Meet the 2018 Imagine Cup Semifinalists!

This post has been republished via RSS; it originally appeared at: Student Developer Blog articles.

First published on MSDN on Jul 24, 2018
Imagine Cup challenges student developers to innovate for the future, and to bring forward their most original ideas to the global stage for the opportunity to win prizes, Azure grants, and a one-on-one mentoring session with Microsoft CEO Satya Nadella.

This week, 49 student teams from across the world have brought their best technological solutions to Microsoft headquarters for the 2018 Imagine Cup World Finals. Starting with a Tech Showcase on Monday, teams pitched and gave demos of their projects in the hopes of advancing to the next round. Spanning leading technology and resources such as Artificial Intelligence, Virtual Mixed Reality, and Big Data, Machine Learning and more, it is inspiring to see students’ passion and creativity combined to create technology with the potential to change the world.

Out of all these amazing teams, 18 Semifinalists have been narrowed down. Judges selected 15 teams to move forward from the Tech Showcase, and three additional teams were saved in the Wildcard round, selected by their peers to advance. These teams will present their projects in front of a panel of judges for the chance at a spot in the Championship round.

Follow the action and stay tuned to see which top 3 teams will be selected to compete in the World Championships on July 25th.

Congratulations to all our incredible Semifinalist teams, and good luck with the rest of the competition!


Team NameCountry & UniversityProject Name & Description

Drugsafe	India RV College of Engineering	Drugsafe was developed to provide multi-layered checks to validate genuine drugs and decrease illness from counterfeit drugs. Using an app with three unique checks, drugs are quickly validated as safe or not safe, and the user is immediately notified.
iCry2Talk	Greece Aristotle University of Thessaloniki	iCry2Talk proposes a low-cost and non-invasive intelligent interface between the infant and the parent that translates in real time the baby’s cry and associates it with a specific physiological and psychological state, depicting the result in a text, image and voice message.
ADAM Robo	Brazil Centro Europeu	ADAM Robo is a visual acuity screening software used to test and prevent common vision problems. ADAM uses bot conversation guiding an individual along anamnesis and vision tests which can identify possible refractive errors such as myopia (nearsightedness), hyperopia (farsightedness), presbyopia (loss of near vision with age), and astigmatism as well as Daltonism (color blindness).
smartARM	Canada University of Ontario Institute of Technology	smartARM is a robotic hand prosthetic, created using Microsoft Azure Computer Vision, Machine Learning and Cloud Storage. The robotic hand uses a camera embedded in its palm to recognize objects and calculate the most appropriate grip for an object. Using Machine Learning, the more the model is used the more accurate it becomes.
Mediated Ear	Japan University of Tokyo	Mediated Ear is software for hearing-impaired individuals to focus on a specific speaker among a multitude of conversations. Mediated Ear can relay specific sounds in audio waveforms through deep learning.
PINE .	Malaysia Universiti Tun Hussein Onn Malaysia	PINE. is a Machine Learning based non-invasive sensor to measure and categorize pineapples based on their sweetness. The goal is to enable Malaysian farmers to reduce waste and increase efficiency when evaluating their produce by predicting a pineapple’s ripeness before harvesting.
SochWare	Nepal Nepal Engineering College, College of Information Technology and Engineering, Madan Bhandari Memorial College	SochWare designed a solution called E-Agrovet to help farmers identify plant diseases, suggest mitigation strategies, connect with experts, and get updated with recent agriculture findings. Additionally, the solution will also enable farmers to alert nearby harvesters about their crops with the goal of reducing the need for pesticides in farming.
Peppa Team	China Sichuan University	Peppa Team created a toy car that can help diagnose ADHD and train kids’ ability to focus. The app can provide the results of early examination, real-time detection, and adjuvant therapy. It is not only a wonderful combination of brain-computer interface and deep learning, but also a breakthrough in the application of Recreation Therapy, achieving painless and convenient diagnosis and treatment.
Team Sentinel	New Zealand University of Canterbury, University of Auckland	Sentinel is an intelligent tool that reimagines the way we manage tank water supplies. The team is working to create a platform that facilitates a toolkit with everything from autonomous supply management, to sustainable tips and forecast insights. With key relationships to industry leaders in property management and agricultural, the team strives to bring an industry-standard IoT platform to meet the real problems faced by companies.
Fe Amaan	Pakistan National University of Sciences and Technology	Fe Amaan is a wearable belt which regularly monitors fetus health through the use of IoT sensor device which is placed on a mother’s abdomen. The device captures the fetal heart rate and movement and sends it via Bluetooth to a mobile app. The main features of this system are to provide automated analysis of fetal health on a regular basis without harming the mother or child. As the system makes remote monitoring of the fetus possible, it aims to reduce the high rate of intrauterine deaths and stillbirths in Pakistan.
Biolegend	Taiwan National Taiwan University of Science and Technology, National Chung Hsing University	"Bioknee" is a rehabilitation system system providing clinical therapists and patients a communication platform during a procedure. It can predict the time to heal through Machine Learning, encouraging the patient to continue rehabilitation.
BeeConnex	Thailand King Mongkut’s University of Technology Thonburi	The BeeConnex team designed and developed an IoT-based solution for beekeeping called the Smart Hive. Their solution captures sounds, images, weight, and humidity from inside the hives, and transmits the data to the cloud. Signals are then processed and classified using techniques including: signal processing, feature extraction and deep learning. Beekeepers can remotely monitor several hives in real-time and can be notified instantly when an abnormal situation arises.
InterviewBot	UK University of Manchester	InterviewBot is a web-based application tailored to aid students with video or physical interviews when applying for jobs. It gives real-time feedback on interview-style questions. Companies can also use this tool to assess their candidates’ performance, with the written transcript allowing employers to dissect the interview in detail.

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Team NameCountry & UniversityProject Name & Description

Pengram	USA University of California, Berkeley	Pengram is an AR/VR platform which allows engineers from around the world to be holographically ‘teleported’ into a workspace when needed. For example, if an operator repairing a $100,000 medical device needs help, they will be able to wire into the service, and using a Hololens can watch an expert perform the repairs in 3D.
Team Prometheus	USA Arizona State University	Prometheus combines surveillance drones and concepts of machine learning to detect wildfires while they are still in their early stages. The concept is to leverage the vast amount of wildfire images and videos available on the internet to train a machine learning algorithm to detect the presence of a fire. A drone then flies over parks and forests collecting the images, and an algorithm will determine the confidence level for if a region is about to develop a fire.
Vinculum	USA University of Massachusetts Amherst, Northwestern University, Rensselaer Polytechnic Institute	Vinculum leverages image processing and computer vision technology to determine if separated family members might be in another location and help reunite refugee families. The application determines a similarity score between a submitted image and the photos in the database. The application utilizes Microsoft’s Cognitive Vision APIs and Azure ML models to determine a similarity score between two photos. The user will then be shown the top matches.
Hachy	Canada University of Waterloo	Hachy aims to provide an easy way for farmers to identify the development status of an egg by enabling autonomous egg development identification and tracking using Machine Learning.
Pavo	Germany Rhine-Waal University of Applied Sciences	Pavo Vision makes websites more accessible to visually impaired users. Utilizing AI, images, and other tools, non-readable website content will be analyzed and made available to visually impaired people. Mistakes in analysis can be fixed and the algorithm will get smarter over time by utilizing crowd-sourcing to generate more accurate descriptions.

Which of these teams will be crowned the 2018 Imagine Cup Champion and take home the trophy? Watch the Championship show live on July 25th at 9:00am PT to find out!