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 Safety Control 

 Sensing 

Identification of optimal sensor locations where direct measurement of temperature distributions in plastic injection moulds is not available due to geometric constrains  

Design of thermal controllers for uniform temperature distribution using fuzzy and neural networks techniques

Project: Thermal management in laminated die systems using neural networks, PhD program (2007-2011) 

Project: Development of Smarter Mobile Working System Based on The Safety & Reliability, Co-PI (2015-2016) 

Design of safety control algorithms for collision avoidance and safety evaluation that play a key role of both maximizing workspaces and ensuring the highest level of safety for an operator and co-workers around an excavator

Development of sensing algorithms for motion perception of mobile machines and environmental obstacles   

Performance validation of control and sensing algorithms using co-simulations with virtual reality techniques

Survey on state-of-the-art technologies in real-time tire-state monitoring for heavy-duty vehicles

[1] https://bit.ly/2ZWh1zt   [2] https://bit.ly/2VeeqC1

Project: Survey on state-of-the-art technologies in real-time tire-state monitoring for heavy-duty vehicles, PI (2018), Research project sponsored by KIMM (Korea Institute of Machinery and Materials)

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Development of sensing algorithms to predict a potential collision

Project: Development of predictive safety algorithms for an excavator using the 3D sensory information, PI (2018-2020), Sponsored by UOIT Startup Fund and UOIT VPRII Research Infrastructure Fund

Project: Clarington Snowplow Route Optimization Project, PI (2020/10-2021/02), Sponsored by The Municipality of Clarington

Finding optimal routes for snowplowing in Clarington by applying optimization theories/methods and GIS technologies

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bit.ly/38Trelj; bit.ly/3aPkLd1; bit.ly/3e0yKib

Project: Study on AI-based sensor fusion technologies for autonomous driving and operations of specialty vehicles, PI (2020/10 - 2021/03), Sponsored by AKCSE (Association of Korean-Canadian Scientists and Engineers) - KIMM Matching Fund

Survey on state-of-the-art technologies in sensor fusion technologies for specialty vehicles

Project: Study on de-noise filtering algorithms for mobile machines in industrial sectors under dust environments, PI (2021/05-2021/11), Sponsored by KIMM (Korea Institute of Machinery and Materials)

Developing de-noise filtering technologies and algorithms to deal with the dust environment using a Lidar sensor

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Project: Development of de-noise filtering algorithms for mobile machines in industrial sectors under dust environments using AI methods, PI (2022/05-2022/08), Sponsored by KIMM (Korea Institute of Machinery and Materials)

Developing dust filtering technologies and algorithms with a Lidar sensor using deep learning/machine learning methods 

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