Malaysia, Univerisiti Tun Hussein Onn Malaysia (UTHM)
XIEN YIN YAP
Yit Peng tan
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Do you know that pineapples are ranked third-most important, and second-most exported tropical fruit in Malaysia? Before shipping the fruits, exporters have to determine the quality of pineapples by using a refractometer, which also means that a number of fruits are subjected to destructive analysis, leading to wastage. Our team developed a sensing device with IoT that integrates with machine learning using Azure cloud computing that can predict the sweetness of pineapple. With the device, we hope can help the pineapple industry improve efficiency and reduce wastage in Malaysia. Besides that, we hope our device can enable farmers to evaluate the pineapples’ optimal level of ripeness in a non-intrusive manner, before being harvested.
We, the PINE, are students from Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia. The team leader, Tan Yit Peng, who involved in optical sensing research since 2015. The team member, Yap Xien Yin involved in optical sensing research since 2015 as well and in machine learning since 2016 and Zulnazim Bin Dzulkurnain, experience in Internet of Thing since 2015. Together, under the supervision of our mentor, Dr Chia Kim Seng, we developed an IoT optical sensing system with Azure cloud computing feature that enable non-invasive sweetness prediction of pineapple.