Companies looking to add Internet of Things (IoT) functionality to their industrial systems have lot of cloud platform options to choose from. These cloud platforms offer the computational and storage backbone for the Industrial IoT (IIoT).
Gartner predicts that 20 billion connected things will be there in market by 2020. With all of these connected devices in the market, companies have no option be to start their IoT implementation, or plan it shortly.
Different IoT Platforms in various Industries
So lets see which are different IoT platforms already being used by various industries. When your company or your client plans to start the implementation of IoT solutions and services, this might help.
1. Predix has robust data integration and application management capabilities, but lack a device management module which it provides through partnerships.
2. Predix offers a strong analytical and edge computing capability which allows for a wide range of uses in the industrial as well as aviation sectors.
1. AWS IoT has a strong data integration and collection capability which allows it to connect to existing databases without the need to change the architecture.
2. Though AWS has a vast partner network which allows it to develop their products, the industry focus is limited to a few use cases.
1. IBM Watson IoT has a very strong data integration capability which uses NLP, machine learning and cognitive computing to assimilate data and provide insights
2. Though not built on edge computing, the IBM has partnered with Cisco to enhance the capability and serve several industries such as retail and transport.
1. Microsoft Azure IoT platform offers an inbuilt bidirectional device management suite along with a robust data integration and collection capability.
2. Microsoft is able to provide a strong analytics and data visualization suite, but the company lacks any significant partnerships to enhance their product capability.
1. Thingworx has a robust data collection and integration capability allowing the platform to connect with several third party cloud platforms such as AWS.
2. Thingworx also has a strong industry presence with use cases in manufacturing, utilities, enterprise, healthcare, public services and transport etc.
1. Cisco connects only with the Cisco Cloud and uses CoAP, XMPP and RESTful HTTPs to connect to it making the cloud platform easy to use and scalable.
2. The platform uses Fog computing which extends the capabilities of the platform and connectivity on the edge allowing the company to focus on different industries
Features of these IoT Platforms
All platforms have strong analytic capabilities as well as the ability to gather real-time data insights.
Application Development & Integration
Almost every company offers a platform that can be connected to via more than just Ethernet or WiFi, such as via cellular, satellite, or low power/short range communication (Bluetooth, ZigBee, etc.).
Common communication protocols among these platforms include HTTP and MQTT. MQTT is an extremely lightweight machine-to-machine (M2M)/IoT connectivity protocol.
All platforms have device management and data management capabilities.
One thing that most all platforms have in common is the ability to send device commands, meaning they are able to send messages to the devices.
Other common capabilities of these platforms include device identification, device lifecycle management, device registries, and device/client/service libraries.
A few of the platforms include object storage, some provide SDKs, and some have virtual device capabilities.
All platforms securely send and receive data, use strong authentication and authorization methods, and use encryption. The majority also have audit capabilities.
Workflow / Event Processing
Most of the platforms have the ability to create workflows, process events, and create rules.
In this thought paper we have investigated the features of the current state-of-the-art IoT software platforms. The investigation focused on aspects such as device management, integration, security, protocols for data collection, types of analytics and support for visualizations.
From this study it was clear that areas such as device management, IoT data analytics, and IoT software system scalability and performance characteristics need special attention from IoT software platform community.
Furthermore, there’s relatively little support for analyzing the generated IoT data in terms of both computation and visualization. Most of them support real-time analytics – a must-have feature in any IoT framework. However, only few IoT software platforms provide support for other three types of analytics.
In terms of the visual interfaces, most of them are focused on the simple patterns of a web portal. These dashboards allow for management of IoT ecosystems, but very few provide the capabilities of visual data analytics.
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