As more organizations look to transform their operations and processes, making progress on their intelligent enterprise journeys, it becomes more important to understand the how and why behind smart applications. Two such technologies include the Internet of Things (IoT) and edge computing. SAP is focusing on both in its SAP IoT and SAP Edge Services offerings.
ASUG sat down with the authors of “Internet of Things With SAP: Implementation and Deployment” to help SAP customers understand both IoT and edge computing, learn about the SAP IoT portfolio, products, and capabilities in detail, and gain an awareness of real-life IoT use cases. The three authors—Sijesh Manohar Valiyaveettil, VP in IoT product development at SAP Labs, PVN PavanKumar, director of IoT product management at SAP Labs, and Shyam Ravindranathan, director of product management in IoT at SAP Labs—discussed the ins and outs, as well as provided tips and tricks in how to start, manage, and understand IoT and edge computing.
Sharon: Can you give us a high-level overview of the Industry 4.Now initiative and the role played by intelligent technologies such as IoT and edge computing in helping companies run an intelligent enterprise?
Shyam: Industry 4.Now is SAP’s answer to the Industry 4.0 transformation program, which is referred to by different names across the globe. It brings together business expertise, software solutions, technology, and ecosystem participants to support customers on their journey to Industry 4.0. The main four themes for Industry 4.0 are intelligent assets, intelligent products, intelligent factories, and empowered people.
The Industry 4.0 themes are enabled by SAP technologies, of which SAP IoT and SAP Edge Services are the key pillars. SAP IoT capabilities are natively embedded into SAP business applications, and it also provides capabilities to extend existing business processes and applications (such as SAP S/4HANA) with IoT capabilities. SAP Edge Services allow specific SAP business processes, applications, and services to run at the edge for near-real-time processing close to the source of data, at low latencies, and in disconnected remote environments.
This book explains how SAP IoT and SAP Edge Services integrate with the SAP Industry 4.Now portfolio of business applications, as well as the common use cases and implementation strategies.
Sharon: Thank you for that high-level overview. Can we dig in a little bit and uncover what is SAP IoT and what is SAP Edge Services? What are the capabilities and practical use cases for each?
Shyam: The SAP IoT product portfolio offers products and business services in the cloud and at the edge, providing necessary capabilities to build end-to-end, IoT-enabled business solutions. The SAP IoT stack in the cloud, which is all about business outcomes, provides business services and capabilities by consuming time series data contextualized with business process data (master data and transactional data).
First, we embed IoT into line-of-business (LoB) applications, such as SAP S/4HANA or SAP Digital Supply Chain, so that customers can benefit from the IoT-enabled intelligent enterprise suite or Industry 4.Now applications. And second, SAP IoT enables customers to extend existing SAP business processes by gaining information and insights from previously unconnected devices (machines, products, assets, etc.), thereby extending the value of existing SAP applications and processes. We do it by associating and analyzing it with relevant business context, which is a key differentiator for SAP.
For example, let’s look at this through the lens of a replenishment scenario. Think of a silo or container with some raw material in it and which is equipped with an IoT sensor to measure the fill level. The sensor typically sends just the distance from the sensor to the surface of the material. But to have a business outcome—for instance, automatic replenishment—we need more business context. We need to know things like what’s the material in the silo, as well as what is the plant and storage location. It’s really the business context that enables us to automatically trigger a purchase requisition in an ERP system or automatic stock correction in SAP S/4HANA.
Another example could be through the lens of a predictive maintenance scenario. The raw sensor data you would typically receive from an asset are readings of temperature, pressure, vibration, electrical current, and so on. But that raw data on its own is, again, meaningless. You need to know which asset is sending this data, what are its specifications, and which customer is operating the asset. Only by associating the sensor data with this business context can we turn it into meaningful data and, for instance, compute a health score and trigger a service call for the customer.
SAP Edge Services, on the other hand, allow powerful microservices to be deployed at the edge, but orchestrated from the cloud to extend the processing power and business processes to the edge, even in conditions with intermittent connectivity, reduced bandwidth, and high latency. For example, SAP Edge Services in oil rigs enables intelligent data processing correlated with business data from SAP Plant Maintenance and inventory systems for streamlined maintenance operations.
