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Hosting Web API IoT data and realizing AI OCR with Openvino

Sembang AIoT #20 From Axiomtek Malaysia kick started with something very interesting this time because the audience is able to experience the real vision OCR ( optical Character Recognition) with Openvino AI engine powered by intel-Axiomtek AI edge platform. 

Of course, the IIoT sensors part is not finished yet, This round we share something related to Smart Agriculture sensors such PH / Salinity sensors, soil NPK sensors, Temperature, and Humidity sensors etc. all these sensors can polled and hosted on the AIoT Edge Connect cloud, Local OPCUA, Local Web API or even on the web server. 

The Demonstration continued with  Axiomek IIoT Edge gateway polling Data from the RTD Temperature module and sensors, data is logged at the IIoT edge gateway and from the database end, the data was then hosted on a Web API or Rest API server on the Edge gateway.  

For this case the remote connection from the other Industrial PC system running another set of SCADA software namely Adisra IIoT SCADA provides a Web API client that allows it to connect to the Web API server earlier on.  This is very handy where the online live data can be shared and the connection or retrieval of data can be scheduled as per how frequently you need the data.  The default setting is at 1 second per connection. 


Axiomtek IIoT edge gateway is hosting the data polled, in this case, 2 x RTD sensors data from the RTD module were obtained. Local display on the temperature was shown on the gateway as an option nevertheless the IIoT edge gateway can be a stand-alone headless if you want it to be.

The right hand picture showed on another IPC running Adisra SCADA software with Web API client driver where the http get can be done in a quite straightforward manner. 

In this demo, we only apply user name and password to connect to the Web API server although it supports token + User name+ Password as well. 

Setup in the Web API Server Demo

Vision AI OCR with Openvino Demo

The second half of the sharing started with some introduction and explanation of the AI model of OCR and some history. We are using one of the model that is able to effectively OCR via computer vision on two main objects with printed characters on the objects. One of them is a 3 PIN power plug ” Sirim” sticker and also on the Axiomtek carton box. 

There are many applications with computer Vision OCR especially in the manufacturing. Some of them are as follows:

1. Quality Control and Inspection:
– AI OCR can be used to inspect product labels, barcodes, serial numbers, and other critical information to ensure they meet quality standards.
– It can identify defects or discrepancies in printed labels or packaging, helping to reduce product recalls and maintain quality control.
2. Inventory Management:
– AI OCR can automate the process of tracking and managing inventory by recognizing and updating product information from labels and packaging.
– It can help prevent overstocking or understocking of items and improve supply chain management.
3. Document Management:
– Manufacturers deal with various documents, such as invoices, purchase orders, and shipping labels. AI OCR can automate the extraction and digitization of data from these documents.
– This improves accuracy and reduces manual data entry, saving time and reducing errors.
4. Equipment Maintenance:
– AI OCR can be used to read and interpret data from equipment sensors and gauges, allowing for predictive maintenance.
– By analyzing this data, AI systems can predict when machinery needs maintenance or repairs, reducing downtime and maintenance costs.
5. Regulatory Compliance:
– Manufacturers often need to comply with various regulatory standards and certifications. AI OCR can assist in the verification and validation of documents and labels to ensure compliance.
– It can flag discrepancies or missing information that could lead to compliance issues.

Of course, having AI in the process is great but, if the IIoT can be incorporated within the implementation the effectiveness can be well increased.

For visual, watch us live at the link below:-