There’s something magical about the “edge”. For example, in environmental science, one studies “habitat frontiers” where certain cultivars grow abundantly at the edges but not further away. Similarly, in astronomy, we have seen dramatic phenomena happening at the edge of the universe.
It seems no different for human society that a new revolution is taking place with high computing power moving towards what is increasingly being called – Edge Computing.
Industry 4.0 and IoT
Essentially, IoT involves the collection and analysis of data, insights, and automation of processes involving machines, people, things, and places. Thus, IoT is a combination of sensors, actuators, connectivity, storage and cloud and edge, AI and ML intelligence, and security.
Industry 4.0, also known as the fourth industrial revolution, relies heavily on IoT technology, redefining automotive, transportation, healthcare, public transportation, retail and commerce. Since AI and ML drive all 5G and IoT innovations, it is a natural phenomenon for them to come together.
Strong IoT-enabled 5G
One of the most important innovations of 5G is providing strong support for IoT, including support for low-cost sensors, long battery life.
When data storage and computation becomes a ‘continuum texture.’ That fabric touches all areas and a wide range of AI, ML and Edge Compute solutions will eventually find their optimal areas to reside and roles to perform depending on the use case. use.
A host of new cloud service providers, such as Google, Amazon, and Microsoft, have introduced a whole new dimension of IaaS (Infrastructure as a Service), with manageability, transparency transparency and analysis at competitive prices.
The plethora of options from LoRAWAN, NB-IoT, and 5G are growing rapidly making it easier and more feasible to deliver cutting-edge IoT solutions.
Massive advances in computing silicon have made advanced devices powerful – allowing for localized data assessment and real-time decision making, completely avoiding the need to transfer to the server.
Some other transformations are starting to be seen, with more clarity in player engagement. For example, telecom operators have Hyperscalers (mentioned above) and Operational Technology (OT) transitions such as machine control systems to the IT sector.
More and more IoT applications are being conceived and built in the hope that they will be used and paid for by businesses and consumers. However, for various reasons, it is clear that it will be best delivered from a location closest to the customer and that area is an operations hub.
Wardrobe space for businesses and consumers is the space all these players want to dominate.
This space will essentially mean a shift in workloads from central data centers to a dedicated edge computing cloud near on-premise or on-premises. Changing data centers can sometimes mean moving the on-premises data center to a dedicated on-premises data center. edge cloud.
This shows the shift from Capex model to Opex model, affecting corporate financial models.
Edge Cloud in IoT World
In some ways, this adds a new direction in the value chain. The cloud is moving towards the edge, in what is now known by the industry as the Edge Cloud.
A simple explanation of Edge Cloud
Edge Cloud is simply a combination of intelligent edge devices (including sensors, nodes, and gateways) with software (algorithms, security stacks, connectivity modules, sensor components, and trigger, one processor in a full stack) to handle hundreds of sensors per port.
Thousands of such nodes automatically come together with advanced clustering and node reconfiguration, rerouting in case of failure in some sort of super-smart IoT network.
Where does the technology for the cloud come from?
Various technologies are already available and scalable use cases are gaining popularity. They even have standardized protocols to offload data to the cloud for non-critical data processing, but retain real-time data processing at the Edge Cloud itself.
Can we stop AI or ML?
As the volume of Silicon increases and the price goes down, we expect millions of IoT devices to be able to communicate through Edge Clouds and support people’s lives. The move of AI/ML towards the edge is an irreversible process and, in fact, a necessity.
The following benefits are clearly visible to industries implementing these technologies:
- RT processing ensures low-latency responses (improves safety, reduces error rates)
- Localized data security
- Sort, filter, and preprocess data before it appears in the cloud (cloud offload)
- The combination of licensed and unlicensed spectrum creates a more efficient transport mechanism.
AI image processing, object detection, and audio/video recognition are also significantly improved. They are currently available as extras with certain Silicon vendors. We expect these to become more common and pricing to improve as the rollout grows.
Is this Edge Cloud real?
Is there hype around Edge Computing? Several assumptions are being made that are driving this extraordinary explosion in edge cloud theory:
- It is not yet clear whether the Edge Cloud market will be as large as it is right now. There is evidence that it can be a high growth area. However, the ownership elements of this service are still being determined; telco versus hyperscaler versus an enterprise systems integrator versus a Cloud Edge specialist.
- Edge Cloud is a solution that fits each use case. Which applications require Edge Cloud capabilities (perhaps RPA and healthcare production versus retail applications) is unclear. Companies are still evaluating business cases, and the cost of models will increase over time.
- Is Edge Computing a solution looking for an app? Does a delay of a few seconds for a round trip make consumers less willing to spend more? Are we confusing edge storage with edge computing and treating all those applications the same?
4. What about the sunk costs of centralized data centers? Will they be used poorly now or end up just storing unimportant data? If Edge Computing is all about Real-Time, then sliced 5G could be a key element of the solution. If so, can a sustainable business model be built between telcos and advertisers.
These revelations will soon come to light. As the space evolves further, it will become more and more clear how AI/ML technologies will rearrange the new world order. This will likely define new positions for service providers, their alliances with solution providers, and hybrid business models.
The AI/ML hybrid will eventually settle on a unique landscape that will drive consumers and users alike over the next decade.