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Project Introduction

The objective of FarmTab is to boost the productivity of urban farming by automating the farming process by embedding Internet of Things (IoT) and Artificial Intelligence (AI) technologies into one platform. FarmTab is designed to enable seamless data collection from various sensors, such as pH level, temperature, humidity and moisture in urban farm conditions. The AI models track and predict various environmental impacts on crop yield for urban farms.

Project Members

* Project Leader
Name Position/Degree Department, Institution, Country
Chong Yung Wey * Lecturer National Advanced IPv6 Centre, Universiti Sains, Malaysia
Ooi Boon Yaik Assistant Professor/ 
Ph.D.
Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Malaysia
Cheng Wai Khuen Ph.D. Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Malaysia
Muhammad Niswar Head of Cloud Computing  
and Internet Engineering 
/Ph.D.
Department of Informatics, Faculty of Engineering, Universitas Hasanuddin, Indonesia
Achmad Basuki Associate Professor/ 
Ph.D.
Universitas Brawijaya, Indonesia
Naoki Shinohara Professor/Ph.D. Research Institute of Sustainable Humanosphere, Kyoto Univeristy, Japan
Widad Ismail Professor/Ph.D. Universiti Sains Malaysia
Tan Eng Kee Research Assistant Universiti Sains Malaysia
Hasnuri Mat Hassan Senior Lecturer/Ph.D. Universiti Sains Malaysia
Zainal Professor/Ph.D. Universitas Hasanuddin, Indonesia
Zulkifli Tahir Lecturer/Ph.D. Universitas Hasanuddin, Indonesia
Abdul Azis S Lecturer/Ph.D. Universitas Hasanuddin, Indonesia
Raden Arief Setyawan Lecturer/Ph.D. Universitas Brawijaya, Indonesia
Myint Myint Sein Professor/Ph.D. University of Computer Studies Yangon, Myanmar
Khin Than Mya Professor/Ph.D. University of Computer Studies Yangon, Myanmar
Thi Thi Soe Nyunt Professor/Ph.D. University of Computer Studies Yangon, Myanmar