Guangdong Weichuang Video Summer Delegation: Big Data and Super High-definition Visualization

Mr. Xia Tuanli, Marketing Director of Guangdong Wetron Video Technology Co., Ltd., brought a keynote speech titled “Big Data and Ultra High-Point Visualization”. The following is the full text of the speech:

Xia Tuanli: Good afternoon, everyone, just from the morning to the afternoon, the main themes are about some of the development directions of visual products and smart life in consumer electronics. What I share with you today is behind my life. It is in the industry or what we call the company and the operating system, they are doing visually related products and technologies. I am from Viagra. The leader is not very clear about the Victron business. I met Viatron in a short video of one minute.

As we have seen, we have seen many large-scale command and control centers with large screens, which is a system-level solution for super-high-level visualized splicing display and back-end signal and data rendering.

The topic of today's presentation is Big Data Super High-Point Visualization. There should be some concepts in the command and control center for all of you here. Our subway, electricity, water, transportation, and so on. Every day in our lives, we can't live without the safe and stable operation of these public basic equipment.

I am talking about big data visualization today. The daily life we ​​enjoy in our daily lives is convenient. Every minute we run the system produces a large amount of data every minute. This data includes every individual consumer's contribution in life. For example, when we go out and take a subway, you are part of the data. Every day we consume, we use water for electricity, including making calls online, and all the behavior will generate data. This is the direction we will take in the future. A running system, we want to provide smarter wisdom to run the system. Learn more about the needs of our consumers.

Just now one person has always been really understanding the needs of customers, how to understand customer needs? Big data is slowly able to accumulate and better understand people's needs. Just mentioned that the urban public infrastructure is very close to our lives, and one can understand it. There are many that may be a little bit far from our lives. But no matter how these systems run, there needs to be a management system that runs management, control and its monitoring and operation. This is usually the operational monitoring in the enterprise application market, or called the operation management, from the military or From the perspective of public safety, there are some scenarios such as the command and control center.

These centers used to operate from the business point of view. We talked more about information construction. From production automation to the end, we called centralized management and control. At the highest level, decision-making and operation were smarter. Nowadays, various industries have begun to look smarter. In the past, the relationship between seemingly unrelated data was better to see what kind of demand the user represents behind the data, so as to make some decisions. The perspective of public safety is more about looking at the factors behind the information and the signals or instructions it brings. This is important for city management and security maintenance.

We see today that due to the informatization of the Internet, the informatization of enterprises, the informatization of the industry, and the construction of informatization, a lot of data is produced. Today, 90% of the world's human storage data are generated in the past two years. A data once said that the 5,000-year data of human civilization in the past may be the sum total of data generated during the current year or a very short period. Informatization brings information explosion. In the past, we talked about information explosion society. Where did this information come from? We have just read a lot about smart appliances. We also have many systems in the industry, its sensors, its operational data, including environmental change data, and all the information we collect is the source of data.

What is big data? From a technical point of view, big data is more about unstructured data. There are four characteristics, one is a huge amount, and the second is the speed of production. 90% of the data produced in two years. The third is diversity, and it has its value. In the past we did not care about the relationship between data. To give a simple example, we have a smart grid. We now say whether real estate is saturated. Real estate prices are noisy every day. Many vacancies, real estate are measured. Where do you come from? One can see some clues from the accumulation of some big data that appear to be of no value. For example, when using electricity data, we cover a lot of communities. Whether each household is really using electricity or not, electricity consumption peaks for a month or so of the year can be used. See the real people living in this community, which do not live, living distribution. This is a big data and it is very valuable for policy makers, including some companies. Can know his house and really use efficiency.

This is just an example, where the real value of big data is mentioned. There are four aspects here. One is the design, we will better understand customer needs through this kind of human behavior collection analysis. The second is the decision. Just mentioned how many infrastructure providers analyze user judgments and user trends. This is a decision-making basis. There is also discovery and storage.

What is the visualization of information? We mentioned just now that, in fact, we now generate very large amounts of data every day. Now it is TB, and then it is a lot more. People observe that there is no good form of data that does not make sense. Big data, now on a lot of big data value, we use some model algorithms and processing tools, we can find some trajectories from the seemingly unrelated irregular data and the accumulation of massive data, quickly capture these trajectories, let us know This is the visualization process. The data is presented again and extracted and the information is established. This is the visualization process. Our ultimate goal is to find some valuable information from our data that truly pertains to our lives and our cities and systems. This is the true value of big data such as insights and decisions we just mentioned.

In the past, enterprises were structured data, and some production data sales data became valuable information for the database. However, today it is seen that enterprises are not structured, such as video, many video information, sensor information, and many seemingly unrelated production garbage. It is rubbish data. These data are extracted by big data today and can be analyzed to some trend judgments or as a basis for our decision. This we now see is the value of corporate big data.

It should be said that in various industries, smart analysis on big data should bring some valuable values ​​to various industries or enterprises and become valuable assets. What is the real business decision demand? Businesses collect insights and then communicate and share data. In simple terms, four aspects, collection is the key data in real-time, and there is an appropriate data for correlation. Through the insight through the data table to see the essence, communication is the rapid transmission of data information in the associated people, to achieve consistent action. Then there is sharing. The information must be symmetrical and transparent so that the relevant personnel can quickly grasp the information and make corresponding actions.

We now see that this enterprise and government-related industries are facing what is the pain point of big data. First of all, information is the islanding effect of our past information system construction, especially the transformation from information to decision-making to the island effect. We see that information is independent. No correlation between systems. The second is the fast, batch-free extraction of operations between mass information. The third is judging the difficulties. There is also the era of video and massive video. We are now faced with two small and one small. The number of videos to be watched is small, because the equipment presented is limited. For example, the city’s 10,000 camera heads are all present at the same time, and there is no way to do it. Our management area is small because of its low expansion capability. Big data super-high visibility visual solution, a business system linkage, unified linkage of all data systems, the second is a super high score presentation, we want to use massive information presentation methods to carry valuable information for high-quality high-volume information Presented, the third is scientific decision-making, data mining and visualization.

