Integrating AI object detection with Manufacturing MES

Integrating AI object detection with Manufacturing MES

Highlights from the July 5th, 2024 Live Session: Integrating MES with Computer Vision AIDuring our live session on July 5th, 2024, we explored the critical integration of Manufacturing Execution Systems (MES) with computer vision AI. We highlighted AIOT AIS CONNECT as a leading computer vision solution, known for its flexibility in data exchange with external software through open protocols like Web API and MQTT.In the rapidly evolving landscape of manufacturing, the integration of advanced technologies is reshaping the industry. At the forefront of this transformation is the Manufacturing Execution System (MES), a pivotal tool that streamlines production processes and enhances efficiency. Coupled with AI-driven computer vision, MES is ushering in a new era of smart factories. Let's delve into the key functions of MES and explore why computer vision AI is so crucial in this context.Key Functions of MES: The Backbone of Modern ManufacturingProduction Scheduling:MES excels in planning and scheduling production processes, ensuring optimal use of resources and timely product...
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Pose Estimation AI application in Smart Factories

Pose Estimation AI application in Smart Factories

Pose estimation AI is like a super-smart computer program that can look at a picture or a video and figure out how a person or an object is positioned. Imagine it like this:Seeing People and Objects: The AI looks at an image or video and "sees" where people or objects are.Finding Key Points: It identifies key points, like the joints on a human body (shoulders, elbows, knees) or important parts of an object.Connecting the Dots: It connects these points to understand the overall pose or position. For a person, it would look like a stick figure showing how they're standing, sitting, or moving.It's like giving the computer eyes and a brain to understand and track how things are positioned and moving in a scene. This technology is used in things like video games, fitness apps, and even for improving safety in workplaces. During the Sembang AIOT live session this round we were sharing and discussed more about the Pose Estimation AI...
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5G RedCap and its impact on AI and IoT applications

5G RedCap and its impact on AI and IoT applications

5G RedCap Talk over " Sembang AIOT" In this session, We shared the subset of 5G which is designed for the IoT, the 5G RedCap. There are a few key areas touched on in this subject. Why 5G RedCap? Area of applications? and also the NB IOT (Narrowband IOT) vs 5G RedCap.5G Reduced Capability, or 5G RedCap, is a new subset of 5G technology introduced by the 3rd Generation Partnership Project (3GPP) in Release 17. Also known as 5G NR-Light, it is designed to cater to IoT applications that require a balance between performance and cost-effectiveness. This includes applications that do not need the full capabilities of traditional 5G, such as high bandwidth and ultra-low latency, but still benefit from faster data rates and improved efficiency compared to 4G and other LPWA (Low Power Wide Area) technologies.Origin and Development5G RedCap originated from the need to address use cases falling between the high-speed, high-capacity demands of enhanced Mobile Broadband (eMBB) and...
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On-premise LLM vs Cloud LLM

On-premise LLM vs Cloud LLM

AI and computing power have become highly dynamic, with applications spreading across various sectors and industries. It's a great time to discuss whether LLM servers or services should be on-premise or cloud-based. Let's dive into this topic on "Sembang AIoT"!An LLM, or Large Language Model, in AI is like a very advanced, super-smart robot that can read, understand, and write human language. Here’s a simpler way to explain it:Smart Robot Brain: Think of an LLM as a brainy robot that has read millions of books, articles, and websites. It has learned a lot about how people talk and write.Text Generation: This robot can help you write. If you give it a few words or a topic, it can create stories, essays, or even chat with you like a human would.Answering Questions: You can ask it questions about almost anything, and it will try to give you a helpful answer based on what it has learned.Translation: If you need to translate...
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From AI to Generative AI

From AI to Generative AI

The "SemBang AIoT" live session began with an introduction to Generative AI, followed by an in-depth exploration of computer vision. It highlighted how deep learning is becoming mainstream in AI, from which Generative AI has also emerged. In the session, Kien Leong shared some history about the Deep learning AI that drove the computer vision in the past and it is closely related to the ImageNet.  ImageNet is a large-scale visual database designed for use in visual object recognition research. It was created and maintained by researchers at Princeton University, Stanford University, and the University of North Carolina, Chapel Hill. Here are some key points about ImageNet:Scale and Scope: ImageNet contains more than 14 million images, each annotated with labels identifying the objects present. These images span over 20,000 categories, which are organized according to the WordNet hierarchy.Use in Competitions: ImageNet is famously known for the ImageNet Large Scale Visual Recognition Challenge (ILSVRC), an annual competition where research teams submit algorithms...
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Exploring Generative AI application in the industries

