IoT Collaboration: The New Power in the Internet of Things

The complexity of IoT implementation and the number of actors involved in end-to-end IoT development have brought new challenges. So you need IoT collaboration.

The increasing complexity of IoT implementation scenarios and the number of actors involved in end-to-end IoT development efforts within a company have brought unprecedented challenges. The scope, depth, complexity, and ubiquity of these challenges are surpassing traditional ways of problem-solving. Further still, the unprecedented nature of these challenges calls not only for new approaches but for a radical rethinking of the entire structures within which IoT development and implementation take place. This is where IoT collaboration steps in.

The rise of collaborative IoT

As the new levels of complexity have changed the nature of IoT project development, so must our ways change. There is an ongoing need to adapt to massive scale-out projects. This calls for the incorporation of an increasing number of experts, decision-makers, and non-technical staff in the IoT development cycle. Further, there is a necessity to build channels of communication that are transparent and accessible to all.

Even more so, IoT development on a global scale requires new modes of collaboration. These new modes of IoT collaboration should enable transversal combinations among the various actors along the value chain. What is needed here is more inclusiveness. This involves a common ground for these actors to convene and a common language that is tangible to everyone involved in the IoT development effort.

A new approach to IoT development should enable all kinds of agents from different fields and levels of know-how to unite their experiences and efforts. We may find ourselves compelled to rethink existing structures, the reasons behind their existence and ways of functioning. As markets change and customer requirements evolve, there is not a single company that is immune to this necessity.

At this juncture, there is a need to think of the kinds of issues we are led to encounter in IoT development and to articulate across the various stages of the IoT development cycle. And this rethinking takes place not within the confines of an individual function or an isolated quandary but from within a mode of togetherness. The treatment of bottlenecks in IoT development calls for dialogue and collaboration across company functions both horizontally (addressing different development stages across the value chain) and vertically (addressing different levels of decision-making).

Collaboration in IIoT now

The turn towards collaboration in IoT is a relatively new phenomenon, best encapsulated in the term C-IoT (Collaborative Internet of Things) coined by Behmann and Wu in 2015. Here the focus is on a collaborative intelligence that improves lives and organizational efficiency, “breaking down the barriers between traditional vertical markets and supply chains”.

The necessity to collaborate on a variety of levels in IoT project development has also been recognized by recent communications by the European Commission. For example, the founding of the Alliance for Internet of Things Innovation is one aspect of the effort to strengthen the collaboration among IoT players in Europe and foster a dynamic European IoT ecosystem. Such initiatives call for open industry collaboration and encourage “novel and radical system concepts that break the current business ecosystem with early market experiments in an internet-economy way.”

According to a recent EC publication called “Internet of Things: The Next Revolution. A Strategic Reflection about a European Approach to the Internet of Things”,

“IoT systems will need to meet stakeholder aspirations over entire value chains … New models of collaboration and cooperation enabling cross-value-chain approaches are needed.”

Towards a culture of co-creation

And just as connected IoT devices cannot operate in isolation, the IoT engineers, developer teams, data scientists and business analysts responsible for the creation of these networks need a common ecosystem to interact and co-create. In focusing on collaboration and connectivity, IoT is then not only pushing the boundaries of innovation but is also working towards the bringing together of teams within an organization, across companies, and even teams from different industries together within a single ecosystem.

Within industrial settings today, essentially we have two major actors involved in IoT development initiatives. These are the engineer and the data scientist. Yet even among these two essential types of actors, there is a lot of miscommunication and gaps in the established processes. This ultimately leads to delays in IoT development and implementation. We describe this difficulty in the article “The Engineer and the Data Scientist: The War of the Worlds in IIoT ”. And beyond that, throughout the entire IoT development cycle, there is a lot more complex picture to consider.

The rise of the IoT platform as a new collaborative paradigm

In recent years, we have seen the rise of a new phenomenon as part of C-IoT. This is the IoT development platform operating both at the edge of an IoT network and in the cloud.

Following the rise of cloud computing as a centralized model, we now have the requirement for a “distributed core” dealing with real-time data processing. In many implementation scenarios, IoT devices cannot afford to wait for a response from a centralized cloud infrastructure. Time-criticality is written large. You can read more about this shift in our article “The Future is Decentralized: IoT Edge Computing as Key to High-Speed IoT Development”.

How do we contribute to this development? The strategic aim of our IoT development platform is to foster non-hierarchical interaction. This also entails fostering modes of self-organization between the various actors across the value chain. Being inclusive at its core, it brings in everyone involved in the IoT development process within a single venue. This is how the free exchange of know-how works. Stakeholders benefit from increased transparency across processes, and shorter decision-making paths are enabled with one solution. The stakes?

“With our IoT development platform, we bring IoT and machine learning together in one ecosystem that extends from the edge to the cloud.”

In doing so, we offer a complete IoT solution to be deployed within organizations of any size. However, this new organizational model is not that of a “single source of truth”. It is best described as a “collective agency”. On the platform, collective agencies are formed around a common development initiative or an implementation difficulty to be dealt with. Each group may consist of IoT engineers, data scientists, business analysts, management representatives, and many other technical or non-technical participants.

One IoT platform to unite all functions

To navigate a complex and often fragmented IoT landscape, an IoT platform must enable people to convene at a single venue while adhering to robust security standards that protect user data, device data, and intellectual property. To this end, the Record Evolution platform has introduced highly granular user privileges and a robust authorization structure. You work in an environment that is completely secure, with clearly defined role assignments.

At the same time, the platform has been conceived as a hub for everyone working with data. You work from within your personal profile with social media features. Here you can follow the work of your peers. You can also request access to particularly exciting public projects within the community. You can convene with developers from across the globe and jointly work on a swarm or a data pod.

And this is how the four types of actors in the IoT development cycle benefit from the unified IoT development platform:

Engineers

Work with the programming environments (C, CODESYS, etc.) and protocols (Modbus, IO-Link, PROFINET, CAN bus, etc.) of your choice to make data available to data scientists;
Monitor and manage IPCs and applications from a central location;
Use the devices and sensors that convince you.

Data scientists

Develop ML models in integrated workbooks with native PostgreSQL or Python based on the data collected by engineers;
Make ML models and artificial intelligence available to engineers for IoT application use on IoT devices;
Create automations quickly and easily.

Business analysts

Integrate sensor data into the tools of your choice and enrich them with additional data;
Develop custom queries on data models using PostgreSQL or Python;
Generate analyses and live presentations intuitively;
Provide data scientists and managers with customized analyses and dashboards.