Let's take a look at the current command and control center CCC, its visual development stage. The first phase is called usable. Currently, the subsystems of each industry command and control center can basically operate independently. The second stage is called linkable. The system uses hardware to supervise the wall on the screen and display the screen on the screen. The third stage of visualization is not the simple signal on the wall in the past. Visualization of data is presented through the basic data pull-through association abstraction to open the business relationship. The fourth is that it can be managed and there is an intelligent linkage mechanism, so that the data between departments can generate action linkage. There are some supportive decisions. The fifth is called intelligence. In the command and control center, there is a smart part, that is, a support system with intelligent decision-making, and an analysis system that can make its decisions appear in the quickest way and act in the fastest way.

High-definition visualization big data solution, including several parts in the visual control center, including remote expert support, multi-machine linkage, including theme display, including business intelligence visualization and resource management. From the perspective of demand classification, just mentioned that the command and control center is the core of business operations and is part of the brain. His basic needs are divided into three parts. The first is to be able to see the data I want, the second is to analyze, to analyze the relevance of the data and the value and significance of the data. The third part is the action. We visualize the action of the rapid transformation of industry information into our command.

All the different industries, its command and control centers, are basically scene-oriented intelligent visual concepts, what is the concept of scene intelligence visualization, regardless of any industry, whether it is transportation, electricity, energy or public safety, or one of our companies Run, run monitoring. Basically, there are four types of data. The first is environmental data. The data collected through the camera, sensors, operational monitoring equipment, and some acquisition device control devices on the production system are called environmental data. The second is business data, such as financial data, sales data, and some planning data in the industry. The third major category we call geographic information associated data. We now know that multidimensional information, our information should be associated with the corresponding location information, and then can effectively call the rapid association between information. The fourth is business intelligence analysis data.

The above four types of data summarize the data types involved in all industry control centers. These four types of integration and association can constitute a scenario of big data solutions. We have just mentioned monitoring and viewing angles, like smart cities, banks and so on. There is also analysis, visualization of urban traffic, and analysis of data. There is also control, we make quick information based on this information, such as signal control, command and control.

This is a simple framework. There are several key technologies for visualizing big data high scores. The first is the user data association. The data is extracted from the user's data. The second is data modeling and mining. The third is data rendering, which makes the data live, allowing people to quickly capture and visually understand and understand quickly. Then there is the presentation, how to present it, and switching hundreds of millions of information.

The next few cases for everyone to share.

The first one is applied in smart cities. We have seen that in smart cities, we are now the smart city or the concept stage. Now the country’s second pilot city construction has 183 cities, and it is currently 333 city-level cities above the national market. The unit establishes some goals for smart city planning. The core of a smart city is an urban service system that involves the operation of real city infrastructure and some of the service architectures of our cities. All the information in this system will be centralized in a city center for monitoring and management of facility operation monitoring and services. Information on transportation, humanities, and infrastructure, including all aspects, is gathered and presented in a city map.

This is finance. We know that finance is really the beneficiary of big data, more financial investment, the efficiency of creating value, big data brings effective analysis and some processing of data. We can see that the bank's data center can present data correlation analysis through the presentation of big data, various kinds of 2D and 3D data, and various data modeling methods, which can be very helpful for daily operations and for such decisions. . This is a case where the graphical change is the actual operation of the bank's data center, and it's a big data visualization.

This is a public transportation system. We don't see only one such transportation system based on cities. We don't see only one. For example, it is a public bus, it is a subway, it is an urban fast track, and the basic planning of public transportation in the whole city is related to multidimensional. Multi-level, is to take care of humans, take care of the travel needs of all types of people in the city, as a public transport perspective, it is also necessary to have a centralized presentation monitoring and scheduling command, when and when what events can do better Route planning, better vehicle deployment, different vehicle convergence and mobility. This is some big data visualization application of public transportation.

This is a large-scale petrochemical company, with a large petrochemical enterprise system and a very large number of people. The actual petrochemical correlation between each production link. For example, from logistics to processing and raw material processing, to the final product, a large petrochemical enterprise is divided into many small enterprises. As an industry-related, the supply relationship between each sub-production enterprise is crucial to its decision-making. important. This petrochemical company is the six major centers. The six major centers were independently operated and managed in the past. The planning and dispatching are all based on human management, which is inconvenient and inefficient. Today, it is linked through big data visualization methods and presented in a comprehensive manner between six centers so that real-time data can be quickly grasped. I can understand the issue of raw materials and immediately make scheduling arrangements for production.

Our public security officials today are in the impression that we see the public security management in the movie. It is a director who is sitting next to the phone and how to direct it and solve the case. Today, the police rely on data. We see that every camera on the street, the bayonet, including all the street patrols, including all the data generated by everyone behind us, are collected and analyzed under the public security system and can be consumed through our online activities. Acts, travel behaviors, and our geographic information are linked. With our true public security big data visualization application, we can quickly deploy a case, quickly discover or even prevent the occurrence of cases, and configure some key areas. These are realizable under the premise of big data visualization.

This is an emergency for the city. We know that apart from the public safety just mentioned, the urban management is also raining in the summer of the city. After the rain is big, it causes the city's internal aggression. In urban emergency management, we have established a command center. These command centers are also based on big data. The sensors quickly know the situation within the city and make some system disposals, including some facilities for flood discharge. These are controlled by big data in the city's emergency command center.

The above is just to share with you some relevant analysis of the big data ultra high marks visual industry.

thank you all!