Edge computing is a hot topic in the Internet of Things (IoT) circles these days, particularly at the thin edge where solutions are increasingly leveraging connected protocol gateways, industrial programmable logic controllers (PLCs) and embedded devices at remote locations.
According to Statista, the worldwide edge computing market is projected to reach $274 billion by 2025. This growth means that vast amounts of data generated by connected devices will require more storage, computing, and network capacities closer to the source.
A good example here is elevators: There are over 17 million elevators and escalators in use, and no one wants to get stuck in one. One company already uses thin edge computing as a cost-effective way of collecting, locally processing and sending back information about the status of its elevators to determine whether it needs a service or has developed a fault. The ability to automatically diagnose elevator maintenance needs along with the scalability required to manage large numbers of these thin edge devices are key requirements.
Challenges of IoT on the edge
While deploying IoT solutions on edge devices (devices with compute abilities that sit close to the sensors and actuators they control) is not new, deploying these solutions as modular, out of the box components onto hardened, cost sensitive, lower compute power devices with a small physical footprint has presented challenges to many organizations.
The reason for this has largely been that, until now, there has been no open embedded software platform to bridge the gap to the serving cloud platforms. As a result, organizations have been faced with the unenviable choice between building, testing and deploying their own IoT services on thin edge devices, building it themselves, or getting locked into a vendor or hyperscaler. This is along with the challenge of making this talk to their existing back-end architecture.
Remove the complexity
What if there was a faster, simpler, more flexible way to have secure connectivity and management of your thin edge devices? There is. Industry leaders including IFM, Nexus, ADAMOS, Kunbus, and Software AG, have teamed up create a cloud-agnostic open-source framework – thin-edge.io. Software AG customers can now take advantage of the strengths of the award-winning Cumulocity IoT platform, including device connectivity and management, and analytics, when managing a wider range IoT devices, running on a multitude of thin edge hardware.
It is a significant step forward in extending Cumulocity IoT’s capabilities. Providing a commercial version of the ground-breaking thin-edge.io framework provides customers with the best of both worlds: open-source extensibility and ecosystem, and multi-year enterprise-grade support and services. This further demonstrates that Software AG is leading the way in delivering open IoT solutions that deliver real value, fast, whilst spreading accrued knowledge to our community of developers and users.
This means there is now an extensible, open platform for building new, flexible IoT applications on thin edge devices, drawing on proving technology. With Cumulocity IoT Thin Edge, you will be able to:
Instantly and securely connect your devices to Cumulocity IoT – shortening response times, improving reliability and reducing upstream bandwidth. Remove the complexity of keeping your software and applications updated in the field, while providing unrivalled security and reliability when it comes to securely connecting and maintaining devices that operate in remote operational environments
Eliminate the limitations associated with rolling out updates across all devices or with capturing consistent data for preventative maintenance – breaking down the barriers of hardware and software fragmentation
Remain competitive, innovative, and drive incremental revenue – be smarter and faster in a world that constantly demands faster and better results.
Meet IT and OT needs by transforming single purpose gateways into flexible platforms running IoT services and apps, thus reducing IoT solution development time and cost.