Successful IoT business: just a question of standards?

There are days the little things in life make me happy. When my microwave broke last week and even a repair couldn’t save it, it took me less than five minutes to solve the problem: simply selected a new model on the manufacturer’s site using my smartphone, ordered it and paid via PayPal. Three days later it was unpacked, plugged in and running. The ease of this process illustrates two things:

  1. digitization makes it incredibly easy for us to handle even extensive processes quickly.
  2. I didn’t ask myself whether the microwave would also fit into my power socket and whether it would meet the usual standards for radio interference suppression, hazardous substances, etc.

Anyone who has ever traveled abroad knows that this lack of concern is not a matter of course. In the case of power sockets, the right time was simply missed to ensure global standards. In the meantime, the implementation of a standard would cause so much cost and electrical waste that it is no longer practicable.

Unimaginable that something like this could happen again to our highly developed society… or could it?

Digitization is opening up new business potential. The focus is shifting from the exchange of physical goods to the exchange of information. When I buy my microwave, it’s not just the manufacturer who earns money, but also the online payment service PayPal. And that is solely through the exchange of information. Digitization is also creating the basis for new business models in industrial companies. This is shown by a recent study by Sopra Steria and the F.A.Z. Institute. More and more machines and systems are being networked via IoT platforms in the industrial Internet of Things in order to determine performance data or offer product-related services. This is a development that has taken hold around the globe and is thus giving rise to many solutions with different data models and integration options. This allows us to draw a worrying parallel to the connector mess mentioned above. Companies that want to drive their digital business forward quickly lose their orientation here when choosing an IoT solution that is suitable for them. After all, how future-proof it is depends largely on how well it can be connected to other systems and data sources.

Global standards for sustainable digitization

Serious initiatives here give hope for an international standard in the industrial Internet of Things. The Plattform Industrie 4.0, for example, has developed the concept of the management shell, which is to be understood as the digital representation of a device. It makes it possible to address machines with all the necessary information and functions. For example, I could develop an app for my microwave, interact with it, display the instructions for use, and set the power intensity or duration via smartphone. If the manufacturer of my washing machine also provides the information and functions of this device according to the management shell concept, it is no effort for app developers to integrate other devices into their application. This manufacturer- and system-independent interoperability paves the way for the future of Industry 4.0.

AI – Where we are in the Hype Cycle and how it continues

While the artificial intelligence index shows that the increase of research articles and conferences in the field of AI continues, the media is slowly showing some fatigue in the face of the hype. So it’s time to take stock: What has been achieved? What is practically possible? And what is the way forward?

What has been achieved?

In the years 2018 and 2019 the previously developed methods for the application of neural networks (this is how I define AI here) were further refined and perfected. Whereas the focus was initially (2012-2016, Imagenet competition) on methods for image classification and processing and then on audio methods (2015-2017, launch of Alexa and other language assistants), major advances in text processing and generation were made in 2019 (NLP = natural language processing). Overall, the available technologies have been further improved and combined with a great deal of effort, especially from the major players (Google, Facebook, OpenAI, Microsoft).

What is practically possible?

The use of AI is still essentially limited to four areas of application:

  • Images: image recognition and segmentation
  • Audio: Conversion from speech to text and vice versa
  • NLP: word processing and generation
  • Labeled Data: Prediction of the label (e.g. price) from a set of features

This list is surprisingly short, measured by the attention AI receives in the media. The most impressive successes of AI, however, result from a combination of techniques such as speech assistants using a combination of audio, NLP and labeled data to convert the input into text, recognition of text intention with NLP and prediction of the speaker’s wish by using huge amounts of labeled data, meaning previous evaluations of similar utterances.

Decisive for the development of precisely these AI application fields were

  1. the existence of large quantities of freely available benchmark data sets (data sets for machine learning) on which algorithms have been developed and compared
  2. a large community of researchers who have jointly agreed on the benchmark data sets and compared their algorithms in public competitions (GLUE, Benchmarks AI, Machine Translation, etc.)
  3. a free availability of the developed models, which serve as a starting point for the practical application (exemplary Tensorflow Hub)

Based on these prerequisites one can quickly assess how realistic some marketing fantasies are. For example, there are neither benchmark data sets nor a community of researchers for the often strikingly presented field of application of predictive maintenance, and accordingly there are no models.

What’s next?

