Prizes and Benefits
The final winners will get prizes inclduing cash, cloud credits and custimized gifts.
Schedule
Theme and Submission Requirements
In the challenge, contestants are required to build and submit weather-related solutions with AI and machine learning. By leverating meteorological data from different platforms, including but not limited to historical weather data, air quality monitoring data, meteorological monitoring data (wind, temperature, rainfall, etc.), and transport data, any weather-related fields can be chosen, including but not limited to the impact of weather pattern changes on urban traffic, air quality, airdrome control and harbor control, crops, revenues of supermarkets and restaurants, and theater ticketing.
A Updated PPT or PDF file (within 20 pages) based on your submission in the preliminary round.
- Please demonstrate the information required in the preliminary round more clearly.
- If you are using any Alibaba Cloud services in your project, please state clearly about what products you are using and how you are using them.
(Optional) A working demo of your project in one of the following formats:
- A link to a website/app which shows how your solution works included in your slides, or;
- Working files of your demo included in your submission.
(Optional) A video clip showing how your project works in one the following formats:
- A video file included in your submission, or;
- A link to a video on YouTube or other online video platform included in your slides.
Adoption of AI technology: 30%
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The submission provides an AI solution to a weather-related existing/future pain point of society, meets users’ demands, attracts public attention, and has a social influence. Algorithms and datasets used in the solution are clearly introduced in the submission.
Implementability: 20%
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The application of the submission is technically feasible, or there is an instance of such application. Using a working demo or video to show the solution will help you to get more points.
Commercial/social value & Innovation: 30%
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he submission is commercially viable with market share and a user base, or has social value; the project plan is complete and has clear goals. The submission is innovative, distinct from well-developed industry solutions, and outperforms existing products. The value and innovation of the submission are clearly demonstrated.
Usage of Alibaba Cloud products: 20%
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One or multiple Alibaba Cloud products are consumed by your account(s) and used in your solution, including for training models or building your working demo.
Project Introduction
- Problem(s) that the project/product addresses
- Solution overview, features, innovations, and core advantages (a demo is encouraged, but not required for the preliminary round)
Technology Adoption
- Technologies employed, technical architecture, and innovations
- Specifically, please provide information including but not limited to the data sets, algorithms, methods for training models, and tools you used.
Commercial Value
- market value, operation models, profit models, development process, etc.
Other Information Required
- Specified requirements for technical implementation: how to apply designated technologies and bonus technologies to present product features.
- Introduction of the project team
- Declaration of Originality
Application of AI technology
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The submission provides an AI solution to a weather- related existing/future pain point of society, meets users’ demands, attracts public attention, and has a social influence. Algorithms and datasets used in the solution are clearly introduced in the submission.
Innovation
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The submission is innovative, distinct from well-developed industry solutions, and outperforms existing products.
Implementability
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The application of the submission is technically feasible, or there is an instance of such application.
Commercial and social value
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The submission is commercially viable with market share and a user base; the project plan is complete and has clear goals; the entry has social value.
Reference Datasets on Tianchi
Historical Climate Observation and Stimulation Dataset
Historical Climate Observation and Stimulation Dataset is provided by Institute for Climate and Application Research (ICAR).
Bike-rental Dataset
Bike-sharing rental process is highly correlated to the environmental and seasonal settings. For instance, weather conditions, precipitation, day of week, season, hour of the day, etc. can affect the rental behaviors.
Denpasar Weather Data
This is historical weather data of Denpasar, Bali, Indonesia. It Contains weather data from Januari 1st, 1990 until Januari 7th 2020 (20 years, hourly)
Chicago Weather
This dataset contains Chicago weather data at Christmas spanning over 148 years. The first observation is from 1871, and the last observation is from 2018.
Global Historical Climatology Network
The Global Historical Climatology Network (GHCN) is an integrated database of climate summaries from land surface stations across the globe.
US Drought & Meteorological Data
This datasets' aim is to help investigate if droughts could be predicted using weather data as well, potentially leading generalization of US predictions to other areas of the world.
Seattle Weather Data
This dataset contains complete records of daily rainfall patterns from January 1st, 1948 to December 12, 2017.
African Agricultural Survey
The dataset specifies farming systems characteristics that can help inform about the importance of each system for agricultural production and its ability to cope with climate changes.