Navigating the Evolution from Industrial Revolution to Industry 4.0

Navigating Evolution from Industrial Revolution 4.0 and 5.0

industry revolution

During the recent “Let’s Sembang AIoT Session,” we delved deeper into the progression of the industrial revolution, revisiting key points and exploring their connection to transformative technologies such as AI and IoT. Our discussion shed light on the intricate relationship between these advancements and the evolution of industry.

industry 4.0 vs industry 5.0

Industrial Revolution 1.0 (18th to 19th centuries):

Introduction of Mechanization: This revolution was marked by the transition from agrarian economies to industrial ones, primarily powered by the invention of the steam engine.

Early mechanization laid the foundation for modern manufacturing processes, focusing on efficiency through machinery and standardization.

Industrial Revolution 2.0 (Late 19th to early 20th centuries):

Mass Production: This era saw the rise of assembly lines and interchangeable parts, notably spearheaded by innovations like the electric motor and the assembly line.

 Standardization and mass production became central, emphasizing economies of scale and process optimization. Introduction of early automation concepts streamlined production.

Industrial Revolution 3.0 (Late 20th century):

Automation and Electronics: The advent of computers and automation technologies revolutionized manufacturing, enabling more precise control and customization.

 Automation expanded significantly, integrating computer-controlled systems for inventory management, production scheduling, and quality control. Emphasis on data collection and analysis for process optimization.

Industrial Revolution 4.0 (21st century):

Digitalization and Interconnectivity: Industry 4.0 is characterized by the fusion of digital technologies with traditional manufacturing processes, leveraging concepts like IoT, AI, and big data.

 Smart factories emerged, where cyber-physical systems monitor processes in real-time, enabling predictive maintenance, agile production, and personalized manufacturing. Integration of IoT devices and AI algorithms optimize production workflows and resource utilization.

Industry 5.0 (Emerging):

Human-Centric Automation: Industry 5.0 seeks to reconcile automation with human labor, emphasizing collaboration between humans and machines.

 This era focuses on integrating advanced robotics and AI with human expertise, fostering a symbiotic relationship where machines augment human capabilities rather than replacing them entirely. Adaptive manufacturing systems respond dynamically to human input and evolving market demands.

In practical terms, smart manufacturing principles across these revolutions involve leveraging technology to enhance efficiency, quality, and flexibility in production processes. This includes deploying sensors for real-time monitoring, utilizing data analytics for predictive maintenance and quality assurance, implementing robotics and automation for repetitive tasks, and integrating AI for decision support and optimization. Ultimately, the aim is to create agile, adaptive manufacturing systems that can respond effectively to changing market dynamics while maximizing productivity and resource efficiency.

industry 4.0 IOT gateway application

Axiomtek industrial IoT gateway were introduced in the application of AIoT OEE Connect where a standard node red open source development tool can be used in this ICO120, one of the IIOT edge gateway that is capable of handling most data collection requirement in manufacturing environment.

To Watch our session on some discussion topic relate to the industrial revolution, click the link below:-


AIoT and Dataspace integration

AIoT and Dataspace integration

5G AIOT and Dataspace integration

Dataspace and AIoT

AIoTmission brought to you the AIOT integration with Dataspace this round in the ” Sembang AIoT session”¬†¬†

In a very layman’s terms, the Dataspace is just like a physical Library or a warehouse where you keep all your books and goods and you have a way to manage them well with a good retrieval, storing, and use method. In the digital terms, dataspace can be of the data you store in the computers, server and storage devices where when it is connected with the internet, it allows reading, writing, and process within the environment. Expanding this part, it can be located at the cloud or data lake at the cloud. The contents can be of any of of files formats from any applications, medial files and¬† databases.¬†

In simple terms, think of a Dataspace as a digital library or storage room. It’s a place where you keep all your digital “books” and “items,” which means all kinds of data, organized so you can easily find, use, and store them again. Just like in a physical library or warehouse, there’s a system in place to help you manage everything smoothly. In the world of technology, this “Dataspace” refers to the data you save on computers, servers, and other storage devices. Once connected to the internet, this setup enables you to read, write, and process data within this digital environment. It can stretch even further, reaching into the cloud or becoming part of a data lake housed in the cloud. This digital collection can include anything from various file formats generated by different applications, media files, to databases.¬†

Dataspace and data eco system with AIOT

Dataspace is formed with the connected infrastructure called Data Eco system. There are several layers in the Eco System. From the very low level of Sensors or IOT sensors that forms the data source that piped into the managed data entities to the applications and processing, AI and IoT play a significant roles in it.

