Robot Literacy 2026/1 – KV Tawau

*UMPSA STEM Lab Robot Literacy – Introduction to Robot and Robotics can be found here.

150 students had participated in this program, in collaboration with Kolej Vokasional Tawau. Students have gone through activities including robot anatomy, actuators and sensors.

Robot Literacy module introduced participants to the basics of robot construction, programming, and problem-solving through interactive challenges.


The initiative aimed to:

  1. Build digital and technical literacy among students.

  2. Nurture creativity, teamwork, and critical thinking.

  3. Spark early interest in engineering, robotics, and STEM-related careers.

Importantly, today’s program also reached underrepresented groups ensuring inclusivity in STEM education.

Thank you Yayasan UMPSA – En Jamil Jaafar, for initiating the program and coordinating the communication between STEM Lab and the participants.

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UMPSA News

BHE3233 BTS4433 – Week 7 – Sequential RTL – Lab 4

Welcome to Week 7! This week, we took a massive leap in our digital design journey by exploring Register Transfer Level (RTL) sequential circuits. Unlike combinational circuits, sequential circuits have memory, meaning their outputs depend not only on current inputs but also on previous input
history. At the heart of these sequential designs is the Finite State Machine (FSM).
In digital design, FSMs are used to control system behavior by transitioning between a finite number of states based on inputs and clock cycles.
When we build FSMs in Verilog, we generally divide the architecture into three main blocks:
        1. The State Register: This is a synchronous block (using always @(posedge clk)) that updates the current state to the next state at every clock edge, or resets it when a reset signal is triggered.
        2. The Next-State Logic: A combinational block that evaluates the current state and external inputs to determine what the next state should be.
        3. The Output Logic: A combinational block that generates the output signals based on the current state (Moore machine) or both the current state and inputs (Mealy machine).
In class, we looked at a practical example: a sequence detector acting as a lock that opens whenever the serial bit pattern “1011” is achieved.
Before writing any Verilog code, it is incredibly important to derive your state machine on pen and paper first. Drawing an abstract state diagram ensures your states and transition logic actually make sense.
For the “1011” detector, our state diagram tracks how much of the pattern we have seen so far:
        1. S0: Nothing matched yet.
        2. S1: Matched “1”.
        3. S2: Matched “10”
        4. S3: Matched “101”
        5. S4: Matched the full “1011” sequence (this is where the output goes high).
By mapping out the transition arrows—such as moving from S1 to S2 if the input is 0, or dropping back to S0 if the sequence is broken—you establish the exact mathematical behavior your next-state logic block needs to model.
Hands-On: Lab 4 and the Satellite Communication System
Once we nailed down the state diagrams on paper, we moved into the hardware phase with Lab 4: Finite State Machine for Satellite Communication Link
In real picosatellite systems, communication links require a strict, multi-stage initialization and termination process . You simulated this exact scenario using a four-state FSM:
      1. IDLE: Waiting for the start command.
      2. LINK_ESTABLISH: Attempting the communication handshake.
      3. DATA_TRANSFER: The active data transmission session
      4. LINK_TERMINATE: Securely closing the session 
During the lab, you mapped your DE10-Lite board’s switches to act as the transition triggers (e.g., SW0 to start communication, SW1 to signify link established) and used the LEDs to track which state the FSM was currently in.
By verifying the state transitions in a ModelSim simulation and testing it directly on the physical board, you successfully built a control system identical to those used in real-time embedded space missions !
Keep practicing drawing those state diagrams on paper before jumping into Quartus. See you next week!

 

2026 Book :) Digital System Design with Verilog: FSM, RTL Modelling, Pipelining and Static Timing Analysis

The book is finally in =).

There is a specific kind of satisfaction in hardware engineering—the moment a conceptual logic circuit transitions from a schematic to a functional physical implementation. My fascination with this process began in 1999 during my undergraduate studies under Professor Othman Sidek. Back then, the ability of an FPGA to house a vast array of logic functions felt revolutionary.

It all started with a project in my Digital Electronics 2 subject. I remember it vividly, we built an automated counter for badminton matches. The digital logic system was designed to detect whether a shuttlecock landed in or out of bounds to assist the umpire in ruling points. That small-scale project served as the gateway to a much deeper exploration into digital systems.

