AIoT -The connected intelligence

FREE AIOT workshop for Fresh graduate

Lets start with the something really  ” Free”. 

In line with the Malaysian government’s talent development, AIoTmission Sdn Bhd  ( Axiomtek Malaysia training arm) thinks that this workshop can be an exciting Kickstarter in industrial AI and IoT where the participant can learn the industrial IoT application as well as how the Vision AI model is built. The main Aim of this AIoT workshop is to create better awareness of technology in the industry and if this understanding of the technology helps them to find a job that they want will be a great Bonus. 

Open from now till further announcement. 

Criteria for the free AIoT Workshop are as follows:- 

1. Must be of YouTube Subscriber

2. Those who are willing to learn more about AIoT in the industry. ( no specific background of studies)

3. Fresh Graduates that have not started for 3 months after graduation. 

Register yourself by scanning the QR code below:-

 

 

 

 

SCAN ME 

Free AIOT Workshop for Fresh Graduates in any discipline
( Half a day) 

LORA WIRELESS for IIOT Applications

In the realm of industrial IoT applications, wireless sensors play a pivotal role by offering an alternative to traditional wired data acquisition methods. They enable data collection in remote areas that are otherwise challenging to access.

During our live session, we introduce an innovative approach to connecting remote sensors using the LoRa wireless transceiver. In this scenario, the LoRa transceiver serves as a transparent wireless link between the IIoT edge gateway and remote sensors. With a frequency band of 864 to 922.5 MHz, LoRa offers superior penetration compared to the 2.4 GHz and 5.8 GHz frequencies. Its low-power radio technology can achieve reliable connections at distances of up to 1.5 kilometers with a clear line of sight. This makes it suitable for a wide range of indoor and outdoor applications, even in cases where the sensor is located on a higher floor, and the IIoT gateway is on a lower floor.

One limitation of this transmission method is the lower speed, with a maximum transmission rate of 10 Kbps. However, for most IIoT sensor data applications, this speed is more than sufficient.

Axiomtek IIoT Edge gateway hosting the data at the host area where the data is captured with the IIoT tool. The above picture showed 9869 is one of the value after being divided by 100 . it is at 98.69 Degree celcius. That is where the probe was burnt during that demo.

 

 

OPEN VINO The concept and Development

OpenVINO, short for Open Visual Inference and Neural Network Optimization, is an open-source toolkit developed by Intel for optimizing and deploying deep learning models on a variety of hardware platforms, including CPUs, GPUs, FPGAs (Field-Programmable Gate Arrays), and VPUs (Vision Processing Units). The primary goal of OpenVINO is to provide a unified framework that enables developers to accelerate and optimize their computer vision and deep learning applications for various Intel hardware platforms.

OpenVINO offers a range of tools and libraries that help streamline the deployment of neural networks for tasks like image recognition, object detection, and other computer vision tasks. It includes model optimization techniques to convert and adapt deep learning models to run efficiently on Intel hardware. This optimization is achieved through quantization, pruning, and other techniques to reduce the computational and memory requirements of models.

Key components of OpenVINO include the Model Optimizer for converting and optimizing models, the Inference Engine for running these models efficiently, and a set of pre-trained models for common computer vision tasks. It also supports popular deep learning frameworks such as TensorFlow, Caffe, and ONNX, making it easier for developers to bring their models into the OpenVINO framework.

OpenVINO is often used in applications such as video surveillance, robotics, autonomous vehicles, and more, where real-time, high-performance inference of deep learning models is required on Intel-based hardware platforms. It provides a bridge between deep learning research and practical deployment, especially for applications that require low latency and high throughput.

Process of computer vision AI

Steps by steps towards the building of AI model was explained in the session. OPen Vino still stay as a practical and reliable way in the building of many AI applications.  By leveraging on the industrial computer produced by Axiomtek, The applications can be further utilized in many different environments that include both indoor and outdoor project. 

Axiomtek AI Edge deployment with Open Vino

Watch us live at the link below:-