Components of a Dataspace Ecosystem

Technological Infrastructure: This includes all hardware and software components, such as data storage systems (databases, data lakes, cloud storage), data processing tools, and networking systems that support the storage, processing, and movement of data.

Data Governance and Management: Policies, standards, and procedures that ensure data quality, security, privacy, and compliance. This aspect also covers the management of metadata, which facilitates data discovery and understanding.

Integration and Interoperability Tools: Software and platforms that enable the seamless connection and interaction between different data sources and formats. These tools help in mapping, transforming, and querying data across the ecosystem without requiring uniformity.

Analytics and Processing Capabilities: Advanced analytics, machine learning models, and processing tools that can work with diverse data types to generate insights, forecasts, and reports.

User Access and Collaboration: Interfaces and protocols that allow various stakeholders, including data scientists, analysts, and business users, to access, share, and collaborate on data insights within the ecosystem.

Security and Compliance Mechanisms: Systems and practices that protect data integrity, confidentiality, and compliance with legal and regulatory requirements.

Importance of a Dataspace Ecosystem

An effective dataspace ecosystem enables organizations to harness the full potential of their data assets by breaking down silos and promoting a more integrated and collaborative approach to data management. It supports decision-making processes, innovation, and operational efficiency by providing a holistic view of the organization’s data landscape. Additionally, it enhances agility by allowing for the rapid integration of new data sources and technologies, adapting to changing business needs and technological advancements.

Challenges in Building a Dataspace Ecosystem

Creating a dataspace ecosystem involves addressing several challenges, including the integration of heterogeneous data sources, ensuring data quality and consistency, managing data privacy and security, and fostering a culture that values data-driven decision-making. Successful implementation requires a strategic approach, involving both technological solutions and organizational change management.

In summary, a dataspace ecosystem represents an advanced model for data management, aiming to create a cohesive, efficient, and flexible environment for leveraging data across an organization or community.

Now, how does this relate to AI (Artificial Intelligence) and IoT (Internet of Things)?

AI and Dataspace

AI is like a smart librarian in this virtual library. It doesn’t just help you find things but also understands what you might need even before you ask. For example, based on what you’ve looked for in the past, it can suggest new information or make connections between different pieces of data to help you make decisions. This is possible because the dataspace organizes data in a way that AI can easily access and learn from it, helping the AI to get smarter over time and provide you with more personalized and accurate assistance.

IoT and Dataspace

Imagine if every book and item in the library could talk and tell you exactly where it is, how it’s feeling (like if a device is overheating), or even if it’s about to run out of battery. That’s what IoT devices do in the dataspace. These devices, like smart thermostats, fitness trackers, and even smart fridges, are constantly sending information to the dataspace. This data can tell you (and the smart librarian AI) what’s happening in the real world, in real-time. So, the dataspace not only stores this information but also helps make sense of it, allowing you to control these devices better or get insights into your daily activities and environment.

The Connection

The magic happens when AI and IoT work together within the dataspace. AI uses the vast amount of data generated by IoT devices to learn patterns, make predictions, and automate tasks. For instance, an AI might analyze the data from smart home devices to optimize energy use, making your home more comfortable while saving on electricity bills.

In layman’s terms, the dataspace is the backbone that supports AI and IoT by organizing and storing all the data they need and produce. It’s like the brain and memory for these technologies, enabling them to work smarter and make our lives easier and more connected.

GPS on the 5G mobile that talks

Imagine 5G mobile communication as the super-fast express delivery service for the digital world, significantly impacting how data is moved, accessed, and utilized within the dataspace. Here’s how 5G plays a pivotal role:

Speed and Bandwidth

5G offers incredibly fast data speeds and more bandwidth compared to its predecessors. This means that information can travel back and forth between devices, servers, and the internet much quicker. In the context of a dataspace, which relies on the timely and efficient exchange of data, 5G ensures that even the most data-intensive tasks are completed smoothly and swiftly. This is akin to upgrading from a bicycle courier to a fleet of high-speed delivery drones for your data.

Reduced Latency

Latency refers to the delay before a transfer of data begins following an instruction for its transfer. 5G dramatically reduces this delay, making real-time data exchange and processing a reality. For applications within the dataspace that require instant response times, such as autonomous driving or real-time analytics for financial trading, 5G’s low latency is a game-changer. It’s like having a conversation with someone in real-time, without those awkward pauses that can disrupt the flow.

