HKU SAAS Data Science Lab of the Department of Statistics & Actuarial Science, The University of Hong Kong is organizing an AI Robotics Vision and Automation Technology Challenges Competition for Secondary School/Undergraduate/Graduated Students, and Companies. The aim of this competition is to promote development of artificial intelligence (AI) robotics vision and automation technologies at the school level and the industry level.
The competition encourages students and companies to develop innovative AI robotics solutions with AI, data science and statistical tools for solving current hot topics/problems in robotics vision and automation. The competition also serves as a platform for local secondary schools, institutions, and industries to share knowledge, innovation and experience on the application of AI robotics technologies for solving business problems, enhancing businesses’ competitiveness, and creating business insights for industries in social science, smart city, healthcare, education, and Internet of Things (IoT).
Below are the detail of the competition :
- Program Overview :
- The HKU SAAS Data Science Lab provides current AI robotics vision and automation problems/challenges for students and companies to solve and discover robotics innovation in statistics, AI and data science disciplines. Students and companies will give a presentation to the judging panel how they would solve the problem, and create innovative robotics application to demonstrate their solution
- The participants’ school/university teachers, and industrial partners will provide mentoring on innovation creation, techniques and skills of solving robotics problems, and project report writing for participants
- The HKU SAAS Data Science Lab will nurture students and companies on innovation development, business insights creation, and entrepreneurship
- The winning team will gain an award certificate
- Objective :
- Identify talented students in the statistics, AI, and data science
- Resolve current robotics vision and automation problems, and create insights for various industries such as social science, smart city, healthcare, education, and Internet of Things (IoT)
- Generate new ideas and innovations with AI robotics vision and automation technologies to increase business competitiveness
- Have practical hands-on experience on AI robotics vision and automation programming
- Take social responsibility to nurture students and companies on applying AI robotic technologies for solving business problems, creating innovation, and building entrepreneurial skills
- Timeline :
- Competition Official Kick Off and Webinar on introduction of AI in robotic programming
- Date : 2021-03-12 (FRI)
- Time : 1300-1600
- Format : Zoom
- Zoom URL : https://hku.zoom.us/j/5108381494
- Meeting ID : 510 838 1494
- Registration Deadline for joining the competition
- 2021-04-25 (SUN)
- Link for Briefing Session Registration : https://saasweb.hku.hk/datasci/register/
- Mar to Apr, 2021
- 8 weeks for participants to think about their idea
- Workshop for students to pitch their ideas, nurture their innovative thinking for robotics vision and automation solutions and obtain feedback from HKU Data Science Lab
- 2021-05-07 (FRI)
- May to Aug, 2021
- 16 weeks for participants to write the business case, and implement the prototypes
- Submit the business case, presentation and demo on YouTube
- 2021-08-29 (SUN)
- Announcement of Winners
- 2021-09-19 (SUN)
- Award & certificate presentation ceremony
- 2021-09-30 (THUR)
- Requirement of Submission :
- Number of Participates in Each Team
- 2-4 people
- Format of Project Report
- Number of words
- The business case writing should have minimum 2000 words (around 5 pages) and not more than 4000 words (around 8 pages)
- Case Writing Format
- Chapter 1 Project Background (200-400 words)
- Chapter 2 Problems (100-200 words)
- Chapter 3 Current solutions and its limitations and why AI robotics vision and automation technology that can solve the problems and limitations (400 – 800 words)
- Chapter 4 Your proposed solutions (800 – 1600 words)
- Chapter 5 Conclusions (100 – 200 words)
- Chapter 6 Future work (400 – 800 words)
- Chapter 7 References and Acknowledgement (not count as the word count limits)
- Prototype Format
- The python program and an AI robotic demonstration in YouTube (set as unlisted)
- Number of words
- Number of Participates in Each Team
- Problems (choose one or more)
- AI in Finance
- Use AI technologies to improve the banking and financial services, e.g. customer services, chatbot, surveillance, business monitoring, accounting and auditing, etc
- AI in Healthcare
- Use AI technologies to improve the healthcare business (e.g. personal health, social distancing monitor, disease screening and diagnostics, therapy operations, etc)
