Ideate-Prototype-Realize (IPR) is an individual project that all MIbD students have to undergo as a graduation requirement, which is spread over 3 terms (1 year). Students can decide on the topic of the project, and work closely with their advisers throughout the entire year to develop their projects in 3 phases, ideate, prototype, and lastly realize. Students can also choose for their IPR topic to be the same as their thesis, which allows them more time and guidance towards the completion of their thesis.
Monthly get-together sessions are organized for MIbD students to come together and share on the topic and progress of the project, using only 1 powerpoint slide. Advisers of MIbD students do join in the get-together sessions to provide feedback on how the projects can be improved.
Here are some examples of ongoing student projects:
William Siew Jing Wen – Harnessing Mobile-Based technologies for Care Giving of Persons with Dementia (PWDs)
The I-P-R project looks at the application of mobile-based technologies for information and support services in care giving for persons with dementia (PWD), using the case of the Dementia Friends mobile app introduced in 2018. It aims to identify gaps in the use and design of mobile-based technologies when providing support for PWD and their caregivers.
With an initial mobile app prototype designed with the different stages of the caregiver journey, the project will run tests to validate its usability and suitability of users based on its enhancements. The work done would contribute to the area of care giving, in terms of the design, development and implementation of mobile technologies as well as the evaluation strategies, usability attributes, human-mobile interaction design elements and other key factors which are relevant for ongoing and future research studies.
Ng Jian Yi Mervin – Programming the 4D Printing of Shape Memory Polymers for Biomedical Applications
In Additive manufacturing processes, when temperature control is involved, there are common inaccuracies caused by warping, cracking and bending due to material shrinkage. However, if we understand this phenomena and predict these situations, not only can we reduce the inaccuracies, but we can also utilize these deformations to create 3D geometries without the use of structural supports, which also eliminates material wastage and reduces the time for printing.
The aim is to develop a prediction model after investigating factors that can control material deformation, so designers can achieve desired 3D geometries just by printing them in 2D.
Edith Gracia Sharon Lawrence – Prediction of Turbulent Flow Behavior Using Machine Intelligence
In the era of Big Data, when there is a universal need for increased precision in lesser amount of time, this project finds itself at the crossroads of the data-intensive field of Fluid Dynamics and the data-driven reality of Machine Learning. With the usage of advanced Neural Networks, the project aims to facilitate turbulent fluid flows more effectively at high level of accuracy, optimal resolution and low computational time.
The current focus is on the implementation of Neural Networks architecture that solves low cost Direct Numerical Simulations for 2D turbulence which would ultimately be extended to be applied to real world 3D turbulence.
Shen Tianruo – Development of Fluorescent Sensors for the Detection of Glucose in Human Body Liquids
The current research project is based on the existing glucose fluorescent probes. Through the combination of the computational calculation and experimental verification, the mechanism principles and best reaction conditions of the probes will be investigated in depth. A new compound with high selectivity and sensitivity will be designed and synthesized after the exploration of the fluorescent probes in different generations. Such compound will be applied as a main probe to detect the glucose concentration by using the human body liquids like saliva, tear or sweat. On this basis, a new fluorescent sensor with the advantage of painless, non-invasive and high efficiency will be developed to reduce the pain of diabetics in the process of measuring their blood glucose level.