Enhanced Connectivity

5G technology supports a higher number of connected devices per unit area than 4G. This capability is crucial in densely populated areas or in scenarios where many IoT devices are deployed, such as smart cities or industrial complexes. Within a dataspace, this means more devices can contribute data and insights without the network becoming congested or unreliable. Imagine a crowded concert where everyone can stream videos without buffering; that’s what 5G offers to the dataspace.

Enabling New Technologies and Applications

The combination of high speed, low latency, and enhanced connectivity allows for the development and deployment of new technologies and applications. For example, augmented reality (AR) and virtual reality (VR), which require the quick processing of massive amounts of data, become more viable and widespread with 5G. In the dataspace, this translates to more immersive and interactive experiences, whether for entertainment, education, or professional training.

Facilitating AI and IoT Integration

5G’s capabilities boost the efficiency and effectiveness of AI and IoT within the dataspace. AI applications can process data collected from IoT devices more quickly, leading to faster insights and actions. This could mean smarter cities that adapt traffic lights in real-time to reduce congestion or manufacturing plants that predict equipment failures before they occur, minimizing downtime.

In layman’s terms, 5G acts as the high-speed highway that connects different parts of the dataspace, ensuring data flows quickly, reliably, and efficiently. This not only enhances the performance of current technologies but also opens up possibilities for new innovations that can transform our lives and work.

To watch ” JOM! lets Sembang AIoT” brought to y by AIoTmission check at the link below:

How AI used to detect Parking Space

How to AI is used in Detecting Parking space

During the recent “Sembang AIoT Episode 34” on January 26, organized by AIoTmission and Axiomtek, we explored the expanded applications of AIoT in the realm of Smart Parking.

The session commenced with an overview of the AI4S program and starter kit, showcasing its utilization in one of the Digital Transformation and Smart Manufacturing initiatives hosted by MPC, Intel, and MIDA.

A comprehensive explanation of the Axiomtek AI Suite (AIS) followed, delving into its functionalities and objectives in generating AI models deployable in production processes. The emphasis was on reducing manpower in specific processes and enhancing overall operational efficiency.


Productive through digitalization
Axiomtek AIS

Axiomtek Industrial AI suite was used as a teaching hands on kit in the program. The AI4S program (also known as Artificial
Intelligence for SMEs), is an Artificial
Intelligence (AI) based machine vision system. It is a three-way partnership, among Malaysia Productivity Corporation (MPC), Malaysian Investment Development Authority (MIDA) and Intel Malaysia. This booklet is a compilation of end-users’ Proof-of-Concepts (PoCs) projects as a result of the experiential training provided to the participants

The Axiomtek AI starter kit is a completed starter kit featuring a high-performance
Intel¬ģ Core‚ĄĘ-based AI edge platform on standard Tower based industrial PC system¬† with high-computing
GPU/VPU support, a high-resolution camera, and built-in Axiomtek AI suite (AIS)
based on Tensorflow Framework, Intel¬ģ Edge Software Hub for Industrial and
Intel¬ģ OpenVINO‚ĄĘ. This application-ready package enables users or manufacturers to
ease the development of vision applications within automation. The hardware
platform, IPC-AIS-524, is a 7 slots industrial system with LGA1151 socket
9th gen Intel¬ģ Core‚ĄĘ i7¬† processor. It comes with front-access I/O and adequate PCIe and PCI Slots. The Axiomtek AI Suite (AIS) is based on
Intel¬ģ Edge Software Hub for Industrial to implement from deep-learning training
to inference. It comes with web apps design and intuitive user interfaces,
helping the users deploy AI without coding.

Smart parking with Vision AI - The parking Space Detection

Demonstration of smart parking with vision AI

There are several models suitable for Parking space detection:- 

Convolutional Neural Networks (CNNs): CNNs are particularly effective for image recognition tasks, making them suitable for parking space detection in smart parking systems. They can analyze images or video feeds from cameras placed in parking areas to identify and classify available and occupied parking spaces.

YOLO (You Only Look Once): YOLO is a real-time object detection system that could be employed for smart parking applications. YOLO can quickly process images and accurately detect and locate multiple objects, including vehicles in parking spaces, in a single pass.

Faster R-CNN (Region-based Convolutional Neural Network): Faster R-CNN is another popular choice for object detection tasks. It’s known for its accuracy and ability to precisely locate objects within an image. This model could be adapted for identifying and monitoring parking spaces in real-time.

Benefits of Smart Parking using AI:

Optimized Parking Management: AI-powered smart parking solutions enhance parking management by providing real-time information about parking space availability. This helps drivers find parking spots quickly, reducing traffic congestion and fuel consumption.

