Blue Ice Cloud
Product Design
Design System
2016 - 2017
Design System
2016 - 2017
Blue Ice Cloud is a cloud computing platform that powers small teams and individuals to deploy and manage their IoT infrastructures and applications with ease.
As the principle designer of a fast-moving engineering team, I created a custom design language and design system, as well as led the product and experience design for the platform’s full line of IoT and machine learning modules.
As the principle designer of a fast-moving engineering team, I created a custom design language and design system, as well as led the product and experience design for the platform’s full line of IoT and machine learning modules.
1 to 1000; then 1000 to 1000,000
Blue Ice Cloud was envisioned to support both tech-savy teams and non-technical individuals. Our top goal, therefore, was to create a flexible device management module that could be scaled up to manage large amounts of IoT devices.
List and spatial views
When IoT devices are deployed in the real world, it is often important for users to be aware of the devices’ status, as well as how they situate in the surrounding physical environment.
We created a robust data table, as well as a map view that could accommodate and visualize a enormously long list of devices and report their status in real time.
When IoT devices are deployed in the real world, it is often important for users to be aware of the devices’ status, as well as how they situate in the surrounding physical environment.
We created a robust data table, as well as a map view that could accommodate and visualize a enormously long list of devices and report their status in real time.
To find and to act on
In a typical IoT use case, users may often need to manage an enormous amount of devices, computing units, as well as the underlying networks and infrastructures. Without an efficient filtering strategy, even a simple task such as locating sensors from a long list of devices may take a lot of effort.
To address the complexity of maintaining such IoT infrastructures, we created a powerful filtering interface for the devices list, through which users could group and filter devices, and therefore to perform the relevant actions on them more efficiently.
In a typical IoT use case, users may often need to manage an enormous amount of devices, computing units, as well as the underlying networks and infrastructures. Without an efficient filtering strategy, even a simple task such as locating sensors from a long list of devices may take a lot of effort.
To address the complexity of maintaining such IoT infrastructures, we created a powerful filtering interface for the devices list, through which users could group and filter devices, and therefore to perform the relevant actions on them more efficiently.
Surfacing actions
There can be many complex actions that could be performed on IoT devices, and the types of such actions would also depend on the types of devices. Therefore, actions are only surfaced to the devices are explicitly selected. At this point, only the relevant actions are displayed to avoid noise and confusion.
There can be many complex actions that could be performed on IoT devices, and the types of such actions would also depend on the types of devices. Therefore, actions are only surfaced to the devices are explicitly selected. At this point, only the relevant actions are displayed to avoid noise and confusion.
Design System
We referenced and built upon various open design systems including Google’s Material Design, IBM’s Carbon Design Language, as well as Atlassian’s design system. Our design challenge was to create a consistent and effective design system that can accommodate the diverse UI components and applications.
Devices _list
Devices _map view
Dashboard _model evaluation
Business ruleset _editing
Model _exporting
© 2022 Chao Feng