2021 Worldwide Champions

2021 Imagine Cup World Championship 2021 Imagine Cup World Finals - Round 2

2021 Imagine Cup World Championship

REWEBA's team photo
REWEBA

Kenya

The growing interest in automating many aspects of our daily lives has seen an increase in the use of emerging technologies such as Internet of Things (IoT) to address numerous societal challenges. A key challenge in many developing countries is health access, especially for people in rural or marginalized communities. In this project we looked at how we can leverage on the benefits of IoT technology to reduce the high infant mortality rate brought about by poor health access. Babies are required to go for regular check-ups from birth until the age of 24 months to detect growth and general health issues for timely intervention. However, many parents are unable to do this due to the cost of this check-up, and long distances to the health centres. Health centres are also very few and constrained with the lack of adequate personnel and resources required to conduct this screening. This project presents an innovative approach to reducing infant mortality in marginalized areas by addressing the key challenge of poor health access. To fulfil this, two novel ideas are integrated in the design. Firstly, it sets out to provide a solution that can conduct the typical screening functions conducted in health centres during regular infant check-ups which are growth monitoring and general health inspection. This primarily comprises of weight and temperature measurements in many rural areas. The proposed solution however presents opportunities to enhance this process by monitoring the body mass index and the presence of skin issues. It can be scaled to take additional measurements such as the babies’ heart rate and the breathing patterns. Innovations in remote infant screening using IoT technology have so far focused on the development of monitoring infants in incubators or the development of wearable technology. Our solution presents a method of screening infants with minimal patient disturbance.

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2021 Imagine Cup World Finals - Round 2

Hands-On Labs's team photo
Hands-On Labs

United States

The ongoing global pandemic due to COVID-19 highlighted how important remote education is. In fact, online education investments are supposed to grow to reach $350 billion by 2025, compared to $18.66 billion in 2019 (Li, 2020). Additionally, as remote education keeps gaining popularity, several institutes worldwide are considering the switch to remote learning even after the pandemic is gone. This consideration came after remote education proved how it could minimize running costs while reaching more students (Nortajuddin, 2020). However, as the industry keeps growing, the challenges are also highlighted; thus, leaving students frustrated and concerned about the future of their education (Haddadi, 2020). Many students reported a lack of "Hands-on lab experience" as their primary deterrent from online and remote education (Colman, 2020). This factor is even more significant for the more practical fields of study. For example, engineering, medicine, and science. While many online courses offer recorded or live videos showing lab work being done, students highlighted that nothing beats the experience resulting from using the lab equipment, making mistakes, and finally watching the results of your effort coming to life (Traft, 2020). Hands-on Labs is a set of remote laboratories that allows students to observe and remotely control various physical tools online in real-time for their courses. Depending on the curriculum, students can choose among different remote laboratories and book a time-slot on the website. On their desired time slot, instructors can add any number of students and assign various permissions for each student. For a robotics/coding course, for example, once the student's log-in to the website, they will be able to use a six-degrees of freedom robotic arm, upload their code/input and change the angles of the joints of the physical robot arm and observe the robot arm executing their commands in real-time. The platform also allows users an unprecedented control level over various aspects such as lighting levels, camera angles, audio controls, various control modes, etc. A deep understanding of the market landscape and the psychological factors involved in students' choices is needed to build that set of virtual labs. This project explores how a realistic and convenient remote lab experience can significantly improve students' educational experience across various age groups, geographies, and specialties. To measure the added benefit for students, a virtual robotics lab was initially designed and built to work with the Minerva Schools' at Keck Graduate Institute online classroom. A rigorous testing process that involves both quantitative and qualitative evaluation of students’ performance change is currently ongoing.

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Threeotech's team photo
Threeotech

Thailand

JustSigns is a web application for content creators to create sign language captions to improve the media accessibility for their hearing-impaired viewers. JustSigns accepts Youtube’s video URL, retrieves the video caption and translates all of the sentences into Thai Sign Language grammar. Then, the application will generate 3D sign language animation which the users can view side by side with the original video and share with their hearing-impaired viewer.

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ProTag's team photo
ProTag

New Zealand

ProTag is a smart ear tag for livestock that can detect the early onset of illness in real-time; lowering costs and increasing animal welfare along with farmers peace of mind. Temperature, movement and location sensors are embedded into an ear tag. Data collected is run through algorithms on board that can determine animal states such as: Chewing, lying, Sleeping etc. This semi-processed data is then transmitted over LoRaWAN where it eventually lands in a cloud database and is combined with data from other animals as well as geographical farm features. All this data on animal metrics and behaviour can then be feed into continually improving machine learning models targeted at identifying early illnesses. If early cases could be identified, then many proactive actions could be taken such as: Mastitis: - Cows with clinical or subclinical cases can be milked last – preventing spread of the disease. - Back flushing could be performed on clusters of clinical or subclinical cases. - Tailored treatment protocols can be administered. Lameness: - Trim claw of cows identified as lame. - Isolate cases that are suspected to be infectious. - Implement foot bathing when needed. BVD: - Early identification of PI calves. - Ensuring early pregnant cows avoid contact with BVD infected herd mates. - Herd testing could be done early. Reproduction: - IVF - Optimized grazing for stage of pregnancy. - Separation of calf’s - Identification of complication during calving. There are several aspects that make our approach novel. The first is the incorporation of GPS with other metric data into a small formfactor ear tag. Products incorporating the same hardware features are usually attached an animal’s neck which can cause problems when caught on objects. The second is a wholistic integrated approach to data analysis. Information from an animal is not viewed in isolation, but against the backdrop of geographic farm features such as shelter belts, water troughs and boundary fences.

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