Best Industrial IoT Platforms (2024) for smart factories

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Devices that are part of the Industrial Internet of Things (IIoT), such as intelligent actuators and sensors, are extremely important in terms of improving the efficiency of manufacturing and industrial activities. It is possible to facilitate the gathering, exchange, and analysis of data in a seamless manner by interconnecting and synchronising these devices, which are often accomplished through dedicated IIoT platforms. The insights that may be obtained from this data are extremely useful since they have the potential to dramatically improve the operational efficiency, reliability, and overall performance of our organisation.

On top of that, platforms for the Industrial Internet of Things not only make it easier to integrate these devices, but they also act as hubs for the collection and analysis of such data. In addition to highlighting areas of success and identifying areas that are ready for development, they offer profound insights into the complexities of a company’s production processes within the organisation. Furthermore, these platforms play a crucial part in increasing the security of equipment connected to the Industrial Internet of Things (IIoT), thereby assuring sturdy protection against potential cyber threats.

Implementing solutions for the Industrial Internet of Things has completely altered the way in which businesses function by providing an unprecedented level of visibility and control over industrial processes. When organizations make efficient use of these technologies, they are able to maintain a competitive advantage, which allows them to drive innovation and maximise production in the current environment of intense competition.

What are Industrial IoT Platforms?

IoT software for industrial application offers a centralised framework that allows for the configuration, management, and monitoring of many Internet of Things devices that are utilised in industrial activities. You will be able to reduce unplanned downtime and shutdowns, improve your ability to make decisions based on data, and streamline industrial operations with the assistance of their respective platforms.

A centralised access to real-time and insightful predictive data is provided by the IIoT platform, which enables the identification of potential malfunctions and the improvement of shop-floor efficiency.

Best Industrial IoT Platforms Comparison Table

In today’s highly digital environment, industrial organizations are dependent on a wide variety of operational technologies in order to carry out their commercial activities. By integrating their Internet of Things assets, organizations are able to support their industrial operations by utilising the data that they have gathered through their digital processes.

Feature	AWS IoT Core	Akenza	IBM Watson IoT Platform	Microsoft Azure IoT	Oracle Internet of Things Cloud Service
Vendor	Amazon Web Services	Akenza Technologies	IBM	Microsoft	Oracle
Device Management	Supports various protocols	Limited device management	Advanced device management	Extensive device management	Supports various protocols
Data Analytics	Integrated with AWS services (e.g., AWS Kinesis, Amazon SageMaker)	Built-in analytics tools, integration with third-party tools	Integrated with IBM services (e.g., IBM Watson)	Integrated with Azure services (e.g., Azure Stream Analytics)	Integrated with Oracle services (e.g., Oracle Analytics Cloud)
Security	Robust security features (e.g., encryption, authentication)	Strong security focus	Comprehensive security features	Secure by design approach	Multi-layered security approach
Scalability	Highly scalable to handle large numbers of devices	Scalable to support various needs	Highly scalable	Highly scalable	Scalable to support various needs
Ease of Use	Moderately complex setup	User-friendly, low-code platform	Moderately complex setup	User-friendly for different levels of expertise	Moderately complex setup

Best Industrial IoT Platforms

Solutions that are based on the Industrial Internet of Things make it feasible to utilise this data by linking devices, assets, and procedures in order to provide total visibility across all areas of an organization.

By utilising their asset data and generating advanced Internet of Things solutions for business optimization, organizations are able to take their company activity to the next level through the utilization of this unique Internet of Things data utilisation.

AWS IoT Core

Feature	Description
Device Management	Manage and track IoT devices
Message Broker	Securely route messages between devices and AWS
Rules Engine	Define actions based on incoming data
Device Shadows	Mirror device state for offline functionality
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IoT Core from Amazon Web Services is a powerful cloud platform that I have personally discovered to be of great value in terms of supporting a connection that is both safe and smooth between devices and the cloud.

Because of its extensive feature set, which includes device management, data processing, and easy connectivity with other AWS services, I am now able to construct Internet of Things apps that are both scalable and reliable with ease.

Akenza

Feature	Description
Device Integration	Easily connect various IoT devices
Data Visualization	Create custom dashboards for data visualization
Analytics	Analyze IoT data for insights
Rule Engine	Automate actions based on predefined rules

The Internet of Things platform known as Akenza is a remarkable example of its versatility, since it streamlines the entire process, from the connecting of devices to the examination and gathering of data.

