Unlocking the Power of AI in Industrial IoT
Table of Contents
- Introduction to IOT Industrial
- The Concept of Industrial IOT
- What is Industrial IOT?
- Collecting and Storing Data
- Big Data Analytics
- Improving Decision Making with Analytics and AI
- The Move Towards Distributed AI
- The Power of AI on Edge Devices
- The Complexity of Distributed AI
- Introducing AI Core X Module
- Industrial Gateways and AI Core X Integration
- Optimizing Edge Devices with Intel Open VINO Toolkit
- Introduction to Intel Open VINO Toolkit
- Leveraging Edge Device Power with AI applications
- Simplifying AI Application Development
- Deep Learning Optimization for Intel Architecture
- Managing Complexity with Containerization
- Introducing Containers
- Exploring Docker Technology
- Streamlining Application Management with Balena
- Demonstrating AI and IOT Technology
- AI and IOT Demos at Bootcamp
- Autonomous Robot Demo
- AI-powered Drone Demo
- Wireless Sensor Demo with IQRF Technology
- Conclusion
- FAQ
Introduction to IOT Industrial
In this article, we will explore the fascinating world of Industrial Internet of Things (IOT) and the advancements made in the field. We will dive into the concept of Industrial IOT, the role of big data analytics and AI in improving decision-making, and the shift towards distributed AI. Furthermore, we will discover the power of AI on edge devices and how Intel's Open VINO toolkit optimizes these devices. We will also look into containerization and its role in managing complexity in the IOT industry. Lastly, we will showcase some AI and IOT demos that highlight the capabilities of these technologies. So, let's embark on this journey and unravel the potential of IOT Industrial.
The Concept of Industrial IOT
What is Industrial IOT?
Industrial IOT refers to the integration of internet-connected devices and systems in the industrial sector. It encompasses the use of sensors, machines, and other devices to collect data and enable intelligent decision-making in industrial processes. Industrial IOT aims to enhance productivity, efficiency, and safety in various sectors such as manufacturing, energy, transportation, and more. Exploring various Industrial IoT use cases demonstrates how businesses leverage connected devices and data-driven insights to optimize operations, reduce downtime, and drive innovation across industries.
Collecting and Storing Data
At the heart of Industrial IOT lies the collection and storage of data. Internet-connected devices and sensors gather data from various sources, such as machines, production lines, and environmental sensors. This data is crucial for monitoring operations, identifying patterns, and predicting potential issues. By storing this data, industrial companies can leverage it for analysis and decision-making.
Big Data Analytics
Big data analytics plays a vital role in Industrial IOT. It involves processing and analyzing large volumes of data to extract valuable insights and actionable information. By applying analytics techniques to the collected data, companies can identify trends, detect anomalies, and optimize operational processes. Big data analytics enables data-driven decision-making, leading to improved efficiency and productivity.
Improving Decision Making with Analytics and AI
The convergence of Industrial IOT and analytics has revolutionized the decision-making process. By analyzing data collected from IOT devices, companies can make informed decisions that improve efficiency, reduce costs, and enhance safety. However, as the volume of data increases, traditional analytics approaches may fall short in addressing all possible scenarios. This is where Artificial Intelligence (AI) comes into play.
The Move Towards Distributed AI
To overcome the limitations of traditional analytics, the industry is now shifting towards distributed AI systems. Instead of relying solely on cloud-based AI services, the decision-making process is being decentralized and moved closer to the edge devices. This approach empowers edge devices to process and analyze data in real-time, reducing latency, enhancing security, and improving scalability.
The Power of AI on Edge Devices
The Complexity of Distributed AI
The transition to distributed AI introduces complexity to edge devices. These devices, such as industrial gateways, feature multiple processing units, including CPUs, GPUs, and even FPGAs. Each unit has its own strengths and is capable of running AI inference applications. The challenge lies in efficiently utilizing the available resources and optimizing the workload to take full advantage of the computational power of edge devices.
Introducing AI Core X Module
To leverage the power of AI on edge devices, AI Core X module comes into play. This module, based on Intel technology, enables edge devices to efficiently run low-power AI inference applications. It offloads the main system from running inference, allowing it to focus on other applications simultaneously. The AI Core X module eliminates the need for expensive and power-hungry solutions, making AI accessible on edge devices.
Industrial Gateways and AI Core X Integration
Industrial gateways, equipped with Intel Atom processors and AI Core X modules, serve as the backbone of distributed AI systems. These gateways, certified with red certification in Europe, provide a range of wireless connectivity options and powerful computing capabilities. With compatibility for existing software provided by Intel, these gateways offer seamless integration of AI technologies and enable efficient edge computing.
Optimizing Edge Devices with Intel Open VINO Toolkit
Introduction to Intel Open VINO Toolkit
The Intel Open VINO toolkit is a powerful software development tool designed to optimize AI applications on edge devices. It allows developers to take advantage of the computational power of CPUs, GPUs, VPUs, and FPGAs without requiring expertise in each specific processing unit. With the ability to run pre-optimized CNN models, developers can easily develop and deploy AI applications on edge devices.
Leveraging Edge Device Power with AI Applications
The Open VINO toolkit enables developers to leverage the full power of edge devices for AI applications. It simplifies the development process by providing a common API for different processing units, ensuring seamless integration. Developers can run face detection algorithms on CPUs, while visual recognition and analysis tasks can be offloaded to VPUs. The toolkit maximizes the computational capabilities of edge devices, unlocking their full potential.
