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Seeking to provide customers with all the components that make up the connected world – including sensors for collecting data, software for developing IoT solutions, and the cloud itself – the Bosch Group recently announced that it is launching the Bosch IoT Cloud. They identified five application patterns that such a cloud must support. That got me thinking - is this the right set of patterns? Are there any others?
Bosch's five patterns are:
Cloud-based apps. This pattern really represents the set of capabilities and services - such as the ability to manage the relationship between users and assets, with different access rights. In a sense it is the null set for IoT applications or basic cloud application requirements. These applications that are not connected to any assets or devices, so not quite IoT.
Asset-based apps. In this pattern, the cloud enables autonomous behavior of assets by supporting application logic and data. Think self-driving cars. This can be challenging at scale.
Distributed IoT apps. This pattern supports applications that take advantage of local asset-based capabilities working together with cloud-based support or optimization.
Digital Twin. In the Digital Twin pattern, real-time data from assets in service feed a digital model in the cloud. Can be the basis for predictive maintenance, remote monitoring and service, and more.
Social IoT. This pattern lets multiple assets coordinate or cooperate with each other. Data from multiple assets is aggregated and can be used by multiple applications and assets. Collaborative route optimization, for example.
All in all, quite a useful set of patterns. But I do have two additional patterns to offer for consideration:
Edge-optimized IoT. In industrial applications, there are cases which may benefit from a pattern in which intelligence and analytics is deployed at or near the assets. Rapid responses and actions would be facilitated, and only a subset of the streaming data would need to be sent to the cloud for storage and processing.
Multi-party IoT. The concept behind this pattern is that there is often more to the story than just the asset and the cloud. For example, look at a mining operation. Data from an asset (heavy machine) may be monitored by the machine manufacturer in order to improve the machine design, by the mine operator to coordinate the machine's work with other machines, by a local third-party field service company; and by a replacement parts company.
Are there other IoT patterns that should be included? Let me know!
Bosch's five patterns are:
- Cloud-based apps: Cloud-based development of responsive web apps
- Asset-based apps: Autonomous apps, over-the-air software updates
- Distributed IoT apps: Apps & data distributed between assets and elastic cloud
- Digital Twin: Data from assets automatically replicated in cloud, cloud apps can build on local data
- Social IoT: Apps leverage data shared by multiple assets
Cloud-based apps. This pattern really represents the set of capabilities and services - such as the ability to manage the relationship between users and assets, with different access rights. In a sense it is the null set for IoT applications or basic cloud application requirements. These applications that are not connected to any assets or devices, so not quite IoT.
Asset-based apps. In this pattern, the cloud enables autonomous behavior of assets by supporting application logic and data. Think self-driving cars. This can be challenging at scale.
Distributed IoT apps. This pattern supports applications that take advantage of local asset-based capabilities working together with cloud-based support or optimization.
Digital Twin. In the Digital Twin pattern, real-time data from assets in service feed a digital model in the cloud. Can be the basis for predictive maintenance, remote monitoring and service, and more.
Social IoT. This pattern lets multiple assets coordinate or cooperate with each other. Data from multiple assets is aggregated and can be used by multiple applications and assets. Collaborative route optimization, for example.
All in all, quite a useful set of patterns. But I do have two additional patterns to offer for consideration:
Edge-optimized IoT. In industrial applications, there are cases which may benefit from a pattern in which intelligence and analytics is deployed at or near the assets. Rapid responses and actions would be facilitated, and only a subset of the streaming data would need to be sent to the cloud for storage and processing.
Multi-party IoT. The concept behind this pattern is that there is often more to the story than just the asset and the cloud. For example, look at a mining operation. Data from an asset (heavy machine) may be monitored by the machine manufacturer in order to improve the machine design, by the mine operator to coordinate the machine's work with other machines, by a local third-party field service company; and by a replacement parts company.
Are there other IoT patterns that should be included? Let me know!