Sharon: What is required to develop IoT applications and how do you manage them?
Sijesh: IoT applications need certain generic key capabilities, such as the ability to collect, stream, process, assign business context, and offer tiered storage to manage large amounts of IoT data from sensors. SAP IoT products provide these key capabilities, making it easier to develop IoT applications quickly.
For example, SAP IoT provides the time series storage of sensor data with certain out-of-the-box aggregations that can be used for quick calculations and comparisons, rather than having to develop them from scratch. SAP IoT provides most of these capabilities as a managed stack where the ingestion and storage of sensor data is provided. The customer or partner do not have to deal with this complexity and can purely focus on the functionality and management of the custom IoT application they develop. SAP IoT supports multitenancy, which allows manufacturers and service providers to build software-as-a-service applications for their customers.
Sharon: How do you create digital twins and perform modeling using IoT? What are the benefits of doing so?
Sijesh: The common thread for Industry 4.0 with respect to IoT as a technology foundation is the digital twin. In simple terms, it is a digital representation of a specific asset, product, or machine characteristic.
In the context of SAP business applications, the underlying data model of the digital twin can be different for different LoBs or industries, as it is unique to the domain or specific use case. For example, if it’s an asset-intensive scenario, then SAP IoT can integrate with the SAP Asset Central data model. If the user wants to build a very niche custom application, they can opt to do the same with SAP IoT's modeling capabilities from scratch. There is a chapter in the book that covers the modeling capabilities of SAP IoT in detail.
Sharon: Can you define rules and actions as they relate to IoT and explain how to create and use them for business outcomes?
PVN: One of the common use cases in IoT is to look for anomaly patterns in IoT data and act upon it. The products SAP IoT and SAP Edge Services offer this capability via rules and actions. Rules play a major role in identifying anomalies from the sensor data stream. SAP IoT provides comprehensive rules, events, and an action framework that defines the business logic required to turn sensor data into business action.
Certain IoT actions might need an end user to make data-driven decisions for which SAP IoT offers decision support services. This action is configurable to include possible decisions and contextual business data that would be presented to the end user to help them make an informed decision.
Key capabilities of IoT rules include fast processing of streaming rules in the ingestion pipeline, complemented with rules processing on persisted data with time windows and scheduling.
Sharon: Can you give us a high-level overview of the steps required to develop IoT application extensions using SAP Web IDE and APIs from SAP IoT? What are the benefits of doing so?
PVN: The very first step is to understand the requirements for the extension of the existing business scenario and the benefits that IoT would bring to the scenario. Once this is known, list the sources of sensor data, additional calculations that might be required, and the related business entities. SAP IoT along with SAP applications, such as asset management solutions, provide the mechanism to model the scenario. The book explains this with a sample scenario and how it can be modeled in SAP IoT.
Simple extensions to the existing business scenario can be accomplished using SAP IoT configurations—for example, a rule to monitor sensor data to trigger any further action in the business application. Sometimes it is necessary to build an end-user application, as well as to visualize IoT data. The book explains how using SAP Web IDE and SAP IoT APIs, one can build a custom IoT application. The easiest way is to get started by using SAP IoT-provided starter SAP Web IDE templates to quickly develop the IoT application and further tweak the generated application.
Sharon: Can you walk us through the steps of configuring SAP Edge Services to solve a business challenge?
Shyam: One of the business challenges that SAP Edge Services addresses is the need to process IoT data at the physical location where the sensor data is generated to fulfill the important requirement of near-real-time response to machines or automation systems. The design time configurations of the processing logic on IoT data, such as a rule condition or machine learning model, is done centrally in the cloud and deployed to the different physical locations or edges.
SAP Edge Services facilitates this central configuration and deployment of this processing logic on the edges with the policy service application in the cloud. During runtime, the designed rule or the machine learning model is executed on IoT data at the edge.
Sharon: Can you give us an example of a cloud-to-edge hybrid use case and how to configure it?
Shyam: Let's imagine a company "XYZ" manufacturing and providing sterilization of equipment as a service. Their customers can vary from medical institutions to food and beverage manufacturers. They might have a central collection and processing factory where they offer this service to their customers. Even though the business is focused on providing the sterilization service, their core competency is manufacturing and operating equipment to do this service efficiently.
