The Internet of Things (IoT) for Built Environment and Automation Professionals course is a 24-hour training programme designed to equip participants with fundamental knowledge and practical skills in IoT technologies and their applications in smart buildings, automation systems, and infrastructure environments.
This course introduces participants to IoT system architecture, sensors, networking, data collection, system integration, and dashboard monitoring. Participants will learn how IoT enables automation, real-time monitoring, operational efficiency, and data-driven decision-making in the built environment sector.
Through a combination of theory and hands-on practical exercises, participants will learn how to configure IoT devices, integrate systems, and develop basic monitoring solutions. Real-world examples from facilities management, construction, and automation industries will be used to demonstrate practical applications.
This course is suitable for engineers, technicians, facilities management personnel, automation professionals, and individuals seeking to develop competencies in IoT technologies for built environment applications.
Gain a clear understanding of what IOT is and how it can be used in everyday work.
Learn how electronics tools can improve development, support decision-making, and spark new ideas.
Explore practical ways to apply IOT in residential, commercial and workplace settings.
Review real-world case studies to see how organizations are using IOT effectively.
This course is open for everyone to attend
Basic use of a computer
Duration: 3 days
Location:
Centrium Square, 320 Serangoon Road #10-03, Innovation Room
If you are looking to build strong technical capability in Internet of Things (IoT) and apply it directly within the built environment, facilities management, automation, and smart infrastructure sectors, the Internet of Things (IoT) for Built Environment and Automation Professionals course at AAT Training Hub in Singapore is designed for you.
Here is why this programme stands out:
The course is led by trainers with hands-on experience in IoT system architecture, sensor integration, microcontrollers (e.g., ESP32/ESP8266), building automation systems, and industrial data communication protocols. Participants gain practical exposure to real implementation scenarios in smart buildings, energy monitoring, environmental sensing, and automation control systems.
IoT cannot be mastered theoretically. This programme emphasizes structured lab-based learning, where participants work with:
Sensors (temperature, humidity, light, motion, ultrasonic)
Microcontrollers and embedded boards
Cloud dashboards and data logging platforms
MQTT / HTTP communication workflows
Basic automation logic and control integration
You will design, wire, program, and deploy functional IoT prototypes aligned with real-world building and automation use cases.
Unlike generic IoT courses, this curriculum is specifically contextualised for:
Facilities managers
Building engineers
M&E professionals
Automation technicians
Energy management teams
Smart city planners
Applications covered include:
Smart energy monitoring
Environmental and indoor air quality sensing
Remote asset monitoring
Predictive maintenance concepts
Building performance analytics
Participants learn how IoT integrates into:
Building Management Systems (BMS)
Industrial automation environments
Workplace safety monitoring
Environmental compliance reporting
This bridges the gap between technical implementation and operational decision-making.
As Singapore accelerates its smart nation and green building initiatives, IoT competency is becoming a critical skill set. This programme enhances your ability to:
Propose and implement smart monitoring systems
Improve operational efficiency
Reduce energy costs
Contribute to digital transformation initiatives
Participants leave with deployable technical skills — not just conceptual understanding.
Upon fulfilling the course requirements with a minimum attendance rate of 75% and demonstrating proficiency in the assessments, candidates will be awarded a Certificate of Completion from AAT Training Hub, along with a nationally recognised
WSQ Statement of Attainment.
Artificial Intelligence (AI) is a branch of computer science focused on building systems capable of performing tasks that would typically require human intelligence. These tasks include learning, reasoning, problem-solving, understanding natural language, and perceiving and interpreting sensory information. AI systems aim to replicate and sometimes exceed human cognitive abilities, with applications in a wide range of fields, from robotics and healthcare to finance and transportation.
Reactive Machines: These AI systems are designed to perform specific tasks based on current inputs without storing past experiences or learning from them. They are limited in scope and are unable to adapt to new or unexpected scenarios. A classic example is IBM’s Deep Blue, which defeated the world chess champion in 1997.
Limited Memory: This type of AI can learn from historical data to some extent. For instance, self-driving cars observe surrounding vehicles over time to make driving decisions. They don’t retain a permanent memory but analyze recent data to act and adapt to new situations.
Theory of Mind: This is a more advanced type of AI that understands human emotions, intentions, and beliefs, enabling more sophisticated interactions. While still largely theoretical, advances in this area are ongoing in fields like human-robot interaction.
Self-Aware AI: This is the most advanced form of AI, which would have consciousness, emotions, and self-awareness. Although still in the realm of science fiction, self-aware AI is often considered the ultimate goal for the future of AI research.
Machine Learning (ML): ML is a subset of AI that uses algorithms and statistical models to enable systems to improve their performance on a task through experience. Examples include supervised learning, unsupervised learning, and reinforcement learning.
Natural Language Processing (NLP): NLP enables machines to understand, interpret, and respond to human language. This component is essential in applications like virtual assistants, chatbots, and language translation services.
Neural Networks: Inspired by the structure of the human brain, neural networks consist of layers of interconnected nodes (neurons) and are foundational in deep learning, which powers image and speech recognition systems.
Computer Vision: This area allows AI systems to interpret and make decisions based on visual data, such as images and videos. It’s commonly used in facial recognition, object detection, and autonomous vehicles.
Robotics: Robotics integrates AI to create machines that can perform physical tasks autonomously or semi-autonomously. Applications include industrial automation, healthcare robotics, and self-driving cars.
Healthcare: AI helps in diagnosing diseases, developing personalized treatment plans, and even performing surgeries using robotic assistants.
Finance: AI is used in fraud detection, algorithmic trading, and personalized financial advice, among other applications.
Transportation: AI powers autonomous vehicles, optimizes logistics, and enhances traffic management systems.
Customer Service: Virtual assistants and chatbots use AI to provide customer support, answer questions, and manage requests efficiently.
AI continues to evolve, pushing boundaries in various sectors and leading to innovations that reshape our daily lives. Its development raises ethical considerations, particularly regarding data privacy, job displacement, and the need for human oversight to ensure beneficial and responsible AI deployment.
Having basic computer skills is sufficient, as the course is designed to be beginner-friendly and covers the fundamental aspects of programming.
Our trainers are experienced in teaching beginners, adept at delivering complex information in a patient and easily understandable manner, ensuring that you can keep up with the course.
Upon successful completion of the course, you will receive a Certificate of Completion from AAT Training Hub and a SkillsFuture WSQ Statement of Attainment (SOA).
The SOA is a certification that identifies you as a competent person in the above topic and is recognised as one of our national qualifications
You can bring your own laptop for the course
| Start Date | End Date | Time | Location | Language | Register |
|---|---|---|---|---|---|
"The course is well-structured and conducted by experienced trainers."
"Trainers were very supportive, I passed my certification smoothly."
"Great hands-on practice with the . Highly recommend."