INTELLIGENT GREEN TECHNOLOGY

connected and start understanding how much each one has deteriorated with time,” says Shekhar.

The previous world of high fidelity systems is changing now. The development of edge computing through intelligent and efficient sensors distributed across industrial networks is allowing data processing within the closed network itself. Both network speeds and compute processing have progressed exponentially since the 1940s, when this innovation cycle was first initiated.

But now it is being fed into machine learning algorithms. This is boosting the development of high fidelity models and taking them to the next level of performance.

Bhanu Shekhar, Chief Digital Officer, GE Power Middle East and Africa.

Improvement in network and compute speeds are now allowing vendors such as GE Power to build new strategies. According to this process, select data is analysed through edge devices, that reside on the operational technology side of control systems. Edge devices provide millisecond compute and help to rapidly optimise the asset. The rest of the data that is not required for optimisation of the asset is sent to the cloud for analytics.

“ Some of the information needs to have a feedback loop. You do not want some information to go the cloud, where somebody analyses and then it comes back. A lot of these functionalities are sitting with the edge device, and a lot of analytics are getting built on those edge devices. Whatever is needed to be addressed within milliseconds we put it on the edge device, and wherever it is long term analyses you do it on the cloud,” adds Shekhar.

GE Power’ s strategy, therefore delivers a two-fold benefit for industrial end users. When data is streamed into cloud based analytical applications, they gain from the insights. But the biggest value is the real-time optimisation of the industrial asset, generated by the edge device itself.

The next level of integration is the ability to bring together, high fidelity models of each asset into a much bigger set up.“ Today the biggest value for the customer is can you take these high-fidelity systems which exist, and can you put it so that the whole set up gets optimised,” points out Shekhar. •

Software is often deployed via an agent client installed on endpoints. Some solutions may also include an identity management component that stores device information and device identities.

Connectivity management ensures data flows from the edge to the cloud and is managed and secured in transit with encryption capabilities. This may be limited to IP communication via a cloud gateway, which communicates bidirectionally with endpoints typically through protocols such as MQTT, AMQP, CoAP, or REST APIs. For deployments relying on cellular connectivity, some IoT platform vendors can provide SIM management, including billing and SIM alerts. Partnerships are common in this area to meet the requirements of global deployments running over various communication networks.

Data ingestion, processing, and management. IoT platforms often include rules engines that route incoming data to the correct destination. Typical destinations include storage mechanisms, other applications, or web services. They may also perform basic anomaly detection by comparing incoming data to a set of rules defined by an organisation. Data transformation, aggregation, and enrichment, and complex event processing capabilities may also be included in some IoT platform products.

Visualisation tools and dashboards allow companies to manipulate IoT data or visualise it in real time.

Application enablement is often in the form of APIs to platform services. With APIs fully documented, organisations or third parties can push and customise IoT platform data according to their requirements. Marketplaces are emerging in this area, and partnerships are often localised to a country or verticalised by industry. Some vendors also package application development tools as a standardised platform component.

Advanced Analytics, such as machine learning and predictive analytics tools, are most often not a standard platform component today but offer a differentiation opportunity for IoT platform vendors.

Source: IDC MarketScape, Worldwide IoT Platforms, Software Vendors, 2017 Vendor Assessment.

42 Issue 17 INTELLIGENT TECH CHANNELS