Since 2020, TAR UMT has been collaborating with Advantech Co Malaysia Sdn Bhd through the Internet of Things (IoT) equipment support for Industry 4.0 implementation and the AIOT Developer InnoWorks programme. Examples of such innovative projects are the One-Piece Manufacturing Individualised Solution (OMIS), Smart Campus Solution, Smart Agriculture in Herbal Farm and Ginger Farm projects.
This year, the Faculty of Computing and Information Technology (FOCS) was honoured to be invited to showcase their student projects at the Advantech ASEAN WISE-IoT Partner Conference, held from 7 - 10 June 2023 at Ascott Gurney Hotel. This event brought together industry leaders, professionals, and technology enthusiasts to explore the latest innovations and solutions in using Advantech WISE series products. The conference showcased a diverse range of cutting-edge solutions in areas such as the integration of IoT, artificial intelligence, and other emerging technologies into Advantech's product portfolio.
FOCS showcased two projects which are the Smart Agriculture and Face Mask Detection solutions. The team that presented the projects to conference attendees consisted of FOCS lecturers, Assoc Prof Ts Dr Tew Yiqi and Ts Dr Tan Chi Wee as well as Bachelor of Software Engineering (Hons) students, Wong Wai Zhong and Chan Yung Her.
(left photo) Assoc Prof Ts Dr Tew during his presentation to the conference delegates.
(right photo) Ts Dr Tan (rightmost) explaining about the Face Mask Detection Solution project to an interested visitor.
Yung Her (leftmost) and Wai Zhong (second from left) explaining the workflow for Smart Agriculture solution to the conference visitors.
In the Smart Agriculture solution, the long-range radio (LoRa) and wireless technology were used for transmitting the sensor data from the plant site, including soil moisture, temperature, electrical conductivity, pH and fertiliser ingredients such as nitrogen, phosphorus, and potassium to a cloud-based database. The solution includes functions for remotely controlling the water valve, scheduling for fertilising the plant, and live camera view providing instant computer vision processing to monitor the plants’ health.
To demonstrate how the Face Mask solution worked to enhance the safety and health status of humans in confined spaces, a webcam and portable tripod were set up at the conference. Then, the trained object detection model YOLO v4 was utilised to detect and compile statistics of conference attendees who were wearing masks correctly, incorrectly and not wearing any.
An overall view of TAR UMT’s projects showcased at the conference.
On relating his experience of sharing about his final-year project with the conference visitors, Wai Zhong said: “As a student, I feel honoured my project is featured in the conference. Interacting with visitors helped me further strengthen my confidence in not only presenting but also in networking with professionals.”
Meanwhile, Yung Her added: “The interactions I had with the visitors were very enriching. I learnt a lot from the questions they asked me about my project and I greatly appreciate the ideas and suggestions they shared with me too.”