Because of its user-friendly interface and procedures that can be customised, I have been presented with a versatile solution that has made the deployment of Internet of Things projects a snap.

IBM Watson IoT Platform

Feature	Description
Device Management	Monitor, manage, and secure IoT devices
Data Analytics	Analyze IoT data for patterns and anomalies
Edge Computing	Process data at the edge for faster insights
Cognitive Services	Apply AI and machine learning to IoT data

Because I have worked with the IBM Watson Internet of Things Platform, I have seen firsthand how powerful it is as an all-encompassing Internet of Things solution.

Extraction of actionable insights from Internet of Things data has been made possible by its increased capabilities in device management, data analytics, and the integration of artificial intelligence. This has led to the making of relevant business decisions.

Microsoft Azure IoT

Feature	Description
Device Provisioning	Easily provision and manage IoT devices
Stream Analytics	Process and analyze real-time IoT data
Azure IoT Edge	Extend cloud intelligence to edge devices
Security	Secure IoT solutions with built-in features

With its extensive suite of tools and services that are specifically designed for the construction and deployment of Internet of Things solutions at scale, Microsoft Azure IoT has been an indispensable component of my Internet of Things endeavours.

I’ve discovered that Azure IoT is a vital platform for promoting innovation in the Internet of Things (IoT) world because of its capabilities, which include the provisioning of devices, strong data storage, and artificial intelligence capabilities.

Oracle Internet of Things Cloud Service

Feature	Description
Device Connectivity	Connect and manage a wide range of devices
Data Analysis	Analyze IoT data for insights and predictions
Integration	Integrate with Oracle’s suite of cloud services
Lifecycle Management	Manage devices throughout their lifecycle

Oracle Internet of Things Cloud Service has demonstrated that it is a platform that is both safe and scalable, and it enables real-time device connectivity, data collection, and analytical analysis.

Through its capabilities, which include device virtualisation, easy data visualisation, and predictive analytics, I have been provided with the tools that are essential for thriving in the ever-changing landscape of the Internet of Things (IoT).

Key Features to Look for in Industrial IoT Platforms

Industrial IoT (IIoT) tools are very important for linking, managing, and looking at data from many different industrial sensors and devices. When picking an IIoT platform, these are the most important things to think about:

1. Device management means being able to remotely set up, watch, and control a wide range of industrial sensors, devices, and tools. This includes things like setting up devices, updating software, and using tools to fix problems.
2. Connectivity and Protocol Support: You can use a number of popular industrial communication protocols and standards, like MQTT, OPC UA, Modbus, and Ethernet/IP. The platform should have strong connectivity options so that it can work with devices and systems that are already in place.
3. Data Acquisition and Ingestion: The ability to get sensor data, telemetry, and machine metrics from linked devices in real time and collect, aggregate, and ingest that data. For large-scale corporate deployments, the platform should be able to handle a lot of data coming in quickly.
4. Edge Computing: Edge computing lets you process and analyse data directly at the network’s edge, cutting down on latency, bandwidth use, and reliance on cloud connectivity. Edge analytics let time-sensitive manufacturing processes get information and make decisions in real time.
5. Data Storage and Management: It has built-in data storage and management tools that make it easy to store, index, and query big amounts of time-series data. The platform should be able to handle both organised and unstructured data formats and have features for encrypting, compressing, and keeping data safe.
6. Security and Compliance: Strong security features to keep private company information and things of value safe from online threats, unauthorised access, and data leaks. This includes things like encryption, authentication, controlling access, and following rules and regulations in the business (like NIST and ISO/IEC 27001).
7. Integration and Interoperability: The ability to work with third-party software tools like SCADA, MES, ERP, and PLM systems that are widely used in industrial settings, as well as existing IT systems and enterprise applications. For easy integration, the platform should allow open APIs, SDKs, and common data formats.
8. Analytics and Insights: this includes advanced analytics tools for getting useful information from industrial data, like predicting repair needs, finding oddities, improving processes, and optimising them. The platform should have analytics tools, machine learning algorithms, and visualisation screens that can be used to look at and explore data.

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