Edge Ai And Machine Learning On Edge Devices For Real-time Cultural Preservation – Edge Computing’s top predictions relate to technological advancements, hybrid edge-cloud architectures, and impact on industries. The impact of edge computing on blockchain and other digital ledger technologies will become more apparent in a few years. Similarly, it is still too early to predict the impact of 5G on edge computing.

Five predictions for edge computing in 2022 include the spread of artificial intelligence (AI) and machine learning to IoT edge and edge-to-cloud architectures.

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IOTech releases a series of predictions for 2022 related to technology advancements, architectures, and impact on industries.

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The company believes that the impact of edge computing on blockchain and other digital ledger technologies will become clear in a few years. Similarly, it is still too early to predict the impact of 5G on edge computing.

“In the past year, we’ve seen computing move from pilot programs to deployment,” said Jim White, CTO of IOTech. “We believe that 2022 will be the year when edge computing will be fully integrated into the architecture of all major industrial IoT systems.

The new position is that edge systems include AI and machine learning. Simple rule engines and edge analytics are already on the cutting edge. Today, organizations demand more intelligence at the edge. Raw computing used to be the limiting factor for running AI/ML, but that’s no longer the case.

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Training of ML systems will largely be done in the cloud or on-premises, and ML models running on lightweight AI engines are more common and will soon become the norm.

Visual inference is the primary use case, but other AI/ML solutions will soon follow. Edge platform providers will play a key role in developing solutions that easily integrate AI/ML technologies.

It’s not edge computing “or” cloud computing, it’s a case of “sister”. Organizations are finding that edge data processing must be done at the edge and in the cloud or on-premises. While there was initially a lot of excitement about cloud providers reaching the edge, the reality is that there are significant challenges in moving all edge data to the cloud and running all processes in the cloud.

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Data transport costs, latency issues and security/data privacy concerns are the main challenges. Likewise, the raw processing power at the edge and the ability to dig deep into edge data over long periods of time to get better insights means that edge computing is not the only solution. Solutions must address the right processes at the right level, and this requires a hybrid edge-cloud architecture.

The industrial sector is focusing and consolidating to offer new solutions at the IoT edge. Businesses in manufacturing, building automation and smart energy are in full “build” or “buy” mode for IoT edge solutions.

Businesses across many major industrial sectors are fully committed to expanding their edge/IoT products and strategies. Buy mode leaders when companies need to accelerate their digital transformation.

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Companies looking to use edge/IoT technologies are looking for more fully integrated solutions. They want immediate tangible business results and are not interested in receiving a bunch of technology pieces that they then have to assemble themselves.

For system integrators, this means developing the right technology partnerships to pre-integrate and deliver complete solutions to clients. Integrators will naturally gravitate toward edge products that are inherently more open and flexible because they are easier to integrate and adapt to more use cases.

Organizations deploying and deploying IoT/edge applications are finding that Kubernetes doesn’t always fit well in resource-constrained edge environments. Furthermore, the K8s only reflect part of the edge management need. More than container management/monitoring.

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An edge management solution should create, manage, and monitor host edge nodes, allow rapid configuration changes, and also assist in sensor/device enablement. K8s will be part of some Edge Management solutions – where there are more resources or smaller K8s solutions can be implemented (eg K3s).

However, thin, resource-constrained, network-constrained, latency-bound, sometimes non-containerized, environments with touch-and-go OT devices demand alternative and more sophisticated edge management solutions.

Edge solutions don’t start with the choice of IT hardware. They start by identifying the challenge to be solved or the desired outcome and then creating the right system to meet those requirements. As the IoT edge becomes ubiquitous, all layers of the architecture must be an effective part of the solution. IT hardware OEMs need to ensure they have a vision and strategy in the edge/IoT space or risk becoming irrelevant or commoditized to customers.

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The current lack of a digital twin standard hinders adoption and requires organizations to use their own interoperability solutions or lock in a single provider’s implementation. As digital twin technology becomes an increasingly sought-after part of IoT solutions, standards are the next logical and important step to drive innovation.

The need to distribute data with confidence and trust from the edge – and control ownership and distribution given its distributed nature – clearly points to the use of blockchains and other digital ledger technologies. In the not-too-distant future, organizations implementing edge solutions will want to monetize edge data and strive to properly protect, label, distribute, and value edge data.

From an edge platform perspective, 5G provides a larger, stronger, lower latency pipe between the edge and the enterprise or cloud. Because it can reduce latency, 5G can enable more processing in the cloud.

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5G may become more interesting for edge/IoT solution providers as telcos work to deploy private (or semi-private) 5G installations in factories, stores, campuses, etc. way

Supply chain issues and human resources challenges were already on display before the pandemic. Covid has accelerated and exacerbated these issues for organizations. As businesses and industries recover from the pandemic, 2022 may not be back to normal.

Companies should use innovative technologies to overcome the above challenges. This will accelerate IoT Edge adoption. This will be the year when companies move from research and pilot programs to large-scale launches and deployments.

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IOTech’s IoT platforms, Edge Xpert and Edge XRT, enable Google Cloud users to extract and process data from a wide range of OT devices at the edge. IOTech announced that it is expanding its partnership with Google Cloud to offer smart and integrated edge-cloud solutions for enterprise companies. Through this partnership, industrial customers including manufacturing, building automation and smart energy can now deploy smart, code-free and integrated edge-cloud solutions at scale.

This expanded partnership will impact the deployment of Industrial IoT, which comes with some challenges, including OT/IT integration. Northbound communication protocols for Google Cloud are typically MQTT or REST, while southbound communication protocols include Modbus, BACnet, Ethernet/IP, S7, OPC-UA, and others. Other challenges faced by industrial users include the ability to extract data from legacy and legacy IoT devices and control what data is sent to Google Cloud, primarily for security, latency and/or cost reasons. Edge computing capabilities and features are playing an increasingly important role in the Industrial IoT.

The partnership enables industrial customers to deploy a smart, code-free and integrated edge-cloud solution at scale. Edge IOTech experts typically reside at the edge gateway or server level, while edge XRT may reside on legacy or resource-constrained hardware such as MCUs and PLCs that are typically found at the far edge.

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Both platforms come with 20 plus OT connectors including Modbus, BACnet, Ethernet/IP, S7, OPC-UA and more. The platform also includes an SDK that makes it easy for users to create new OT connectors if needed. Seamless data integration with Google Cloud is provided as standard.

“IOTech is pleased to be a Google Cloud Edge ISV Partner. An integrated edge-cloud solution enables faster deployment, reducing downtime. Adding an OT device is enabled through simple configuration and requires no coding skills,” said Keith Steele, CEO of IOTech Systems.

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