Reduced Traffic and Emissions: Efficient parking space detection contributes to the overall reduction of traffic congestion as drivers spend less time searching for parking. This, in turn, leads to a decrease in vehicle emissions, promoting a more environmentally friendly and sustainable urban environment.

Improved City Planning: The data collected from smart parking systems can be analyzed to gain insights into parking patterns, peak usage times, and demand trends. City planners can use this information to make informed decisions about urban infrastructure, optimize parking layouts, and create more efficient transportation systems within smart cities.

A Live demo on the AI parking Space detection was performed with one of the AIoT appliances with deep learning AI model detecting the parking space with vehicle counting capability. 

To watch us in the live session:-

Applying AIoT in Smart Parking

Smart Parking for Smart City with AIoT

sembang AIOT smart transport IPC

The “Sembang AIoT” Episod 33 was held on 19th of Jan 2024. The main topic was still Smart City covering Smart Parking with AI and industrial IoT. We started this with one of the Smart Transport embedded system introductions, The Axiomtek TBox810, it is a en50155 certified Industrial PC system that allows the users to run this on a moving vehicles or Trains.

If you’re involved in transportation-related projects or applications, consider exploring the Axiomtek TBOX series. This series boasts numerous certifications, making it suitable for railway train applications. Key certifications include En50155, En 45545-2, Iso7637-2, E-Mark (E13 / E24), IEC609045, DNV2.4, among others.

These TBOX units are particularly effective for various smart transport applications. They can be used for graphical display systems at train stations or on trains, Internet of Things (IoT) implementations on trains, and Vision AI analytics systems onboard.

In our recent presentation, we highlighted the Tbox810, a low-power option from this series. It is an Intel Atom-based, low-power embedded system, ideal for adding to Mass Rapid Transit (MRT) or Light Rail Transit (LRT) for onboard IoT monitoring applications.

Cloud based integrated IIOT EDGE Gateway that drives the Smart Parking Display

We shared some case studies on Smart parking within building like those installed at the Mall parking area, where the incoming cars can be diverted to some areas with more parking space by indicators. although this is not a new thing the impact is good in the sense of avoiding congestion and regulating traffic within the parking area.  The other set of LPR ( license Plate recognition) is used in some of the malls that provide license plate recognition and parking fee collection. This application seems to be smooth running and it should come to the maturity state.   

We demonstrate the counting of the incoming vehicle entering and exit the parking space where the balance parking space is projected at the Dot matrix Display panel.  For IoT sake, we included the AIOT Edge Connect Cloud capability where the tracking data of all the counts can be seen at the cloud level.  The communication to and from the cloud is made possible where you can even publish those data directly to the display panel from the Remote. 

AI based Camera is used in this case to provide the object and LPR ( License plate recognition) but in this demo, we merely do the object detection where the incoming and outgoing cars are being counted. 


Cloud based Smart parking Display

The AIoT appliances used is the AEC100 Edge Gateway where it provides the following functions in this application:-

  • Vehicle counting via AI camera
  • counting via loop detector ( optional)
  • linking to Dot Matrix Display¬†¬†
  • AIOT Edge Connect¬† to Cloud enabled over MQTT¬†
  • Web API Data Host for interaction with local system or further integration.¬†


‚ÄúDemonstration of remote Tablet connected to Cloud for direction interaction of the Smart Parking Display panel‚ÄĚ

Watch this session live with the link below and remember to subscribe for the extension of the Smart parking next week.


Integrating Smart Traffic Technologies in Cities

Smart Traffic with AIoT for Smart Cities

Driving smart city with smart traffic

In the latest episode (32) of “Sembang AIoT,” we had the privilege of welcoming Professor Dr. LIM K.C from UTEM Melaka, an expert in Smart Traffic systems for smart cities. He shared his extensive knowledge and insights on the evolution and intricacies of developing efficient Smart Traffic systems.

The session began with a reflection on our early experiences with Malaysia’s traffic light system, both as pedestrians at crosswalks and as drivers at traffic junctions. This led to various discussions about how technology is fundamentally transforming the design and operation of traffic systems.

Additionally, we had a segment on product and solution sharing. This time, we highlighted the PT805, a compact yet impressive panel PC system. This device boasts a 5.5-inch wide screen LCD display, enhanced with an IPS PCAP touchscreen for superior visual quality. Its unique features include optional additions for RFID and NFC, expanding its utility in interactive applications like payment systems. Moreover, the PT805 can be used in both landscape and portrait modes and is compatible with Windows or Linux operating systems.

