Official announcement: Official notice of the National Industrial Internet Data Innovation Application Competition

In order to promote the development of my country's industrial big data industry and accelerate the engineering implementation of data innovation application scenarios covering all elements of the industrial Internet, the entire industry chain, and the entire value chain, the Fifth National Industrial Internet Data Innovation Application Competition (hereinafter referred to as the "Contest") It is scheduled to be held from September to November 2021. The competition is sponsored by the People's Government of Bao'an District, Shenzhen, and undertaken by China Academy of Information and Communications Technology. The relevant matters are hereby notified as follows:

1. The name of the contest

The 5th National Industrial Internet Data Innovation Application Competition

Second, the theme of the competition

The future of digital-driven smart industry is here

3. Organizational unit

Organizer: People's Government of Bao'an District, Shenzhen
Special guidance: Shenzhen Municipal Bureau of Industry and Information Technology
Organizer: China Academy of Information and Communications Technology
Co-organizers: Harbin Electric Wind Energy Co., Ltd., Zoomlion Heavy Industry Co., Ltd., Guangdong Meiyun Smart Number Technology Co., Ltd.
Co-organizers: Industrial Big Data and Intelligent System Branch of Chinese Mechanical Engineering Society, Beijing Industrial Big Data Innovation Center
Technical support: Kunlun Zhihui Data Technology (Beijing) Co., Ltd.

4. Competition organization

Competition Organizing Committee: Responsible for the organization and implementation of the competition. The Office of the Competition Organizing Committee is affiliated with China Academy of Information and Communications Technology.
Competition Expert Committee: Responsible for the review of each competition question, it is composed of experts in scientific research institutes, industry institutions, large enterprises and other fields.

5. Competition Arrangement

(1) Setting of contest questions

1. Wind farm short-term wind condition prediction driven by unit data

https://www.bilibili.com/video/BV18U4y1w7mK/?aid=676030973&cid=423898669&page=1
: Harbin Electric Wind Energy Co., Ltd.
Background of the : With the expansion of onshore wind turbine assembly plant sites, wind turbines installed in areas with frequent sudden changes in weather are increasingly affected by weather changes. When the wind condition changes suddenly, due to the hysteresis of the control system, it is easy to cause the unit to experience excessive load, or even to reverse, causing major economic losses. At the same time, the accuracy of the existing ultra-short-term wind power forecasting is poor, resulting in the wind power forecasting system being of little reference value for grid dispatching, and it will cause owners to produce a large number of power generation plan assessments. Because of the high unit price of common wind speed measurement products such as lidar, they are greatly affected by the weather, and it is difficult to realize batch application deployment, and it is still difficult to be reliable and forward-looking under large time and space scales. Therefore, reliable ultra-short-term wind forecasts are imminent. The prediction of ultra-short-term wind conditions is a worldwide problem. If big data and artificial intelligence technology can predict the wind speed and wind direction data of each unit in a short time in the future, it can improve the foresight of wind turbine control and increase the load of wind turbines. Safety; At the same time, improving the existing ultra-short-term wind power prediction capabilities will bring significant safety value and economic benefits.

2. Forecast of demand for heavy equipment accessories

https://www.bilibili.com/video/BV1JQ4y1D7hg/?aid=718593649&cid=423897714&page=1
: Zoomlion Heavy Industry Co., Ltd.
Background of the : As high-end equipment, heavy equipment is widely used in key industries and fields such as energy, transportation, shipbuilding, construction machinery, metallurgy, aerospace, and military industry. The forecast of demand for heavy equipment parts is an important factor that affects the accuracy of stocking, and it has a huge impact on operating indicators such as inventory occupation, spot fulfillment rate, and sluggish inventory rate. Due to the sparseness of parts sales historical data, the difficulty of forecasting parts demand is increased. If big data, artificial intelligence and other technical means can be used to improve the accuracy of parts demand forecasting, it will bring significant economic benefits and improve customer satisfaction.

3. Intelligent prediction of product material demand in discrete manufacturing industry

https://www.bilibili.com/video/BV1NL411G7o3/?aid=463538654&cid=423903296&page=1
Questioning party : Guangdong Meiyun Smart Number Technology Co., Ltd.
Background of the : In recent years, the external environment of enterprises has become more and more uncertain, and the complex and changeable external environment has caused many problems in the supply chain of enterprises. Changing demands are difficult to predict, plans cannot keep up with changes, and many urgent orders are inserted, resulting in long delivery cycles, low delivery rates, high shortages and high inventories. Therefore, accurate product material demand forecasting is very important for companies in the discrete manufacturing industry. On the one hand, it can ensure that the production plan can proceed smoothly, and on the other hand, it can effectively reduce material waste and over-purchasing. However, because the demand for product materials is affected by many factors, it is difficult to predict. Therefore, more excellent intelligent AI algorithms are needed to improve the accuracy of prediction, so as to help companies reduce inventory costs, improve procurement efficiency, shorten delivery cycles, and improve Enterprise's ability to resist risks.

(2) Schedule and competition system

Competition tasks, schedule specific time, judging rules, please refer to the official website of the competition for details
https://www.industrial-bigdata.com/Challenge/2021ii

Registration time (September 28-October 30) Contestants registration, registration, and team competition.
The training data set will be opened during the preliminary round (September 30th-October 31st). Players submit their answers according to the preliminary round requirements, and the system will automatically give scores.
Final time (November 2-November 8). The contestants selected from the preliminary rounds enter the finals, and the contests and results are submitted based on the newly provided data.
Final defense and awards (end of November). Invite the winning teams of each final session to gather in Bao'an District, Shenzhen for on-site defense, accept the expert committee’s evaluation, and finally calculate the final score (80%) and defense score (20%), and select the final winning team for awards .

6. Participation conditions

The competition is open to the whole society, and teams and individuals from various enterprises, institutions, universities, scientific research institutes and other organizations can participate.

7. Name of the award

There are first, second, and third prizes for each contest, and they will compete for one million prizes together. There will be more opportunities for you to settle in Shenzhen.

8. Other

The final interpretation right of the competition belongs to the competition organizing committee. For the latest news of the competition, please log on to the official website of the competition for inquiries.

Official website address:
https://www.industrial-bigdata.com/Challenge/2021ii

Contact email:
[e-mail]