It’s wise to invest in intelligent edge for multi-fold business benefits from IoT

If data is the new oil of the 21^st century, then in this analogy, “IoT Edge” is the oil field extracting that oil (data) from the physical world. IoT Edge enables organizations to extract raw data from the underlying asset and pass it to the right refinery i.e. an ML-based application. So, wise businesses are using the squatting strategy of deploying IoT Edge on as many manufacturing assets as possible, with some quick use cases and then extracting more and more data from those edge systems.

Importance of IoT Edge

Edge computing will undoubtedly provide multiple business benefits to organizations. Forbes has named edge computing as one of the top trends for digital transformation in 2018.  To understand the importance of IoT Edge, let’s review the place of Edge in the IoT architecture components:

• Business Application: These enable responses and even predict the business events by the processed IoT data coming from the Edge;
• IoT Cloud: It receives and stores data from Edge systems or devices, processes the data, helps onboard devices, and manages devices throughout their lifecycle;
• IoT Edge system: This system connects with the underlying asset to extract data, process the data locally, take autonomous decisions, and on the other side uploads data and actionable events to the IoT server.

With configurable and expandable IoT Edge system, IoT data can be sent to any or even multiple IoT clouds that can be processed by potentially any application. With this intelligent Edge serves tremendous potential benefits for the edge owner.

IoT Edge at the center

• IoT Edge must provide multiple ways to connect with the underlying assets. This connectivity is going to be a major part of the cost of the IoT project as manufacturing assets offer limited connectivity options, and Edge must offer standard interface options to extract data easily with as little investment as possible – from the existing PLCs, CNC, motion sensors and gateways.
• IoT edge processes the extracted data before sending it to the IoT server. It generates events and processes those events with local rules. IoT Edge must provide options to configure these processing rules locally, and even centrally, to minimize the cost of maintenance.
• On the other side, IoT Edge sends data to the IoT server. IoT Edge should allow configuration to the IoT server(s) to send data in addition to the primary IoT server.
• Security and administration. IoT edge must allow handling this centrally to minimize the cost of the upgrade.

If the above four functions are established successfully for the initial set of applications, then Edge can be configured or extended to supply data to any new application. Let’s say a manufacturer deploys Edge sensors on all machines for production monitoring, the same Edge systems can then share the data with quality systems to track the rework and rejects, and then further share asset health data with the assets maintenance team. Cutting down the cost of data collection and deployment time to fractions.

Expand the scope of business benefits reusing the extracted data

Capgemini developed the edge solutions keeping these points in mind to help manufacturers and hence we could easily expand and configure same “FD4 IoT Edge” for asset health monitoring, for visual inspections for Quality and for the predictive maintenance use case in a very short time.

Edge features enabling incremental exaction data out of the asset

Capgemini “FD4 IoT Edge” offers following high level that allows expanding business benefits with ease. Following are the pointers to some of the work being done in those respective areas by leading product vendors and researchers.

Agility of device configuration

ScienceDirect’s 3^rd Workshop on Internet of Things published a paper on “AGILE project” that aims to create IoT Gateway technologies that support local management of devices and data, application development and includes security features that allow users to share data in the trusted way. More work is expected to happen in this space:

• To configure connectivity options with the local machine;
• To build a trusted network of IoT server or parent device and peers to operate with;
• To configure events;
• To offer “freedom zone” or autonomy to operate for a device;
• To configure the escalation mechanism.

Machine Learning

Microsoft talks about Waves of Innovation on the Edge defining what intelligence is needed on the edge.

• Provide intelligent inputs to the cloud systems to learn from;
• Collective learning – ability to use the past learnings by similar devices.

Ability to operate autonomously in both connected and disconnected state

Forrester’s report, Make Room for The Autonomous Edge in Your IoT Strategy underscores the importance of autonomous Edge devices. Recently at Microsoft Ignite, an annual 2018 user conference for IT professionals, Microsoft demonstrated their capability for edge devices to operate disconnectedly from the internet for extended periods with the public preview of Azure IoT Edge extended offline.

• Edge devices should be able to be in a disconnected state and sync up again once connected.

Remote administration, monitoring, and support

Microsoft has rolled out capabilities extending operator capabilities to the IoT edge. Amazon has rolled out products promising ability to manage millions of devices to ensure that devices are working properly and securely.

• Remote device onboarding, firmware upgrade, remote access, and remote configuration.

Connectivity options to integrate with manufacturing world comprised dated and protected/locked controllers.

• Offers connectivity to manufacturing assets with wired and wireless modes, provides connectivity with OPC-UA and other industry standard interfaces.

To learn more about how you can get the IoT Edge advantage, feel free to connect with me.