Widescreen 5.5" penel pc
  • ¬†

Some unique feature of PT805 Mini panel PC system:

5.5″ LCD display¬† with¬†Stunning IPS PCAP touchscreen

Add-on option: NFC, RFID with Landscape and portrait orientation

LCD Panel¬†Display Size: 5.5″

Brightness: 400 nits

Resolution: 720 x 1280

Viewing Angle (Up/Down/Left/Right): 80¬į/80¬į/80¬į/80¬į

CPU¬†Intel¬ģ Celeron¬ģ processor N3350 (Apollo Lake), 1.10 GHz


In the realm of traffic control, a key focus area for traffic management teams is the integration of IoT and AI sensors at traffic junctions to enhance operational intelligence. However, in Western countries, there‚Äôs a trend of reducing the number of sensors at these junctions due to high maintenance costs. Instead, the latest innovation involves equipping vehicles with necessary sensors that connect to a central system via 4G/5G networks, which are now fully operational. This approach of gathering data and uploading it to the cloud is seen as more efficient for managing traffic flow. This advancement leads to the emergence of ‚ÄúV2X‚ÄĚ technology, standing for ‚ÄúVehicle to Everything,‚ÄĚ which represents a significant shift in how traffic systems interact with vehicles and their environment. That is also one of the Sustainability factors that this ‚ÄĚ V2X‚ÄĚ is able bring about in the building of the Smart City.¬†

Thirty years ago, the scarcity of IoT sensors at traffic junctions limited our confidence in most traffic systems. However, today, we have an abundance of these sensors. Additionally, the emergence of 5G communication technology has made real-time data transfer from devices to the cloud a reality. This connectivity enables vehicles to link up with central big data systems, which is invaluable for traffic system planning.

Addressing the issue of traffic congestion, the utilization of a central data repository is key. By pooling all traffic-related data in one place, this information can be used for AI to suggest the  plan of  future infrastructure developments, such as highways, public transportation routes, and the location of new townships or commercial centers.



Driving Smart Urban Transformation and AIoT

AIOT for Smart City

Can AI and IoT Propel Smart Urban Transformation? Absolutely! In our very session 2024 live Sembang AIoT session, we delved deeply into this fascinating topic.

The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) in driving smart urban transformation is a multifaceted process that can revolutionize how cities function, enhancing efficiency, sustainability, and quality of life. Here are some key applications:

Smart Traffic Management: AI can analyze data from IoT sensors placed throughout the city to optimize traffic flow, reduce congestion, and improve road safety. This includes smart traffic lights, real-time traffic updates, and predictive analytics for traffic patterns.

Waste Management: Smart bins equipped with IoT sensors can notify collection services when they are full, optimizing waste collection routes and schedules. AI algorithms can also analyze waste patterns to improve recycling and reduce landfill usage.

Energy Management: AIoT can be crucial in managing energy consumption in urban areas. IoT sensors can monitor energy usage across the city, while AI can analyze this data to optimize energy distribution, reduce waste, and integrate renewable energy sources more effectively.

Water Resource Management: IoT sensors can detect leaks, monitor water quality, and manage water usage in real-time. AI can predict water demand, optimize water distribution, and ensure sustainable water management practices.

Public Safety and Security: AI-enhanced surveillance systems can analyze footage from IoT-connected cameras in real-time, helping to detect and prevent crime. AI can also analyze data from various sensors to improve emergency response times and disaster management strategies.

Healthcare Services: In smart cities, IoT devices can monitor public health trends and environmental factors that affect health. AI can analyze this data to predict outbreaks, manage hospital resources, and personalize healthcare.

Environmental Monitoring: AIoT can monitor air quality, noise levels, and other environmental parameters, providing data to make informed decisions about urban planning and public health initiatives.

Infrastructure Maintenance: IoT sensors can monitor the condition of roads, bridges, and buildings, with AI analyzing this data to predict when maintenance is needed, thus preventing costly repairs and enhancing public safety.

Smart Parking: IoT sensors can provide real-time information on parking availability, while AI algorithms can analyze patterns to improve parking management and reduce congestion caused by drivers searching for parking spaces.

Enhanced Citizen Engagement: AI can analyze data from IoT devices and social media to gauge public opinion and needs, leading to more responsive and citizen-centric urban governance.


In summary, the application of AI and IoT in smart urban transformation involves leveraging these technologies to collect and analyze vast amounts of data from various city operations. This enables more informed decision-making, leading to efficient, sustainable, and improved urban living experiences.

AIOT people counting

People tracking and counting with Vision AI is one of the example to continuously monitor or provide surveillance with anomaly detection on sudden crowd, density of people per location and activity movement of people. That covers the safety and the healthy living part of it.