From Undergraduate Roots to GSM Architecture

By the time I reached my final year project, I was diving deep into digital systems for GSM communication modules. Through a family connection—my cousin, who was then a technician for a leading telecommunications provider—I gained invaluable access to the industry standards of the time.

I was particularly focused on implementing Convolutional Encoders, which were essential for error correction in mobile networks. At the time, we worked across the five primary channel types:

      1. TCH/FS (Full Rate Speech)

      2. TCH/HS (Half Rate Speech)

      3. FACCH (Fast Associated Control Channel)

      4. SACCH (Slow Associated Control Channel)

      5. SDCCH (Standalone Dedicated Control Channel)

The successful implementation of these designs wasn’t just a hurdle to pass for graduation, it was the foundation of my continued passion with digital logic =p

Fast forward to 2021, I returned to the classroom to teach Digital System Design. Re-engaging with the subject after years in the field felt like a homecoming. During this period, I began supervising Phuah Soon Eu on the project involving the implementation of metaheuristic algorithms on IC chips.

The inherent challenges of translating high-level algorithms into hardware were tackled: managing floating-point arithmetic, optimizing RAM architectures, and modifying algorithmic flows to suit the rigid requirements of digital implementation.

Introducing the Book: A Practical Path for the Novice

Through the project implementation, a persistent “missing link” in technical FPGA education literature. There is a steep cliff between learning basic Verilog and understanding the professional constraints of a production-ready FPGA design.

To bridge this gap, this book is introduced.

Digital System Design with Verilog: FSM, RTL Modelling, Pipelining and Static Timing Analysis

The philosophy is simple: The best way to learn a system is to build it. We designed this text to guide the reader through three critical phases:

      1. Foundations: Introduction to FPGA architecture and Hardware Description Language (HDL).

      2. Synthesis: A deep dive into RTL modeling and the complexities of Static Timing Analysis (STA).

      3. Implementation: Mastering FPGA-specific design and the art of optimization.

Moving from Functional to Professional

This book is specifically written for those at the “Novice to Early-Intermediate” stage. It is for the designer to learn to perform a functional simulation but needs to learn how to read synthesis reports, meet specific timing targets, and redesign circuits with objective-driven outcomes.

It has been a privilege to author this with Phuah Soon Eu, and we hope this work serves as a catalyst for the next generation of digital designers—much like a badminton counter did for me decades ago :).

Raspberry Pi Programming 2026/3 – KV Tawau

*UMPSA STEM Lab Raspberry Pi Programming Synopsis can be found here.

In the Raspberry Pi IoT session, 20 students and teachers from Kolej Vokasional Kulim were introduced to the concept of the Internet of Things (IoT) using Raspberry Pi on the UMP STEM Cube, a pico-satellite learning kit specifically designed to facilitate engineering learning.

The content covered basic digital input/output operations on onboard LEDs, as well as topics such as dashboard design using gyro meter and BMU280 sensor data, including collecting and storing data in a cloud database. Participants learned to interface sensors with Raspberry Pi boards and develop IoT applications for real-world scenarios. The session provided students with valuable insights into IoT technology and its applications in various domains.

A special appreciation is extended to Cikgu Shufi from KV Tawau, Sabah for coordination in facilitating communication between the participants and the UMPSA STEM Lab :).

Nurul April 26th

 

Raspberry Pi Programming 2026/2 – KV Kulim

*UMPSA STEM Lab Raspberry Pi Programming Synopsis can be found here.

In the Raspberry Pi IoT session, 28 students and teachers from Kolej Vokasional Kulim were introduced to the concept of the Internet of Things (IoT) using Raspberry Pi on the UMP STEM Cube, a pico-satellite learning kit specifically designed to facilitate engineering learning.

The content covered basic digital input/output operations on onboard LEDs, as well as topics such as dashboard design using gyro meter and BMU280 sensor data, including collecting and storing data in a cloud database. Participants learned to interface sensors with Raspberry Pi boards and develop IoT applications for real-world scenarios. The session provided students with valuable insights into IoT technology and its applications in various domains.

A special appreciation is extended to Cikgu Aminah dan Cikgu Huraiah from KV Kulim for coordination in facilitating communication between the participants and the UMPSA STEM Lab :).

Nurul April 26th

 

 

 

Raspberry Pi Programming 2026/1 – Mentor Training

*UMPSA STEM Lab Raspberry Pi Programming Synopsis can be found here.

