As the pandemic struck, a vast majority of offices in Sri Lanka started a “working from home” system in order to reduce the risk of exposure of employees.
While we were enjoying the fruits of being with our loved ones for most of the day, some were not so lucky – especially the brave souls who were employed in the healthcare sector. While they were doing a commendable job, they too had their fair share of worries: the risk of exposure being a primary risk.
The healthcare workers who dealt with COVID-19 positive patients were quite literally on the front lines – despite the masks, hazmat suits, and protection, there was always a risk of getting infected – a worry some workers were quite vocal about.
Continue reading “A system to monitor COVID-19 patients remotely”
Following the publication of my paper, I was invited to collaborate on yet another research. This time involving the detection of musical patterns in real time. The project was the initial step in a larger idea of an Internet-of-Musical-Things system. The idea was this: “a smart musical instrument, which is able to convert musical notes to MIDI signals in real time, and a pattern detection system, which is able to recognize pre-programmed patterns, in real time, and use that data to control peripheral devices such as stage lights or smoke machines”.
Continue reading “Detection of Musical Patterns in Real-Time”
For a while throughout my last year of the masters program, I was thinking left right and center for a good project. I thought about several things, robotics, image processing, or an interesting gadget.
I landed on a brilliant idea! Why not do something about music, which I absolutely love. After racking my brain, I thought of designing an interesting and intelligent musical indexing and retrieval system – I will talk about this on a later post.
Upon doing some preliminary work, me and my supervisor realized that this is too much; there were so many things to consider – musical information retrieval, machine learning and sentiment analysis were some of the topics involved. The first stage of the work seemed sufficient in breadth and depth for a good research, so we stuck with it.
Continue reading “Musical Onset Detection and the S-Transform”