Using IoT and AI for traffic monitoring in city parking areas is a prime example of their application. By tracking vehicle occupancy in parking spaces, we can offer real-time information about available spots to drivers. This approach not only guides traffic efficiently to the appropriate locations but also helps in reducing waiting times and lowering carbon emissions.

CAR park tracking with AIOT
Vehicle counting with AIOT
counting car with Vision AI

In the Live demo that we showed in the live session, We demonstrated how Axiomtek AIoT appliance where it  is able to provide the numbers counted by the AI model for the passing by vehicle. The above snap shot shows the passing vehicle with the indicator 49 ( in the first picture) and increase to 50 after the vehicle has passed.  

Watch us in youtube:-

Throwback AIoT 2023

AIOT Throwback 2023

throwback AIOT 2023

Time flies ! We are the end of 2023.

As we bid farewell to another remarkable year, we want to extend our deepest gratitude to all our cherished followers and esteemed partners and customers. Your unwavering support and trust have been the cornerstone of our journey, lighting our path towards countless achievements and shared successes.

As we step into this New Year, filled with hope and new possibilities, we look forward to continuing this incredible journey with you. May this year bring you abundant joy, prosperity, and success in all your endeavors.

Thank you for being an integral part of our story. Here’s to a fantastic year ahead!

It is such a coincidence that the last session of the ” Jom ! lets sembang AIOT live fall on the very last moment of the year 2023 and It is a full 30th session.¬†

During the session, we recalled the very first session that we had, which was on the 24th of May, yes it was 7 months ago. A big round of applause to CC Lee and Kien Leong to stay committed to this live session and we have not missed any of them. 

The setup and recording of the first and second sessions wasn’t that clear on the video due to the resolution and in the second session, the video was streamed with our face and lettering mirrored. That was how we started. Despite some challenges to host this, our team learned fast and we managed to get this up and running till today.¬† Good job! Team.

We started the sharing with a very interesting talk about AI Machine learning with one of the tiny KIWI310 embedded board.  A vibration sensor with Modbus RTU was taken as a data source for Anomaly detection using Machine Learning AI.  

Axiomtek Kiwi board Rasberry PIE formfactor

Kiwi 310 1.8″ embedded board is tiny but he can hold good responsibility in performing the Anomaly ML AI function¬†

AIS ( AI Suite) powered by Intel OpenVino is always our preference in working on most of the Vision AI modeling.

IIOT OEE and AI suite

AIOT and SCADA Training


Not forgetting AIOT Training and IIOT SCADA Training with our partners and customers.

Many of our customers do not know that one of our as competent in the SCADA solutions. Our main team members in the team added 50 years of experience in supporting and integrating SCADA projects. We are currently carrying three main SCADA software packages namely, TeslaSCada, Adisra SmartView SCADA, and Indusoft Web Studio or AVevaEdge. 

One of the training sessions involves the highest end requirement with SCADA Redundancy where 2 SCADA servers running at the same time with HOT Standby.  

Watch us live and don’t forget to subscribe to our Live channel as we have more to share in 2024 .. and happy new year.¬†




Fundamental of Digital IO and Power saving in 4G router iiot gateway

JOM! Lets Sembang AIoT episod 29

sembang AIOT episod 29

During the live session of Sembang AIoT 29, we discussed the application of Digital IO in Industrial IoT and presented power-saving solutions for remote data collection using cloud-based 4G routers.

Digital IO systems represent a fundamental requirement in virtually all industrial IoT applications. Whether you need to monitor switch status, equipment status, count occurrences, measure frequencies, or control lighting, Digital Input and Output play a crucial role.


There are two primary categories of Digital Inputs:

TTL Input (0-5VDC):

TTL inputs are typically non-isolated and are suitable for internal detection systems where external interference is not a concern.

Isolated Digital Input (Wider Voltage Input):

Isolated inputs are predominantly used in industrial systems where isolating the connected equipment is essential to ensure resistance to external surges or signal noise.


In an IoT system, Digital Outputs are similar to Digital Inputs but can be categorized into three types:

TTL Output (0-5VDC)

Isolated Output

Relay Output (Isolated Electromechanical Outputs)

digital IO in IIOT application
digtal ouput in IIOT

Axiomtek IIoT edge gateway provides a 8 GPIO ( General Purpose IO) with TTL DIO where it can be configured to inputs or outputs. The standard is 4 DI and 4 DO. It is good enough for some simple requirement to detect some local alarm or status inputs and also to trigger Siren or indicators for local  notification. We have made this gateway to equip with a signal conditional where all the TTL inputs and outputs is converted on a daughter board electronically to provide isolation input that required by the industries and also the Relay output that will be ready to connect to any of the indicators and Siren output. 