- Use AI technologies to enable patients (or their careers) to track and modify lifestyle attributes critical in the prevention and early interception of potentially more serious health conditions
- Use AI technologies to enable consumers to easily detect their own (or those in their care) health conditions, to aid in the timely and appropriate preventative or treatment intervention
- AI in SmartCity
- Use AI technologies to help retail business, shopping malls, building management, etc., (e.g. better customer services, minimize payment counter queueing, energy saving and security surveillance for building management, etc) to improve customer service and/or product offerings
- Use AI technologies to optimize buildings’ operational efficiency and occupants’ experience through an integrated solution in order to achieve increase efficiency, resiliency, sustainability, comfort and safety
- AI in Social Science
- Use AI robotics vision and automation technology to resolve and improve some current social issues (e.g. traffic congestion, pollutions vs conservation, elderly living conditions, etc)
- AI in Education
- Use different AI robotics and/or intelligent machines in STEM Education to cultivate the interest of school/university students or company trainings in AI study
- AI in Internet of Things (IoT)
- Use AI technologies to improve the intelligence of smart home solutions, or others, through sensing technologies
- AI in Finance
- Hardware and Software commonly used in AI, IoT and school STEM projects (Participants are not limited to use the following robot simulator or robots for programming)
- Robot Simulator
- NVIDIA Isaac SDK: https://developer.nvidia.com/isaac-sdk
- SimSpark: http://simspark.sourceforge.net/
- Gazebo: http://gazebosim.org/
- Webots: https://cyberbotics.com/
- SimSpark: http://simspark.sourceforge.net/
- NVIDIA Isaac SDK: https://developer.nvidia.com/isaac-sdk
- Real Robot
- Hardware
- Nvidia Jetson https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/
- All CPU+GPU, single-board computer for small, medium to large scale AI and IoT projects; Medium to High Cost
- Raspberry Pi https://www.raspberrypi.org/
- Mostly CPU, single-board computer for small to medium scale AI and IoT projects; Low to Medium Cost
- Arduino https://www.arduino.cc/
- CPU only, single-board computer for small to medium IoT projects; Low Cost
- Nvidia Jetson https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/
- Software
- Scratch https://scratch.mit.edu/
- Easy to learn programming concept and understand application logic
- Coding time consumption and not powerful for large application development
- Not used by AI industry for real-world application development
- Python https://www.python.org/
- Take time to learn and need mature coding skill
- Rich opensource libraries and frameworks available freely for AI development
- The most popular programming language for AI development
- Scratch https://scratch.mit.edu/
- Hardware
- Robot Simulator
- Scoring Criteria
- Solution to problem (20%)
- How well the evaluation and reviews of the current potential solutions are discussed? (Knowledgeable)
- How well does the solution resolve the problem? (Problem Solving Skill)
- How relevant is the solution to the problem? (Critical Thinking)
- What value can the solution add? (Business Insights)
- Innovation (20%)
- How innovative is the solution? (Innovation)
- Any companies in the market have provided similar solutions? (Knowledgeable)
- Traditional approach versus non-traditional approach? (Critical Thinking)
- Has the solution applied any latest technologies in statistics, AI, and/or data science? (Knowledgeable)
- Commercialization (20%)
- Can the solution be commercialized practically (cost, timeline)? (Global Outlook)
- How much commercial value can the solution bring (revenue)? (Business Insight)
- Design and Features (40%)
- How well has the solution leveraged the design? (Problem solving)
- How good is the user experience in the application design? (Problem Solving)
- Solution to problem (20%)
- Prizes (HKU SAAS Data Science Lab will polish the business case writing if the case report is in high standard, and will publish the polished business cases in their website and/or potential conference/journal with the participants.)
- First prize
- Souvenir
- Innovation and Business Insight Award Certificates
- Second prize
- Souvenir
- Global Outlook and Critical Thinker Award Certificates
- Third prize
- Souvenir
- Knowledgeable Award Certificates
- Best Business Concept
- Souvenir
- Problem Solver Award Certificates
- Other groups
- Team Spirit and Risk Taker Award Certificates
- First prize
- Competition Official Kick Off and Webinar on introduction of AI in robotic programming
Official Website : https://saasweb.hku.hk/datasci/competitions.php
Flyer of Competition : https://saasweb.hku.hk/datasci/files/AI_Robotics_Vision_and_AutomationTechnologyChallengesCompetition.pdf