Exploring Generative AI application in the industries

24th of May 2024, "Sembang AIoT" open up a topic on generative AI on exploring Generative AI application in the industries. The primary focus of the whole live session is about the generative AI and the application of Generative AI in the industries. the session is hosted by Mr. CC Lee at technology trainer and speaker, along with Mr. Tan Kien Leong, the AIoT trainer and solution architect of AIoTmission.In the live session, an old piece of literature on microcomputer system design was referenced to discuss the role of math coprocessors like the Intel 8087 in handling complex calculations, such as multiplication and floating-point operations. Today, a similar reliance is seen in AI, which heavily depends on sophisticated computing, especially for handling floating-point operations. Most GPUs now come equipped with dedicated processors for this purpose. This underscores the importance of specialized processors in performing mathematical calculations, which are crucial for running many AI applications.  A reference design book that was used...
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Smart Supply Chain Management with AIoT

Smart Supply Chain Management with AIoT

The primary focus of the discussion was on smart supply chain management utilizing AI and IoT. This topic was presented by Mr. CC Lee, our technology trainer and technology public speaker, along with Mr. Tan Kien Leong, the AIoT trainer and solution architect from AIoTmission Sdn Bhd.The Fourth Industrial Revolution (IR4) brings numerous advanced technologies that can significantly enhance smart supply chain management. Key technologies include: Internet of Things (IoT): Smart Sensors: Enable real-time tracking of goods and assets, monitoring conditions like temperature and humidity. RFID Tags: Facilitate automated inventory management and asset tracking. Artificial Intelligence (AI) and Machine Learning (ML): Predictive Analytics: Improve demand forecasting and inventory management. Automated Decision-Making: Enhance supply chain efficiency by optimizing routes, scheduling, and resource allocation. Blockchain: Transparency and Traceability: Provide an immutable record of transactions, ensuring authenticity and reducing fraud. Smart Contracts: Automate and enforce contractual agreements without intermediaries. Big Data Analytics: Data Integration: Combine data from various sources for comprehensive insights. Trend...
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5G for Smart manufacturing

5G for Smart manufacturing

Welcome everyone to our "Sembang AIoT" live session, where today, on the 10th of May 2024, we delve into the dynamic realm of 5G infrastructure within the sphere of Smart Manufacturing. As the world continues its rapid march towards digitization, the integration of Artificial Intelligence and the Internet of Things (AIoT) into manufacturing processes has become not just a trend but a necessity for staying competitive in today's market. With 5G technology revolutionizing connectivity, the possibilities for enhancing efficiency, productivity, and agility in manufacturing are boundless. In this session, we will explore the transformative potential of 5G infrastructure, its applications, challenges, and the promising future it holds for the manufacturing landscape. So, let's embark on this journey together and uncover the intricacies of 5G in Smart Manufacturing! The picture above show how 5G is able to have its redundant path in avoiding signal breakage due to the obstable.While 5G technology is not an absolute necessity for Smart Manufacturing, its integration can...
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Industrial Robot for Smart Manufacturing

Industrial Robot for Smart Manufacturing

Industrial Robots for Smart Manufacturing Smart manufacturing integrates advanced technologies, including robotics, to optimize processes, improve efficiency, and enhance flexibility. Several types of robots are utilized in smart manufacturing to achieve these goals. Here are some key types:Industrial Robots: These robots are versatile and programmable machines used for various manufacturing tasks, such as welding, assembly, material handling, and packaging. They are equipped with sensors, vision systems, and sometimes AI algorithms to adapt to changing conditions and interact with other machines or humans.Collaborative Robots (Cobots): Cobots are designed to work alongside humans in a shared workspace safely. They typically feature advanced safety features and are used for tasks that require close collaboration between humans and machines, such as assembly, inspection, and testing.Mobile Robots: Mobile robots, including Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs), navigate autonomously within a manufacturing facility to transport materials, components, or finished products between different locations. They optimize logistics processes and increase flexibility in material handling.3D Printing...
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Understanding Data Security for Digital Transformation

Understanding Data Security for Digital Transformation

What are challenges in digital transformation in the building of smart manufacturing.The digital transformation in manufacturing brings numerous benefits, but it also presents significant challenges to data security. Here are some key challenges: Increased Attack Surface: As manufacturing processes become more interconnected through digital technologies like IoT devices, cloud computing, and automation systems, the attack surface for potential cyber threats expands. Each new endpoint or connection represents a potential entry point for attackers.Complexity of Systems: Modern manufacturing facilities often comprise a complex ecosystem of interconnected systems and devices, including legacy equipment that may not have been designed with security in mind. Managing the security of such a complex environment can be challenging.Data Protection: Manufacturing involves the collection and processing of sensitive data, including intellectual property, trade secrets, and personally identifiable information (PII). Ensuring the confidentiality, integrity, and availability of this data is crucial to protecting business interests and complying with regulations.Supply Chain Risks: Manufacturers often rely on extensive supply chains involving...
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