Data Group. After joining in DT Data Group, our business has expanded IoT and automotive field. From 2016, we have three shareholders, including Denso. Our sale revenue is shown on the right side on the bottom. Automotive takes the biggest volume of our revenue and this is the field we most consider to concentrate on at that moment. In automotive field, we were the wide range of business by using our knowledge and technical skills of IoT cloud embedded. Among these business, the area where we have most advantage is in vehicle devices such as Metacluster, in vehicle information and connectivity. Our achievements and engagements in vehicle device development are shown in this slide. For Metacluster, we have development display functionality such as HMI opportunity display. And for IoT system, communication, radio and DCU-DCM development using the skills of mobile device development are our achievements. Regarding productivity, we have implemented Android Auto, PowerPlay and Miracast. Our exosystem of productivity is smart device being and our demo system is now showcased at our booth today so please visit us when you have the time. Everyday, we are driving our activities with our engagement and space like this to contribute to automotive industry. From this slide, I would like to talk about the importance of making a new civilization in the political career. What is productivity to come? In past, the car had evolved as a standalone device but recently, the car has been changed to device which can be used inside the network according to the evolution of controlling the computers and mobile network. We have this type of car which has the capability to get the service from the network as a connected car. In the world of the connected car, it is able to collaborate with the IT package of OEMs and service providers. As a result, various data surrounding the car will fuse together and make it possible to realize not only the service of the drivers but more new variable services. In other words, how to collect data from car and how to use data for the services is very important for the connected car. There are three major points in the data cycle of the connected car. Firstly, sense. Various sense data generated from sensors in car for example, because status surrounding development status were driver's condition. Secondly, the changes to the generated data to information and the value of intelligence. Third is to take action according to the information with intelligence. Out of this point, I'd like to focus on information and intelligence. Key one of information are 3V, variety, volume, density. I'd like to describe the point of consideration of these 3V. Let's start from variety. We can collect various data from the car for car data. We can get the driving data, the condition of each car parts and the information around the car. And human data. We can get operations history at the view of drivers or passengers and biological data. We can also get the traffic information, map information and other cars information and society data. The important point is the relationship of each data. For example, in combination data like drivers have repeat with sudden speed dropping at specific crossroad is correct so often then we can assume that the crossroad has some safety issue. This kind of various information can be used not only for personalized services. It will be possible to offer new value to consumers with big data analysis. To realize this, it is important to build a system to handle different attributes of the data, similar to the products and the society data. Second, it is important, but again data is not only provided by only one car. When an output quantity to car increased then the amount of data is kept sending and receiving over the network. This crossroads a very important quantity of connectivity of each ship in the automatic. You can see that it goes from 2020 to 2035. In 2035, it is expected that all image data such as camera or rider will increase so that total amount of communication data from all reviews is predicted to be approximately 3.0 if divided per year, which is a hundred times bigger than in 2025. For this amount of data, it is important to process with a consideration of purpose and the timing of use. The path design with efficient data process is necessary with consideration of data volume, communication performance and responsibility. Last one is the loss city. To manage and control the car, each of the information needed to the process and providing them proper time. So we think it is important to spread the process according to the characteristics to process data efficiency, efficiency to the reality. Client points each issue takes a role to process data inside the car. Data process is finished with few seconds or needs to be done without network connection such as autonomous driving should be done at client side. Each takes a role to process data which are only used in the digital car and faster process preferred. Especially the information which is difficult to process in the client side due to processing capability or needs to accumulate data should be handled to add edge side. Cloud takes role and process data collected from the number of car. Cloud side takes and paper handle in case to generate and process value information even if data sometimes for example data from cars. To build effective and efficient network I think that the architecture design is very important. I have explained all importance reviews of information data but to use the information for each driver and cars. The situation of moving cars keep changing the movement. There is a difference driving technique and like send the test for each driver. So it is necessary to driver services or driving control information which we do the driver. To realize this AI will be an important role. There are two AI methodologies which is important to use for the car. One thing is the machine learning AI which has a majority with deep learning and just from fast experience. The other thing is loop based AI which just from data registered or configured in advance. This AI method needs to be arrived to be approved for private services. Let's think about building example of the service using AI to control some behavior of on-car, life and life center or crisis prevention. All of the car need to be controlled according to the same rule. In this case it is approved for private based AI for safety car control and it will become possible to set this driver route by making AI learning and driving data with machine learning. If there are any crossroads or routes when sudden braking open for car they can set the driving route excluding the points. If AI learning the preference of data and driver then it can set the driving route which the driving routes comfortable. As you can see it is necessary to apply and compile suitable AI methodologies for each purpose to realize safety and comfortable traffic control. But further discussion is necessary to determine which combination is reasonable as an automotive industry. For next generation of the connected car services we assure that various information which is connected from the connected car will not be limited to services of the car such as on-car development or safety driving support like ADAS or autonomous driving. For example it is expected to use foreign cases. Provide autonomous driving control to examine the usage of traffic brains and realize the efficiency. Realize effective road maintenance and condition arrangement by using road condition information protected from driving car. Control build safety and security such as priority control of emergency vehicle or inflation avoidance to residential road. Further we believe that the evolution of the connected car is surely contribute to improve the society infrastructure. Further evolution of the connected car there are still many issues and structural obstacles to overcome in each sector. To overcome we think that each field of ground edge and client need to be evolved with aligned steps ensuring quality and security. From that point of view relaxed can be applied to all fields and involved with aligned steps. In order to build a relaxed world to realize the solutions we believe the power of relaxed communication is necessary and we expected it also. Relax which is the most popular OS or the server and cloud and agile which make a breakthrough as a connected car cutoff. We would like to go forward inspired from relaxing the car to relaxing the mother automotive society with combination of these. LTT Data MSC will contribute to realize the power which our full knowledge accumulated in the connected car.