Wearable technology is a hallmark of the Internet of Things and the most ubiquitous of its implementations to date. The efficiency of data processing achieved by various smart wristwear, smart clothes, and medical wearables is getting to the point where this consumer-oriented side of IoT technology will bring tangible value to our everyday lives. Soon, we will have access to unobtrusive remote healthcare, personal lifestyle management, work assistance, parental controls, public safety monitoring, and many other IoT services based on wearable technologies. With the help of modern cloud-based IoT platforms, such as Kaa, wearable device manufacturers and application developers can introduce these new capabilities in shorter timeframes and at greater scale.
The Kaa IoT Platform functions as a device, application, and data management platform for your wearables. Thanks to its user-centric approach, Kaa dramatically simplifies device-to-cloud integration routines for your engineers, and offers perhaps the most straightforward device management UI on the market. Another benefit of Kaa is that it can be redistributed under the hood of your wearable technology to your own customers, thus enabling you to deliver various SaaS solutions on top of your smart devices.
As a cloud-native IoT platform, Kaa offers second-to-none scalability and reliable performance to ensure loss-free communication between your wearable devices. Built on a modern microservice architecture, it also provides developers and DevOps engineers with broad freedom of customization, broad choice of development tools and languages, and the ability to implement any type of cloud deployment. As a result, your team can quickly get started with Kaa and shorten the development timeline for wearable devices & software management solutions from months to weeks or even days.
In addition to its device management and data collection functionality, Kaa empowers your wearable solutions with data analytics and visualization tools, which enable device manufacturers to track performance and device health stats, analyze the accuracy of sensor algorithms, and execute A / B testing for different device software.