On-Premise IoT Platforms and Examples


IoT is growing rapidly. IoT platforms do all the tasks from data collecting & storage to analyzing the data. It makes IoT platforms the backbone of the IoT ecosystem. In the market, there are two main types of IoT platforms one is cloud−based & other one is on−premise.

In this article, we will concentrate on on−premise IoT platforms and give application examples.

On−Premise IoT Platforms

IoT platforms known as "on−premise" IoT platforms are those that are set up and run on a business's servers or internal data centers. They offer the same features as cloud−based IoT platforms, including data management, analysis & acquisition but because they are deployed locally, businesses have more control over their data and security.

Companies that must operate in remote areas with sparse internet connectivity or that have tight security standards and compliance requirements frequently employ on−premise IoT platforms. Companies can guarantee the security of their data and have total control over its processing and analysis using on−premise IoT platforms.

Examples of On−Premise IoT Platforms

  • Microsoft Azure IoT Edge

    Microsoft Azure IoT Edge is an On−Premise IoT Platform that enables companies to run IoT workloads on the edge, close to the devices and sensors generating the data. It offers a safe and expandable infrastructure for data processing, enabling businesses to instantly analyze data & take appropriate action. Microsoft Azure IoT Edge also includes machine learning capabilities that enable predictive maintenance and anomaly detection.

  • IBM Watson IoT Platform

    IBM Watson IoT Platform allows them to collect error−free data. Organizations need to make data−driven decisions. IBM Watson IoT Platform also includes AI & machine learning capabilities that enable predictive maintenance, asset tracking, and other advanced analytics.

  • Oracle IoT Cloud

    Oracle IoT Cloud enables companies to operate and analyze IoT sensors and devices. It allows a safe & scalable platform for data gathering, analysis, & management for businesses to make data−driven decisions. Oracle IoT Cloud also includes machine learning capabilities that permit predictive maintenance, anomaly detection & other advanced analytics.

  • HiveMQ

    HiveMQ is a highly scalable & secure On−Premise IoT Platform that allows organizations to connect. HiveMQ supports various IoT protocols & includes machine learning capabilities that allow predictive maintenance, anomaly detection & other advanced analytics. It is an ideal choice for companies that require a flexible and customizable IoT solution with high performance and low latency. HiveMQ also offers a cloud−based option for companies that require both On−Premise and cloud−based IoT solutions.

  • EMQX On−Premise IoT Platform

    EMQX, created by EMQ, is an MQTT messaging platform that is highly scalable and dependable. It is capable of supporting up to 100 million simultaneous connections to IoT devices per cluster, all while maintaining exceptional throughput and sub−millisecond latency.

  • Armis Security

    Armis Security is a leading On−Premise IoT Platform that provides comprehensive security solutions for IoT devices and sensors. It provides real−time visibility into all devices & their behaviors, allowing companies to identify and remediate security threats quickly. Armis Security uses machine learning and artificial intelligence to analyze device behavior and detect anomalies, enabling predictive maintenance and other advanced analytics. It is an ideal choice for companies that require a robust and scalable security solution for their IoT ecosystem. Armis Security also offers cloud−based and hybrid options, providing companies with flexible deployment models to meet their specific needs.

  • Siemens MindSphere

    Siemens MindSphere is an On−Premise IoT Platform that enables companies to connect and manage IoT devices and sensors. It provides a secure and scalable infrastructure for data collection. Siemens MindSphere also includes AI and machine learning capabilities that enable predictive maintenance, asset tracking, and other advanced analytics.

  • Rayven

    Rayven specializes in providing real−time data integration. The company collaborates with both partner organizations and industrial businesses to create tailored IoT solutions using Dynamix & their technology. With these solutions, industrial businesses can deliver more to their customers with ease.

  • AWS Greengrass

    AWS IoT Greengrass is a technology that enables edge devices to process data locally while still utilizing the cloud for management, analysis, and storage. It empowers connected devices to execute AWS Lambda functions. You may create and test device software in the cloud using well−known programming languages with the help of AWS IoT Greengrass before putting it on your devices. Additionally, AWS IoT Greengrass can be programmed to filter device data, manage its lifecycle on the device, and only transmit necessary data back to AWS. AWS IoT Greengrass Connectors promote seamless integration with third−party apps, on−premises software, and AWS services.

Conclusion

In conclusion, On−premise IoT platforms are ideal for organizations working in remote areas with poor internet connectivity or having tight security standards & compliance requirements. The article emphasizes different on−premise IoT platforms & their features, including data management, analysis, and acquisition, along with machine learning capabilities that enable predictive maintenance, asset tracking, & other advanced analytics. It will guide you to understand IoT in a better way.

Updated on: 29-Aug-2023

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