In the Raspberry Pi IoT session, 24 UMPSA mentors were introduced to the concept of the Internet of Things (IoT) using Raspberry Pi on the UMP STEM Cube, a pico-satellite learning kit specifically designed to facilitate engineering learning.

The content covered basic digital input/output operations on onboard LEDs, as well as topics such as dashboard design using gyro meter and BMU280 sensor data, including collecting and storing data in a cloud database. Participants learned to interface sensors with Raspberry Pi boards and develop IoT applications for real-world scenarios. The session provided students with valuable insights into IoT technology and its applications in various domains.

A special appreciation is extended to En Mohd Jamil Jaafar for coordination in facilitating communication between the participants and the UMPSA STEM Lab :).

 

IMG_4939

TTT – Arduino and Edge Computing

As part of ongoing efforts to strengthen digital pedagogy and future-ready STEM education, a Train-the-Trainer (TTT) Teachers Training Programme was successfully conducted for teachers from across Pahang, focusing on Arduino programming using ESP platforms and Edge Impulse for image classification.

The programme was designed to equip teachers with hands-on experience in digital making while introducing fundamental concepts of machine learning, particularly in the context of computer vision and image classification.

Programme Objectives

The main objectives of this TTT programme were to:

    1. Familiarise teachers with digital making concepts using Arduino and ESP-based microcontrollers
    2. Provide foundational understanding of machine learning, specifically image classification
    3. Introduce Edge Impulse as an accessible platform for developing embedded AI applications
    4. Enable teachers to confidently integrate AI, IoT and embedded systems into classroom teaching and student projects
    5. Support the development of future-ready educators aligned with Industry 4.0 and AI-driven education

Hands-On Learning with Arduino and ESP

During the training, teachers were introduced to Arduino programming on ESP platforms (such as ESP32), covering:

    1. Basic Arduino IDE setup and programming workflow
    2. Interfacing ESP boards with peripherals (camera modules, sensors)
    3. Understanding microcontroller capabilities for edge computing
    4. Deploying lightweight AI models on embedded devices

This hands-on approach allowed participants to move beyond theory and experience how hardware, software and AI intersect in real-world applications.

Introduction to Edge Impulse and Image Classification

A key highlight of the programme was the introduction to Edge Impulse, a powerful yet beginner-friendly platform for embedded machine learning.

Teachers learned:

    1. The fundamentals of machine learning and image classification
    2. How to collect image datasets using ESP camera modules
    3. Data labelling and training simple image classification models
    4. Deploying trained models directly onto ESP devices for on-device inference (edge AI)

Through guided activities, participants successfully implemented basic image classification tasks, gaining confidence in applying AI concepts without requiring advanced programming or mathematical backgrounds.

Building Confidence in Teaching AI and Digital Making

Beyond technical skills, the programme emphasised pedagogical readiness. Discussions and activities focused on:

    1. Translating complex AI concepts into classroom-friendly learning activities
    2. Designing project-based learning (PBL) tasks using Arduino and AI
    3. Encouraging student creativity, problem-solving and ethical awareness in AI use
    4. Aligning AI and digital making activities with school STEM curricula

Teachers shared ideas on how these technologies could be adapted for subjects such as Asas Sains Komputer, Reka Bentuk Teknologi, STEM projects and robotics clubs.

Impact and Way Forward

This TTT programme marked an important step in empowering educators in Pahang with practical skills in embedded systems, AI and digital innovation. By strengthening teachers’ confidence and competency, the programme supports the broader goal of cultivating AI-literate students who are prepared for future technological challenges.

Moving forward, participants are expected to:

    1. Implement Arduino- and AI-based projects in their schools
    2. Act as multipliers, training fellow teachers and students
    3. Contribute to a growing ecosystem of responsible, ethical and sustainable AI education

Conclusion

The Arduino–ESP–Edge Impulse TTT programme demonstrates that machine learning and AI are no longer confined to advanced laboratories. With the right tools and training, educators can bring AI-powered digital making into everyday classrooms—sparking curiosity, innovation and future-ready skills among students.

This initiative reinforces the commitment to strengthening STEM and AI education at the grassroots level, ensuring teachers remain at the heart of Malaysia’s digital and educational transformation.