Comparison for Smart City Data

I、Introduction

Urban agglomerations in bay areas enjoy great developing superiority and competiveness. With various advantages of open economic structure, efficient resource allocation capabilities, strong agglomeration effect, and advanced international communication network, economies in bay areas play a prominent role in the world. The San Francisco Bay Area, the New York Bay Area, the Tokyo Bay Area and the Guangdong-Hong Kong-Macao Greater Bay Area are currently listed as the world's four largest Bay Areas. As the last one to be established, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) ranks among the top in terms of aggregate economic output. However, thanks to large total population and land areas, per capita GDP of GBA also lags behind that of other three bay areas. Based on the development of smart cities in the four major bay areas in the world, participants are supposed to conduct comparative analysis in accordance to the city data of the four major bay areas including New York, Tokyo, San Francisco, and Guangdong, Hong Kong and Macao. Challenges and pain points of these smart cities in the Bay Area shall be explored to further clarify the strategic development status of GBA. Participants may create practical proposals or innovative methods to solve problems the Guangdong-Hong Kong-Macao Greater Bay Area faced in its development.

Requirements
Based on the relevant data of GBA Area provided by the competition committee, or in combination with other Bay Area data that is independently obtained, participants shall compare the gaps and find pain points of these smart cities in the Bay Area. Integrated with strategic development direction of the Guangdong-Hong Kong-Macao Greater Bay Area, project proposal or plans shall be conducted.

Data Introduction
1. The datasets of the Guangdong-Hong Kong-Macao Greater Bay Area are provided by the organizing committee. Participants are encouraged to refer to other public data resources, for instance, the New York City Open Data, for comparison and analysis. (https://opendata.cityofnewyork.us/data/)
2. All data have been sampled and desensitized to protect privacy of users and data security.
3. Involving sensitive data, the reference data is allowed to be used in this competition only. Any data leakage or usage for other purposes is strictly prohibited.

II、Competition Rules

III、Review Methods

The contest observes a principle of being fair, equitable and open and strictly abides by the review procedures. It follows standard operations to ensure the objectivity and authenticity of the review results.
Rules of review
    1. The review board holds the final say and legal binding effect;
    2. Preliminary and semi-final contests: At least five experts shall be involved in review for each project. 
    3. Final contest: At least nine experts shall be involved in review for each project.
Requirements for review
1. Review board: The expert team for review can comprise university or college professors, scholars from scientific research institutions, industry experts, investors from venture investment institutions, persons in charge of listed companies, financial experts and management experts. 
2. Filing of review experts: All experts engaged in review for the contest shall file their profiles for record to the contest organizing committee, including name, age, gender, organization, position, contact information, qualification and certificates of honor and background introduction. 
3. Archiving of review documents: The review scoring sheet shall include the reviewer’s signature and review comments.  
4. Review method: Contesting projects are scored by scoring sheets, with a full credit of 100 points. Each reviewer scores the project separately. After all scoring sheets are ready, the highest and the lowest scores are removed and the weighted average of the rest scores is the final score of the contestant. 
5. Review dimensions and weights
● Technology, algorithm and product (25 points) 
● Innovativeness points and implementation scheme (30 points) 
● Project value and feasibility (20 points) 
● Industry and market significance (10 points) 
● Data analysis results(5 points) 
● Team performance (5 points) 
● Financial performance (5 points) 
Total: 100 points 
About scoring items：
        (1) Technology, product and algorithm: Descriptions of product development and production strategies, industry characteristics, focus of competition, major algorithm, technical indicators and key technologies which primarily involve the technology, product and background, as well as the current progress.
        (2) Innovative points and implementation scheme: Innovative points of the project or product, the prospective marketing strategies of the project or product, product profit models, and whether there is a detailed implementation plan in place.
        (3) Industry and market significance: Market positioning and demand analysis, industry history and outlook, rationality of the marketing positioning, forecast of the future market sales, technical barriers to the industry, trade barriers and policy restrictions. 
        (4) Project value and feasibility: Commercial value, social value and positive influence of the project; feasibility.
        (5) Data analysis results: Data analysis method, analysis result description, self-obtained data description (if any).
        (6) Team performance: Composition of the core team, and whether the background, qualification and expertise of the team members are capable of supporting the whole project throughout the R&D and innovation.
        (7) Financial performance: Demonstration of the history and prospective financial performance of the company, demonstration of the expected financial performance of the team, whether there is a financial barrier, and capital usage details including fixed asset investment, ongoing construction, R&D investment and management fees.  
        (8). Review scoring basis: Experts will focus on the submitted project proposals and refer to the review dimensions to single out outstanding teams.