Skill Level: Any Skill Level

Industrial IoT and AI enable a new surge of manufacturing productivity with Industry 5.0. The Cloud Robotics Platform aims to Remote Control, Monitoring and Analysis of Production Line using Siemens S7-1500 using IBM Cloud AI capabilities.


Software Requirements

IBM Cloud Account

Watson Visual Recognition

Node-Red skills 

Tia Portal basic skills

Hardware Requirements

Robotic Platform :

Robot Schneider MD1AE915D  (or any robot compatible with SIMATIC S7-1500 Controllers ) 



Raspberry PI 3 used for Node-red platform

IoT node : SensiBLE 




  1. Towards Industry 5.0

    The most common definitions of the Industry 5.0 reveals that it will focus on Bridging the Gap between AI and human, as human intelligence works in harmony with cognitive computing. AI capabilities such as Watson services allows a human and machine interconnection and communication to meet the manufacturing complexity of the future in dealing with increasing customization through an optimized robotized manufacturing process.

    We developed a cloud robotic platform allowing bridging the gap between human and machines (AI). The AI panel consists of  using personalized Watson services such as a customized Virtual Assistant called Industrial Virtual Assiatnt  (IVA) (communicate with both robot and human), Visual recognition to detect defects in products and Voice recognition service. Actually, for predictive maintenance purposes we used SensiBLE (Stm32 IoT node) which allows delivery sensors data over BLE, including accelerometer, gyro, microphone, UV, proximity and ranging sensors.



    Video demonstration: 

    Robot Cloud monitoring (Node-RED via Simenes S7-1500) and product quality checking (Vsion recogniton): 


    Voice robot control ( Voice Recognition) : 



    A schematic representation of the developped Cloud Robotics Platform, given as follow:  



  2. Node-RED industrial IoT platform

    Node-RED Dashboard:

     Real-time robot visualization, product quality checking :



    The SensiBLE IoT node is actuality fixed to the robot gripper. Collection of data from sensors to cloud allows to perform prediction maintenance tasks.  




    SensiBLE IoT Dashboard node Flow :



  3. AI panel

    Visual recognition for manufacture quality control

    We use a Raspberry Pi3 , a Camera and the Watson Visual Recognition Service to take a picture and detect defect in the products (cylinder pieces). Custom Classifier Training is Included.

    Camera (connected to Raspberry Pi3) capturing pieces at the end of manufacturing processes :


    Custom Classifier Training (Uncolored cylinder piece as perfect manufactured product, Blue colored cylinder as defected product)   :



     Node-RED flow:


    Perfect piece detected ( (uncolored cylinder piece) : 

    defectparfait parfaitScore 


    Defect detection (Blue colored cylinder piece)  : 

    defect1  defectScore


    Industrial Watson Assistant coupled to voice recognition capabilities

    The main goal of using a customized Virtual Assistant is to allow user asking the V.A about information related to robot sensors event autonomous controlling the robot with the ability to take the robot under control for diagnosis tasks. We started actually by connecting the V.A to Siemens S7-1500 controller and to the user microphone.

    Node-RED flow:



  4. Cloud based remote monitoring of Siemens S7-1500

    Cloud-based monitoring system allows to remotely control system state and get messages concerning inner system events from S7-1500 Siemens and third-party sensors/Actuators.  To learn abour how to use Node-RED with siemens S7-1500 please check  my previous article :



  5. Conclusion

    In this recipe we have shown the implementation of a PoC about Cloud Robotics Platform with IBM Watson AI and Siemens S7 1500.  After successfully connecting S7-1500 to robot and Node-RED over Raspberry Pi3. We developed a dashboard allowing communication between user and robotic platform. We got fluidic immersion between user and machine thanks to Watson AI capabilities. Other AI functions allows Data analytics, Monitoring, Predictive Maintenance and even product quality control. 

    Dr. Mustapha

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