Artificial Intelligence (AI) is one of the most recognized and rapidly evolving branches of Computer Science worldwide. AI refers to machines or systems that mimic human intelligence and behavior, enabling them to learn, reason, and make decisions like humans. Today, scientists are continuously advancing AI technologies to enhance machine capabilities, allowing them to imitate human actions and improve our day-to-day efficiency.
AI has the potential to revolutionize industries by solving complex problems more effectively than humans. It is already being used to tackle numerous global challenges, from environmental sustainability to healthcare innovation. iWISE encourages young minds to explore the power of Artificial Intelligence, utilizing it not only to address real-world issues but also to foster creativity and critical thinking while having fun with cutting-edge technology.
Through the iTECH – Artificial Intelligence category, we aim to inspire students to harness the potential of AI in solving problems that matter to them, empowering the next generation of innovators.
Story: A large agricultural company currently uses traditional methods to assess the health of its crops across vast farmlands. These methods are time-consuming, expensive, and sometimes inaccurate. The company is looking for an innovative solution to overcome these challenges and improve productivity and profits.
Task Objective: The goal of this task is to create an AI program using the Python programming language that can determine the health of crops in a given image. The program should be able to analyse various farm images and provide an output for each image as “Healthy Crops Confirmed,” “Unhealthy Crops Detected,” or “This is not a farm image.”
Story: In a world where robots and humans coexist, a city police department is upgrading its systems to combat crime using artificial intelligence. They seek a new AI-powered robot police officer to assist in predicting potential criminals.
Task Objective: The goal of this task is to create an AI program using the Python programming language that can predict the likelihood of suspects being criminals based on their personal information. The program should be able to utilize various data such as criminal records, occupation, education level, marital status, residence location, driving history, and online activity to train its model and predict the criminality of new individuals.
Task Objective: The goal of this task is to create an AI program using the Python programming language that can recognize emotions from human faces in images and videos. The program should be able to take various images and videos as input and classify the emotion depicted in each.
Requirements for Virtual Finals:
• No theme for this category.
Requirements for Global Finals:
• Participants must submit written abstract describing their work together with their presentation.
• Entries must be the original work.
• The original copy of the work must be presented to the judges.
• No clip art, stock photos, or copyrighted materials.
• Abstract, Portfolio, Poster.
• Group submission is up to 3 participants.
• No theme for this category.
Judging will be done at the discretion of the iWISE Olympiad Committee. All submissions will be judged by a panel selected by the iWISE Olympiad Organization. The Judges will score each criterion on a scale of 0-5, with zero being the lowest and 5 being the highest rank.
Accuracy: the solution correctly addresses the problem statement and produces the expected results.
Completeness: All parts of the problem are fully solved as per the requirements specified in the challenge.
Functionality: the solution runs without errors and handless edge cases appropriately.
Readability of Code: Code is well- organized in order.
Modularity: Code is modular, with functions and methods that have a single responsibility and can be reused.
Professionalism: the submission is professional and polished, reflecting a high level of effort and attention to detail.
Testing: Comprehensive test cases are provided, covering a wide range of scenarios and edge cases.