In addition to the first and second place winners at the Group Innovation Challenge, the InnoTech department also awarded prizes to teams that demonstrated great potential through their solutions.
This was done to encourage the spirit of innovation and reiterate the department’s philosophy of the importance of the iterative process and learning from all types of innovative attempts.
The Leading Edge Technologies Award was presented to a two-member team from the Thimphu Tech Park Ltd.
The team introduced the concept of On-Device AI (TinyML) and the potential role it could play in Industrial Predictive Maintenance. They argued that through TinyML, companies would be able to predict machinery fault or breakdowns and prevent that failure by taking relevant action, adding that future updates would include the ability to schedule maintenance in advance. Through their solution, the DHI companies would be able to unlock the potential of IoT with edge AI, and enable ultra-low power machine learning.
A study by The Wall Street Journal and Emerson reported that unplanned downtime, which is caused 42% of the time by equipment failure, amounts to an estimated $50 billion per year for industrial manufacturers. Failure or degradation can cause loss of efficiency, increased energy consumption, system failure and expensive maintenance. These are all problems that the team aims to address through their proposal.
In addition to their final presentation, the team also conducted a demo session to showcase the potential of AI/ML when combined with IoT. They designed a system to classify the operations of a fan – to determine whether the fan was powered or off, working normally or had issues in operating.
New fast growing field of AI/ML is emerged, TinyML. Not a hype, it’s a game changer.~TTPL Team
We would like to express our sincere thanks to DHI for organizing such tech event as we were inspired to see what’s possible with machine learning on-device.~TTPL Team
The team consisted of the following employees from Thimphu Tech Park Ltd:
– Nanda Kumar Gurung, Associate Software Developer, ePIS Project
– Deepesh Chhetri, Associate Software Developer, ePIS Project