About the AIoT User Group

Welcome to the AIoT Playbook! Let`s start by looking at the following questions: How did we get here? What do we mean by smart, connected products (and solutions)? What are the key plays of the AIoT Playbook? And how to best read the book?

About the AIoT Playbook and the AIoT User Group

In January 2020, a hand full of senior IT experts and enthusiasts from different companies met at the Bosch Connectory in Stuttgart to exchange their experiences and views on AI and IoT. AI was at the peak of a new hype, fueled by Alpha Go, advancements in autonomous driving, and not to forget about Cambridge Analytica. The general feeling was that - with the exception of autonomous driving - AI had not really arrived in the world of IoT. Sure, every IoT article or presentation in the last 10 years had mentioned predictive maintenance, but in reality many IoT applications were still much more basic. So how could one better utilize AI in the world of physical products, manufacturing, and equipment operations? The workshop was organized as an open exchange, with a mixture of presentations and group discussions. After three days, there was so much excitement about the topic and the way collaboration in the group worked, that it was decided to make this a regular thing. The result was the formation of the AIoT User Group, a loosely coupled, non-profit network of AI and IoT practitioners, who work together to exchange experiences and best practices on the application of AI in the IoT. Throughout 2021, local chapters were set up in Singapore (special thanks to CK and Thomas!), Shanghai (Nǐ hǎo, Gene and Cherry!) and Chicago (hi Fermin and Hans!).

Picture: First AIoT User Group meeting, with practitioners from Accenture, Bosch, Clariba, Deutsche Post, Evaco, mm1, Opitz, Recogizer, TH Köln and Tomorrow Labs, at the Bosch Connectory in Stuttgart.

Over time, it became clear that it would make sense to document the collected wisdom in a good practice framework - this is how the AIoT Playbook started. Content creation is driven by experts in different domains (see the AIoT Expert Network). The AIoT Editorial Board provides strategic guidance and management support. The basic working mode are so-called Unplugged-Sessions, where the real work on the Playbook is happening. All the material is developed as open source content (using CC BY 4.0), and is also used as foundation for different AIoT-related training courses.

If you are interested in joining the AIoT User Group, good starting points are the website aiot.rocks, as well as the AIoT User Group on LinkedIn. The main site for the AIoT Playbook is simply aiotplaybook.org.

If you are reading the AIoT Playbook as a PDF or on an eBook reader, you might sometimes find that not everything is perfect, like in a fully edited book. The reason is that the Playbook is constantly evolving, and so the decision was made to use a Wiki as the foundation for the playbook. The other book formats are derived as snapshots from the wiki, and the conversion is sometimes not perfect. Also, some content might sometimes still not be perfectly ready. This was a tradeoff between having the perfect book on the one hand, and having an open, digital platform that can evolve over time, on the other. Since the book formats are published in the open access format, this should hopefully also be acceptable to all readers of the offline versions.

Smart, connected products (and solutions)

So what is AIoT all about? Heiko Löffler and David Monzel are Senior Consultants at mm1 consulting and frequent contributors to the AIoT Playbook. Their definition is as follows: AIoT combines AI and connectivity for physical products. These can be new product categories (smart, connected products - short SPCs), or retrofit solutions for existing assets and equipment in the field. The general idea is summarized in the figure below: physical products (e.g. a forklift) are end points with physical components and on-board computing (combining hardware, software and AI). The physical component has a unique identifier and continuously captures status and process-critical data, as well as data about its environment. This data is both processed on the device (e.g. via AI) and transmitted to the cloud/backend via IoT connectivity. The product is integrated with business processes (e.g. warehousing), and solves specific customer problems (e.g. optimizing warehousing tasks). The product is exchanging data in a closed loop with a backend (e.g. cloud or on-premise systems). In the cloud, the data is processed to create a digital twin of the physical component. This is then continuously analyzed by AI to derive and communicate measures or predictions for both the individual physical components and the entire fleet of products. Furthermore, both the physical and the cloud component are integrated with the customer environment to ensure customer-centric value delivery. SCPs become part of the customer’s physical and business processes: They sense and interact with their physical environment and are connected to the customer’s IT infrastructure (e.g. ERP systems). Finally, the product is providing it`s manufacturer with information about the performance of the product in the field, and how customers are using the product. In all of this, AI can enable new functionality either on-board the product, or in the backend. IoT provides the required connectivity between the product and the backend. Digital Twins are a digital presentation of the real, physical product - providing abstraction, standardization and a rich, semantic view on the AIoT data. AI can be used to help create Digital Twins, or to build applications which utilize them. Of course this is a big vision, which will not become a reality for each product category over night. But it shows the potential of AIoT. Also, not all projects might look at such a high level of productization and deep integration - AIoT can also support more basic retrofit approaches (referred to as solutions throughout the playbook).

Why and AIoT Playbook?

How to enable smart, connected products and solutions with AIoT? The AIoT Playbook is addressing this on two levels: First, the AIoT 101 provides an overview of the relevant core concepts and technologies, including AI, data, Digital Twins, IoT and hardware. This helps creating a common understanding and common language in a team. Second, the AIoT Playbook provides a rich set of good practices and templates to help master business strategy, business execution and technical execution for AIoT-enabled products and solutions. These 3 areas need to be closely aligned, which is also supported by the playbook.

Heiko Löffler and David Monzel from mm1 have the following take on this: In the development and operation of AIoT-enabled systems, many new issues have to be considered, especially for traditional product companies. As a result, new competencies and skills must be acquired, which represents a central challenge. The AIoT Playbook gives companies a clear overview of the topics that need to be added to the physical product component in order to identify individual competence gaps. Underlying these, there are then a number of challenges that companies must address to ensure successful implementation. Examples include adapting the business model, building a scalable hardware, software and AI architecture, and transforming sales. The AIoT Playbook specifically addresses these challenge areas and serves as a comprehensive framework for the realization of smart connected products and solutions.

Key Plays of the AIoT Playbook?

The AIoT Playbook aims to support a holistic and realistic approach for creating and operating AIoT-enabled products and solutions, including:

• AIoT 101: Provides common language and understanding of key concepts, including AI, IoT, Digital Twin and Data
• Business Strategy: What is a suitable strategy for AIoT-enabled products and services, addressing the market perspective as well as key internal aspects such as innovation management and target organization.
• Business Execution: From design to procurement and operations - how to execute an AIoT initiative on the business side?
• Technical Execution: From agile to architecture and DevOps - how to execute an AIoT initiative on the technology side?