4G gateway router with power saving

4G or LTE technology is widely employed in numerous remote data acquisition systems. However, in certain remote areas, a stable power source may not be readily available. In such cases, solar energy paired with batteries often emerges as the most viable solution.


The AEC300 and AEC310 4G IIOT routers come equipped with Cloud capabilities, including MQTT and Web API integration. Among their impressive features is power-saving functionality, allowing them to enter sleep mode with a customizable wake-up interval.


When the module is in sleep mode, it consumes approximately 100-120mA, but upon awakening, the power consumption increases to around 230-300mA. This remarkable feature results in nearly a 50% reduction in power consumption. By implementing this capability, the power requirements are significantly lowered, which, in turn, simplifies the sizing of solar panels and batteries for practical deployment.


You can access the recorded live session via the link below, and please consider subscribing to our channel if you find the information beneficial.


Do watch and subscribe our youtube channel if you you find this relevant.



Empowering ESG with AIoT

Sembang AIoT -IIoT and ESG

non intrusive data extraction with AIOT

We have just come back from the Malaysia IoT association event on the empowering ESG with IoT.  There is an open discussion in the event with the panelists like Dr. Ong Kian Ming, the ex Deputy Minister of international of trade,  Mr. Steven Lim the president of ESG Malaysia and others.  It was an informative session where ESG was touched at at a deeper level for the industries and how IoT can played the role in providing data that contribute to the framework of compliance of ESG for the companies.

ESG stands for Environmental, Social, and Governance, and it refers to a set of criteria used to evaluate a company’s performance in these three key areas. ESG has become an important framework for investors, businesses, and other stakeholders interested in assessing the sustainability and ethical impact of an organization.

1. Environmental (E): This aspect assesses a company’s impact on the environment and how it manages environmental risks. It includes considerations such as the company’s carbon footprint, energy efficiency, waste management, use of natural resources, and adherence to environmental regulations.

2. Social (S): The social component evaluates a company’s relationships with its employees, communities, customers, and other stakeholders. Social factors encompass issues like labor practices, diversity and inclusion, employee relations, community engagement, and the overall impact on society.

3. Governance (G): Governance focuses on the structure and effectiveness of a company’s leadership, management practices, and internal controls. Key governance factors include board composition, executive compensation, shareholder rights, transparency, and ethical business practices.

Investors and financial institutions increasingly consider ESG factors in their decision-making processes. Companies that perform well in ESG criteria are often viewed as more sustainable, responsible, and better positioned for long-term success. ESG considerations are not only driven by ethical concerns but also by the recognition that companies with strong ESG practices may be better positioned to manage risks, attract capital, and build positive relationships with stakeholders.

The integration of ESG principles has gained momentum globally, and various reporting standards and frameworks, such as the Global Reporting Initiative (GRI), Sustainability Accounting Standards Board (SASB), and Task Force on Climate-related Financial Disclosures (TCFD), provide guidelines for companies to disclose relevant ESG information in a standardized manner.

In the event, we took part in presenting Non intrusive Data Extraction with AI where as far as data collection is concern, this AIoT non-intrusive connect solutions from us can be fully utilized to obtain the data we want with least effort when it was assisted with the AI.

Malaysia IoT association ESG -IOT event

Two demos was presented :

1.  Analogue gauge reading via AI 

2. process display and indicators reading with Vision AI

Demonstration by Kien Leong during the event. 

After data extraction, data can be published to cloud and link to the local SCADA system. 

Malaysia IoT association ESG -IOT event

During the live session, Mr. CC Lee talk about the building block of developing the Remote Terminal units. The system components in term of hard and software necessary in the building of RTU was shared. One of the Axiomtek ICO platform was selected as a development platform of the RTU because, it has almost all features required by the RTU.  

A Remote Terminal Unit (RTU) is a specialized device used in industrial control systems to monitor and manage remote equipment. It plays a crucial role in supervisory control and data acquisition (SCADA) systems, which are used in various industries such as manufacturing, energy, water treatment, and more.

Key features of an RTU include:

1. Remote Monitoring: RTUs are placed in remote locations to monitor and collect data from sensors and devices. These sensors could measure parameters like temperature, pressure, flow rates, voltage, or other relevant data depending on the application.

2. Data Acquisition: RTUs are equipped with input channels to collect analog and digital data from field devices. They convert this data into a digital format for transmission and processing.

