DK Dr Hayati Pg Hj Mohd Yassin
hayati.yassin@ubd.edu.bn
RESEARCH INTERESTS
Biometrics
Neural Networks
Image Processing
Pattern Recognition
Information Security
FUTURE PROJECTS
Deep learning based wave and tidal in deep-water (Ocean Engineering)
Grant Details: UBD/RSCH/1.11/FICBF(b)/2020/004 Reliable and accurate predictions of deep-water wave conditions is crucial for any ocean engineering activities, for example, safe ship navigation, design of marine structures (like oil platforms and harbours), and design and management of marine energy systems as it has an impact on human safety, economics and clean energy production. Different empirical, numerical and soft-computing approaches have been proposed for wave height prediction. Wave conditions in regions where historical data is available and collected can be predicted using numerical and soft-computing methods. However, for new regions of interest, in this case Brunei sea, historical data of wave conditions is not available. Hence, there is a need for collecting and predicting the wave conditions data in Brunei sea. This project will employ advanced artificial intelligence (AI) algorithms and modelling methods to improve the accuracy of the wave conditions prediction. (FIT/IADA project)
Applications Invited
PhD or Master Students
Other engineering with AI projects: 1) Secure Cloud and Deep Learning based Smart Framework for Renewable Energy 2) Impact of Age and Ageing on Biometric Application 3) Data security and privacy-preserving on fog, edge and cloud based computing
(1) Grant Details: UBD/RSCH/1.3/FICBF(b)/2020/011 Due to the recent environmental concerns and long-term challenges in energy security, the Global energy scenarios are shifting more towards sustainable and renewable energy resources. As rightly reported by the International Renewable Energy Association (IRENA), renewable energy technologies are fast becoming cost effective and soon can compete with the traditional energy options. (2) The effect of ageing on biometric systems and particularly its impact on biometric recognition systems. Being biological tissue in nature, facial biometric trait undergoes significant changes as a person ages. Consequently, developing biometric applications for long-term use becomes a particularly challenging task. (3) Fog computing and edge computing are used interchangeably because both involve an intermediate level of processing and storage. However, the key difference between the two is the location of computing. In fog computing, the LAN acts as a gateway where as in an edge environment, computing is done at smart devices by devices like PACs .
Applications Invited
PhD or Master Students
Digital Agriculture using Intelligent Deep Learning Application
Digital agriculture is integrating both concepts – precision farming and smart farming. For farmers, digital agriculture allows for the opportunity to increase their farm’s production, save costs in the long-term, and eliminate risks. Many view digital agriculture as the future of the agricultural industry. In smart farming, the pertained Internet of Things devices tells farmers what they need to know regarding humidity, soil, water level, and other important metrics related to farming. Basically, this offers awareness to farmers about the current condition and makes them ready to face forthcoming challenges making their life easier. For example, by using smart agricultural sensors to monitor the state of crops, farmers can define exactly how many pesticides and fertilizers they have to use to reach optimal efficiency. There are two potential major issues that have been identified with regards to smart farming. That is the security of this IoT and environmental sustainability.
Applications Invited
PhD or Master Students
GRANT DETAILS
Grant Details: UBD/RSCH/1.11/FICBF(b)/2020/004
Wave and Tide Prediction for Brunei Deep-Water Operation
BND 65,000.00
Grant Details: UBD/RSCH/1.3/FICBF(b)/2020/011
Artificial intelligent management system (AIMS) for solar PV projects in Brunei Darussalam
BND 27,000.00
INDUSTRY EXPERIENCE
Industry Experience working at Cisco Premier Partner Certified in Brunei Darussalam and Brunei Shell Petroleum (BSP)