đź“ť Summary
Universiti Teknologi Malaysia (UTM) strengthened its edge AI expertise through a two-day training program with Infineon Technologies, equipping 15 academics with skills in edge artificial intelligence, embedded systems, and the Internet of Things (IoT). The training focused on the Infineon PSoC Edge E84 AI Kit platform and explored applications in smart systems, industrial monitoring, and AI-driven IoT solutions. The program aims to empower UTM lecturers with practical skills to transfer to students and support the university’s efforts in enhancing future-ready education and academic-industry collaboration.
KUALA LUMPUR, May 6 – Universiti Teknologi Malaysia (UTM), through the Faculty of Artificial Intelligence (FAI), successfully organised a two-day Training of Trainers (TTT) Infineon PSoC™ Edge E84 AI Kit programme on 4 and 6 May 2026 at UTM Kuala Lumpur. The programme gathered 15 academics from UTM Kuala Lumpur to strengthen competencies in Edge Artificial Intelligence (Edge AI), embedded systems, and the Internet of Things (IoT).
The training was conducted by Infineon trainer Pong Chi Leong, who guided participants through both theoretical and hands-on sessions using the latest Infineon PSoC™ Edge E84 AI Kit platform. The programme forms part of the ongoing collaboration between UTM and Infineon Technologies in advancing industry-driven talent development and innovation in AI-enabled embedded systems.
Throughout the programme, participants were introduced to the fundamentals of Edge AI, which refers to the deployment of artificial intelligence directly on edge devices without relying heavily on cloud computing. This approach enables faster processing, lower latency, improved data privacy, and real-time intelligent decision-making for IoT applications.
The Infineon PSoC™ Edge E84 AI Kit offers a powerful development platform integrating microcontroller processing, AI acceleration, sensor connectivity, and wireless communication features. During the hands-on sessions, participants explored basic application development, sensor integration, IoT communication, and lightweight AI implementation at the edge level. The training also highlighted potential applications in smart systems, industrial monitoring, intelligent automation, healthcare devices, and AI-driven IoT solutions.
In line with the Train-the-Trainer (TTT) approach, the programme aimed to empower UTM lecturers with practical skills that can be transferred to students, research groups, and future academic training activities. The initiative also supports UTM’s ongoing efforts to enhance future-ready education and strengthen academic-industry collaboration in emerging technologies.
The programme was further supported through the UTM–Infineon Innovation Launchpad (UIIL), a collaborative platform established to accelerate innovation, research, and talent development in embedded AI and intelligent systems. The initiative reflects FAI UTM’s commitment to advancing AI education and preparing academic communities for the rapidly evolving digital and semiconductor technology landscape.
Through this programme, UTM continues to position itself as a proactive institution in empowering educators and researchers with advanced technological knowledge aligned with Industry 4.0 and next-generation AI applications.
Author: Ir. Dr. Hazilah Mad Kaidi and Dr. Mohd Shahrizal Rusli