3. Control Functions: In addition to monitoring, some RTUs also have control capabilities. They can send commands to remote devices, such as turning equipment on or off, adjusting settings, or executing specific actions based on the data they receive.

4. Communication: RTUs communicate with a central control system or a master station, usually located at a central facility. Common communication protocols include Modbus, DNP3 (Distributed Network Protocol), and others, depending on the industry standards and requirements.

5. Real-time Operation: RTUs are designed to operate in real-time, ensuring timely and accurate data acquisition and control.

6. Reliability and Environmental Resistance: Since RTUs are often deployed in harsh environments, they are designed to be robust and resistant to environmental factors such as extreme temperatures, humidity, and vibrations.

RTUs are a crucial component in the automation and control of processes in industries where remote monitoring and control are essential. They enable efficient management of distributed systems by providing a link between field devices and the central control system, allowing operators to make informed decisions and respond to changes in the environment or process.

As you can see, the RTU still stay a valid and important equipment in the process control especially at the remote area. In the sembang AIoT live session, we shared the building block of RTU, How Axiomtek’s ICO hardware+ IIoT software tools can be used to build a reliable RTU system that serve the industry. 

AIOT non intrusive connect

Extracting data from a process plant poses significant challenges. The process involves substantial efforts, including the addition of extra components, sensor readjustments, configuration changes, and rewiring accompanied by commissioning tests. This not only incurs considerable work and costs but also results in substantial downtime.

In response to these challenges, we showcased a non-intrusive data extraction demonstration. This innovative approach involves extracting data from process displays without the need for additional hardware adjustments. The extracted data is seamlessly shared through a SCADA interface, providing real-time visibility on a Ruggedized tablet.

Subscribe and watch us live in the next coming session on ” JOM ! Let’s sembang AIOT” with the link below:-





Industrial Transformation with AIoT

Intel Meteor Lake featuring AI Edge solution

Industrial Transformation with AIoTmission

The “Sembang AIoT” live session commenced by introducing the AIoT Edge Connect Cloud platform, catering to users seeking visualization and management of their data on the cloud. Emphasis was placed on the significance of addressing numerous Programmable Logic Controllers (PLCs) on shop floors, where crucial data from machines, instruments, and equipment plays a pivotal role in ensuring seamless process execution. The session highlighted the importance of visualizing data through dashboards, receiving alerts for process deviations, and establishing data historians for future optimization using Machine Learning (ML) and Artificial Intelligence (AI) techniques.

The presentation featured two prominent gateway solutions: the Axiomtek IIoT edge gateway AEC100 and the 4G mobile router gateway AEC310. Both solutions were lauded for their effectiveness in managing diverse data types and models of PLCs, considering the varying PLC brands present in different machines. Notable examples included Siemens PLCs, Omron PLCs, Allen Bradley PLCs, Mitsubishi PLCs, and Panasonics PLCs, each employing different communication protocols. The Axiomtek AEC100, equipped with the IIoT software tool, was highlighted for its configurability to request essential data from the diverse range of PLCs mentioned.

PLC data to Cloud
AMR development package

One of the main focus item being demonstrated is the¬†AMR¬†in a prototype form. It is powered by the CAPA55R- 11th gen I5 intel processor on a 3.5″ form factor. Equipped with Intel Realsense 3D cameras, LiDAR as main sensors in this unit is sufficient for us to highlight some features from the Axiomtek Builder support Packages.

Vision AI Anomaly detection system

AIoTmission Anomaly AI detection demonstrates the Power of built-in Graphics that allow OpenVino ( Intel AI inferencing tool)  to perform an efficient Vision AI. 

AMR builder support package

The AMR building process presents several challenges, with accuracy standing out as a primary concern. Precision is intricately tied to the design of sensors and nodes within the ROS 2 platform. Axiomtek addresses this issue through the AMR Builder support package, which rigorously tests and evaluates suitable sensors. A comprehensive sensor list is published in the sensor kit module. The accompanying software package, integrated with the Digihub module, provides finely tuned nodes, facilitating rapid development. This significantly reduces development time, making it an ideal solution for those seeking to construct customized AMRs for diverse industrial applications.

The event brought forth two significant announcements in the realm of AI. Firstly, the introduction of the latest Intel processors marked a departure from the conventional 15th generation nomenclature, now rebranded as Core Ultra. Secondly, the unveiling of the Intel ARC GPU was a notable highlight, categorized into 3 series‚ÄĒ3, 5, and 7‚ÄĒeach offering distinct performance levels. Notably, the A770 stands out as one of the highest-end models in the lineup.


For an in-depth exploration of these developments, join us in a 40-minute live sharing session.