Industrial Internet of Things

The Industrial Internet of Things (IIoT) refers to interconnected sensors, instruments, machines, computers and other devices networked together for manufacturing, energy management, etc. This connectivity allows for data collection, exchange and analysis thereby, facilitating improvements in productivity and efficiency as well as other economic benefits. The architecture typically consisits of the Device Layer which refers to the physical components like sensors or machines. The Network Layer consists of physical network buses, cloud computing and communication protocols that aggregates and transports the data to the service layer. The Service Layer consists of applications that manipulate and combine data into information that can be displayed on the dashboard. The top-most stratum of the stack is the Content Layer or the user interface.

Internet of Things (IoT) refers to managed platform services across edge and cloud that Connect, Monitor and Control IoT Assets. These services work together across typically the following components: Things - The physical objects or things such as industrial equipments, devices or sensors that connect to the cloud. Insights - Information collected by the things which is then analysed and turned into actionable knowledge using Machine Learning, Artificial Intelligence etc. Actions - The way people respond to the insights and connect them to their business as well as the used systems and tools.

IoT Edge Solutions

Machines, PLC's & Sensors support varied industrial protocols which need to undergo a protocol translation at the edge using platforms such as Azure IoT Edge, AWS Greengrass or Ignition/Kepware. After protocol translation this data can then be ingested, processed & visualized.
Industrial IoT platforms such as KepserverEX or Ignition can be used for protocol translation of a wide range of industrial protocols such as Modbus, OPCUA, etc. and these platforms support an extensive list of industrial protocols from varied equipment manufacturers.
Amazon Web Services IoT Sitewise Edge along with Domatica EasyEdge can be deployed on the edge to support protocols such as Modbus, Ethernet/IP, LoraWAN, REST, KNX, Profibus & Profinet.

Industrial IoT Solutions

The Microsoft Azure IoT platform allows plant operators to discover OPC UA-enabled servers in a factory network, compute/visualize KPI's and also create Azure Digital Twins to model the factory data.
Amazon Web Services IoT SiteWise can be used to implement end to end Industrial IoT solutions also, Digital Twins can be modelled using AWS Twinmaker.
Azure, Microsoft Fabric or AWS can be used to Ingest & Store data, Compute KPI's, Raise Alarms/Alerts and Visualize the ingested data.
Ignition or Kepware can be used to build end-to-end Industrial IoT solutions starting from data acquistion at the edge over a wide range of Industrial protocols to raising computing KPI's, raising alarms and visualizing the data.

Artificial Intelligence

An artificially intelligent system makes predictions or takes actions based on patterns in existing data and can then learn from its errors to increase its accuracy. Azure or AWS AI services assist developers and organizations to create intelligent, cutting-edge, market-ready and responsible applications. Examples of such AI applications include natural language processing, monitoring, translation, speech, vision and predictions.
Machine learning (ML) is a field of study in artificial intelligence concerned with the development of algorithms that can learn from data, perform predictive analytics and generalize to unseen data thereby performing tasks without explicit instructions. ML finds application in many fields such as manufacturing, agriculture, energy and medicine. Azure Machine Learning and Amazon SageMaker are services which can be used to build ML solutions.

Amazon Web Services & Azure/Fabric

Microsoft Fabric is an all-in-one analytics solution that covers everything from data movement, Real-Time Analytics to Business Intelligence. Fabric has a suite of services including data lake, data engineering and data integration.
Microsoft Azure is used to build, transform and visualize Industrial IoT Solutions. Azure Data Explorer, Stream Analytics, Digital Twins, Power BI, Azure Functions etc. can be used to build Industrial IoT solutions.
Amazon Web Services is used to build end to end Industrial IoT Solutions which includes data ingestion, storage, computation, machine learning and visualization. AWS Internet of Things, AWS IoT Sitewise, AWS Timestream, Grafana, Twinmaker, Lambda, Kinesis etc. can be used to build Industrial IoT solutions.