Simplifying AI Application Development
Developing AI applications for edge devices can be complex, considering the diverse processing units available. However, with the Open VINO toolkit, developers can develop generic AI applications without the need for expertise in individual processing units. The toolkit's pre-optimized CNN models for Intel Architecture ensure efficient execution across all available processing units, making AI application development more accessible and intuitive.
Deep Learning Optimization for Intel Architecture
The Open VINO toolkit's support for Intel Architecture optimizes deep learning workloads on edge devices. Developers can benefit from the exceptional performance of CPUs, GPUs, and VPUs, ensuring efficient execution of AI models. With Intel's commitment to continuous improvement and advancements in AI technologies, the Open VINO toolkit remains at the forefront of edge computing optimization.
Managing Complexity with Containerization
Introducing Containers
Containerization is a technology that simplifies the management of complex applications in the IOT industry. Similar to virtual machines, containers provide isolation for applications, allowing them to coexist on the same system without interference. This modularity enables developers to create and manage separate applications for different purposes, streamlining the deployment and maintenance process.
Exploring Docker Technology
Docker is one of the most widely-known containerization technologies used in the IOT industry. It enables developers to isolate and manage applications efficiently, simplifying the deployment process. Docker containers can be easily deployed across multiple devices, ensuring consistency and reliability. It provides a flexible and scalable solution that enhances the management of IOT applications.
Streamlining Application Management with Balena
To effectively manage fleets of IOT applications, Balena offers a cloud-based solution based on containerization technology. Balena Cloud helps developers deploy, develop, and maintain a multitude of IOT applications remotely. With an intuitive dashboard, developers can easily monitor, update, and configure multiple applications simultaneously. Balena Cloud supports a wide range of devices, including Intel-based gateways, making it a comprehensive solution for IOT application management.
Demonstrating AI and IOT Technology
To showcase the capabilities of AI and IOT technology, several demonstrations have been prepared. These demos highlight the practical applications and versatility of these technologies.
Autonomous Robot Demo
One of the demos features an autonomous robot built using App Square AI Edge Gateway, Intel Realsense technology, and AI Core X. This robot can navigate its environment, map areas, interact with people, and avoid obstacles. It utilizes AI algorithms for object detection and person recognition. The autonomous capabilities of this robot demonstrate the potential of AI on edge devices and its impact on industrial processes.
AI-powered Drone Demo
Another demonstration showcases a drone developed by HotArea, a software company, utilizing App Square and AI Core X. This drone uses AI algorithms to identify objects and can track and follow subjects based on captured images. The drone can trigger actions based on situations detected during its flight. This demo emphasizes the integration of AI and IOT technologies in creating smart and autonomous systems.
Wireless Sensor Demo with IQRF Technology
A third demo involves IQRF wireless technology and UP Square Gateway. The system utilizes wireless sensors to detect various parameters such as the number of people in a room and temperature. Based on this data, the system can automatically adjust temperature and lighting, optimizing energy consumption and usability. This demo showcases the potential of AI-powered systems in achieving efficient and personalized environments.
Conclusion
In conclusion, Industrial IOT, coupled with AI and advanced technologies, is shaping the future of industries worldwide. The integration of Industrial IOT devices, big data analytics, and AI enables data-driven decision-making, leading to improved efficiency and productivity. With the power of AI on edge devices and the optimization provided by Intel Open VINO toolkit, the complexity of distributed AI is managed effectively. Containerization further streamlines application management, making it easier to develop, deploy, and maintain IOT applications. The showcased demos illustrate the practical applications and potential of AI and IOT technology in various industries. As technology continues to evolve, embracing these innovations will unlock new possibilities and drive progress in the IOT Industrial landscape.
Highlights
- Industrial IOT combines internet-connected devices and systems in the industrial sector, enabling data-driven decision-making and improving efficiency.
- Big data analytics plays a crucial role in processing and analyzing large volumes of data collected from IOT devices.
- The integration of AI into the decision-making process enhances the ability to extract actionable insights from IOT data.
- Distributed AI brings decision-making capabilities closer to the edge devices, reducing latency, enhancing security, and improving scalability.
- The AI Core X module empowers edge devices to efficiently run AI inference applications without the need for costly upgrades.
- Intel's Open VINO toolkit optimizes AI applications on edge devices, allowing developers to leverage CPUs, GPUs, and VPUs without expertise in each unit.
- Containerization technology, such as Docker, simplifies the management of complex IOT applications by isolating them and ensuring consistency.
- Balena Cloud offers a cloud-based solution for managing fleets of IOT applications remotely.
- Demonstrations of AI and IOT technology showcase autonomous robots, AI-powered drones, and wireless sensor systems.
FAQ
Q: What processors are used in the Industrial Gateways?
A: The Industrial Gateways are equipped with Intel Atom X5 and X7 processors, offering powerful computing capabilities for edge devices.
Q: Can the gateways officially support FreeBSD?
A: The gateways do not have official support for FreeBSD, but there are community-supported projects that enable FreeBSD and OpenBSD on the platforms. Collaboration with customers is possible to provide specific support for certain projects.
Q: Is there a limit on the number of devices that can be managed with Balena Cloud?
A: Balena Cloud offers a free tier that supports up to 10 devices. For larger deployments, there are paid options available. Alternatively, the open-source server can be used to create a custom management system based on the same containerization technology.