Certain customers might want the capability to quickly sterilize a limited amount of equipment as needed without having to send it to the central processing factory. The company then leases out sterilization equipment to these customers for them to be able to do this on site. This product-as-a-service model warrants that company XYZ is still able to monitor the equipment to service any maintenance issues and to note the usage of the equipment to invoice their customers. Using SAP Edge Services at the on-site locations integrated with and orchestrated from SAP IoT cloud running at the central processing facility, company XYZ will be able to monitor, service, and run its equipment and operations seamlessly.
Sharon: Can you define interoperability and discuss the difference between cloud-to-cloud and cloud-to-edge?
Sijesh: SAP IoT offers customers a managed solution including device connectivity, ingestion, and data storage, as well as higher order business services and capabilities that are integrated with SAP business solutions such as SAP Intelligent Asset Management, SAP S/4HANA, etc. Nevertheless, SAP understands that customers might already have their own components or third-party components for device management and connectivity that they would want to integrate with SAP IoT and SAP business applications.
In the cloud, SAP enables out-of-the-box integration with specific third-party IoT cloud connectivity offerings to integrate with SAP IoT. In such a scenario, SAP IoT will provide the complete set of IoT capabilities other than device management along with integration to SAP business applications. This is the cloud-to-cloud interoperability concept.
Cloud-to-edge interoperability has cloud and the edge components work in an orchestrated fashion to achieve business outcomes. For example, the end user can define a rule and choose to run the same rule in the cloud or at the edge, depending on the use case and business need. In addition, the configuration of all artifacts will remain centrally in the cloud and be deployed to the various edge nodes, facilitating seamless integration to business applications.
Sharon: Can you give us examples of uses cases for both SAP IoT and SAP Edge Services?
PVN: In this book, we have covered more than 25 real-life IoT projects and prospect customer use cases and how these projects leverage SAP IoT and SAP Edge Services. In addition, we had provided the best practices from these projects from which we also derived an implementation questionnaire that customers can use to start any project with IoT.
Looking at customer use case examples, we covered four different types of cases leveraging SAP IoT and SAP Edge Services. The first is process optimization: Companies leverage IoT to improve their bottom line by automating and accelerating their business processes based on IoT—in other words, process optimization for a step change in productivity. The second is superior customer experience: Companies use SAP IoT to improve their top line by adding new and enhanced services to existing products to achieve superior customer experience. The third is platform business: Companies use SAP IoT to build their own platform business, entering into completely new markets. And the fourth is to extend business processes to the edge: SAP provides intelligent data processing at the edge orchestrated from the cloud. SAP Edge Services runs business transactions correlated with device data, close to the data source at the edge, even in conditions with intermittent connectivity, reduced bandwidth, and high latency.
Sharon: What do you want ASUG members to know about SAP IoT and SAP Edge Services?
Shyam: SAP’s strategy has been to build intelligence into existing SAP enterprise applications with new technologies such as IoT. This is primarily achieved by embedding SAP IoT capabilities natively into SAP business applications and by enabling extension of existing business processes/scenarios in solutions such as SAP S/4HANA with IoT capabilities. The edge and the cloud are two pillars of the SAP IoT portfolio.
IoT data correlated with business process data can run on the edge and the cloud, depending on scenarios. SAP IoT and SAP Edge Services provides value and differentiation by enabling customers to contextualize raw IoT data with business process data and out-of-the-box integration to SAP business applications. This allows SAP customers to focus on implementing software with a focus on business outcomes as opposed to investing in a technical and custom IoT implementation. Customer and partners can also use SAP IoT and SAP Edge services to build custom IoT applications and extensions to suit their specific needs for their industry.
Sharon: Can you summarize this book in a few sentences?
PVN: We’ve organized this book into four parts, starting with an introduction of IoT and edge computing and their relevance. We have consistently tried to explain IoT and edge concepts in the context of enterprise applications and business scenarios. On completion of the book, readers will be able to understand all the necessary concepts of IoT and edge such as detailed functionality, configuration, custom application builds, integration to enterprise applications, and more. It will also educate the reader about common implementation strategies, pitfalls, and several enterprise use cases where IoT and edge solutions can be applied.