Edge computing emerged with the growth and demand for the Internet of Things (IoT). It is an architecture that places fast computing power or storage capacity close to the data source, such as a sensor or a camera. Whether looking at controllers that connect to a cloud platform over the Internet or small data centers on a campus, there is one thing that all applications have in common. Edge computing enables faster response times compared to a central data center connection and reduces data volume in the cloud when needed through local data processing. Small and medium-sized enterprises (SMEs) often use their own computer resources as independent hubs from their IT to overcome slow internet connections or insufficient bandwidth. This is important because anything that slows down fast computing will put you behind your competitors.
Another great advantage of edge computing is that you maintain both autonomy and control over your data at all times; the data that remains local and what is sent to the cloud. This protects personal data and equally important business critical information in general and in particular when the US CLOUD Act comes into force. Keep in mind that US authorities may require the disclosure of information even if it violates a country’s legislation, such as the EU General Data Protection Regulation (GDPR). It is valid in the EU and protects the data in the country of treatment. Therefore, since the end of the so-called ‘Privacy Shield’, all US cloud platform providers are required by the US CLOUD Act to disclose all data about their users to the US federal authorities upon request. This applies not only to personal data, but also to business-related data, even though this data is stored in a data center within the EU and is in fact protected by the GDPR.
Edge as part of a hybrid cloud environment
With few exceptions, an edge infrastructure today is designed as a private cloud. In this way, local installations can be more easily integrated into a central cloud environment and managed through a single interface. In addition, the connection to the cloud also provides access to a higher data pool and enables, for example, big data analysis or applications that support machine learning. Cloud management solution providers are currently expanding their software to hybrid and multi-cloud environments across the board. Fortunately, the administrative burden also stays within limits, for most administration platforms, despite all the complexity of the background, are now quite user-friendly and intuitive.
It does not matter
Edge computing has many usage scenarios and different system requirements. Let’s put the most obvious things aside, such as production and autonomous driving. Edge computing clearly drives the digital transformation on several levels. Its integration into a wide range of business processes not only increases efficiency but also security. Let’s look at a few examples:
- Improved safety in remote or dangerous areas
Warehouses or construction sites in remote locations require protection against unauthorized access for a variety of reasons, whether it is protection against theft of stored goods or access control to a potentially dangerous construction site. In order not to have on-site staff, such sites often have an autonomous access control system combined with edge-to-edge camera surveillance to allow communication with a central port. In an industrial environment, safety features for dangerous places become a reality. Think, for example, of emergency buttons for staff, or an analysis of movement close to a dangerous zone. Edge computing can even automatically check if security equipment is being carried. If danger is detected, the software immediately issues a rule-based alarm so that appropriate action can be taken before anything happens or people are injured. Data protection is not a problem either, because most of this type of data is deleted immediately.
- More digitization in branches
In the retail or restaurant chain, edge computing typically integrates multiple computers, POS systems, and other devices into the corporate network. Customer data is on site and local availability guarantees a positive customer experience. For example, edge computing marketing allows you to communicate directly and interact with customers and visitors via Bluetooth and WLAN. Edge computing allows banks to use face recognition technologies and virtual customer advisors in their self-service zones without violating strict data protection rules. By processing data on the spot, edge ensures fast response times and helps to further reduce branch visits from online banking fans, as well as the piles of paper still generated during manual processes.
- More efficient use of inventory and patient management in healthcare
The Medical Internet of Things in a private cloud simplifies inventory management, localization and patient management across the healthcare industry. Compliance with the GDPR and special protection of sensitive patient data is a top priority. As is so often the case, healthcare is not about edge computing or cloud, it is about data management strategies. These determine where cloud and edge computing should be used strategically, based on individual requirements, costs and benefits. Thanks to a growing number of medical devices, the average hospital now produces more than 50 petabytes of data per year. Therefore, the edge data center is particularly important here to optimize clinical and operational values. Connecting to a cloud platform, in turn, enables AI-assisted analytics, and networking with other institutions creates additional significant synergies and economic benefits.
A critical role for all edge computing solutions is that they run largely autonomously on site and are centrally managed. Like any other infrastructure solution, edge devices must be suitable for the corresponding environmental conditions. In addition, the list contains adjectives related to the requirements, such as compact, fail-safe, protected against cyber attacks and unauthorized access. Of course, any new edge computing solution must be scalable and quickly adaptable to new requirements and applications.