On the one hand, it is foreseeable that the further development in the AI area will certainly continue initially in the above-mentioned fields of application and continue to develop in the peripheral areas. On the other hand, areas are emerging which, similar to the above-mentioned fields of application, will be driven forward at the expense of large public and private funds (e.g. OpenAI and Deepmind are being subsidised by Elon Musk and Google with billions of euros respectively). An example of large investments in this area is certainly autonomous driving, but also the area of IoT. In total, I see the following areas developing strongly in 2020-2022:

  • The combination of reinforcement learning with AI areas for faster learning of models
  • A further strengthening in the area of autonomous driving resulting from the application and combination of AI and reinforcement learning
  • Breakthroughs in the generalization of the knowledge gained from image processing to 3D (Geometric Deep Learning and Graph Networks)
  • A fusion of traditional methods from statistics with neural networks
  • IoT time series (see below)

I see a big change coming with the rise of IoT and the associated sensor technology and data. By their very nature, IoT data are time series that must be filtered, combined, smoothed and enriched for evaluation. Relatively little specific has been done to date for this purpose. It could be that from 2020 – 2022, this topic could hold some surprising twists and breakthroughs for us. German industry in particular, which has benefited rather little from the initial developments in the field of AI, should find a promising area of application here.

#workfromhome – How does our software development work together now?

At CONTACT we believe that personal and informal interaction of people is an important success factor in complex technical projects – and without doubt this includes the development of our own software products. We therefore attach great importance to giving our teams the opportunity to meet with their colleagues in their offices, our meeting rooms or in places like the “Red Sofa”. All this came to an abrupt and hopefully temporary end through Corona.

Home office for everyone
After initial preparations in the days before, CONTACT decided over the weekend of 14-15 March to let all employees work from home. In contrast to many of our customers, “Work from Home” meets particularly favourable conditions at a software manufacturer: There is no production where material has to be moved, and software as a “virtual” product can in principle be processed anywhere in the world.

As an IT company, we naturally have a suitable and efficient technical infrastructure, and apart from a few necessary hardware transports of workstations, screens and so on, the software development and also the other areas at CONTACT were ready for use in less than a day.

In addition to our headquarter in Bremen, we operate development sites in Munich, Cologne, Paderborn and Stuttgart and frequently work together with external partners. That’s why means of communication such as e-mail, telephoning via Voice-over-IP, Microsoft teams and so on are an daily routine for our technology-aware software developers anyway.

What really holds our development together, however, are the common processes and procedures, and the associated systems. The most important business platform is our in-house installation of CONTACT Elements, or CEDM for short. Everything we do converges there, and all other IT systems are connected to CONTACT Elements.

CONTACT Elements’ Activity Stream enables us to share information and documents quickly and efficiently.

Products
Each software component of CONTACT Elements is listed as a product in our Elements in-house installation. We manage the source code of our business applications in Git or Subversion repositories, which are linked to the product object. Errors or change requests for the software products that arise from the field are managed as “Change Requests” in Elements. If these lead to code changes, a direct link is created between a change request and a source code change (a “commit”) in Git or Subversion. Of course, we also keep a list of product releases and their maturity level in CONTACT Elements.

Our development processes are highly automated and, by nature, completely digital. We operate many other systems that automatically build, test and measure software. All these systems are directly or indirectly connected to CONTACT Elements.

Every hour that a developer spends maintaining or further developing a software component is recorded in CONTACT Elements. This way we always have an overview of the extent to which we invest in software components and what the maintenance costs are.

Projects
Our development methodology combines several agile methods with extensions specific to our company. It is called “Revolution” and is stored in CONTACT Elements by templates for projects that can be adapted by “Tayloring”. In “Revolution” there are also a number of deliverables, which are defined in CONTACT Elements as documents from templates. We create requirements as specifications in CONTACT Elements’ requirements management. Project planning is done in iterations, which are planned and processed with task boards.

Task board for a current development project at CONTACT.

As a result, all information that is important for our development can be found in one system and linked together. All employees are well acquainted with the terms, are able to access the relevant information at any time and are guided by the systems to the right next activities.

Conclusion
In the current crisis, this system and process landscape creates trust and the ability to act. It has enabled us to switch to remote work practically from one moment to the next without any distortions. In addition, thanks to the willingness of our staff to change and the already existing tendency towards technical tools of communication, we have succeeded in shifting personal interaction and meetings to the Internet via video chats and web conferences.