the IoT development cycle for IoT and data science

One Development Platform for IoT and Data Science: Discover How

We show how a complete IoT development cycle combines both tangible components such as specific IoT and data science capabilities and intangible components such as the enablement of knowledge transfer and the flow of cross-functional know-how. This transfer takes place within a single, comprehensive IoT development platform best suited for industrial IoT scenarios.

Our proposition: Achieving independence without building a costly in-house IoT infrastructure as the prerequisite for even starting an IoT project involves the bringing together of data science and IoT capabilities on one collaborative industrial IoT platform.

It has been our vision to develop one such platform to facilitate the exchange between these two knowledge domains: data science and IoT. Further, the internet of things platform will not only bring together different types of technology but also people—different types of specialists in different functions within an organization—and with that, different types of mindsets.

Bringing technology and people together for a fully rounded IoT development cycle

It is our understanding that a fully rounded IoT development cycle has both tangible and intangible components. We will be discussing these in the following sections.

The tangible components of IoT development: end-to-end data science and IoT toolchain

The tangible components of IoT development include the complete set of capabilities needed to ensure uninterrupted, full-circle development scenarios together with the iterability of these scenarios. Roughly, this includes the ability to:

  1. connect to and manage IoT devices at scale; 
  2. harvest IoT data from these devices; 
  3. process and analyze that data; 
  4. build apps and models under consideration of that data; 
  5. roll out these apps and models back on your connected device(s), as well as 
  6. continually improve on the apps and models on the basis of newly harvested data.  
Image 1. Showing the fully rounded IoT development cycle from the edge to the cloud

The intangible components of IoT development: knowledge and people

The intangible components within your IoT ecosystem are somewhat more difficult to capture. They involve people in different organizational functions and the transfer of knowledge among them. We speak of intangibility here because this aspect of the IoT development cycle involves the exchange of know-how.

This involves the application of collaborative strategies that differ from one development scenario to another. Across specificities, knowledge transfer takes place in such a way that IoT development in all its complexity can issue forth seamlessly.  

Towards a fully integrated IoT development environment with free collaborative exchange

Both tangible and intangible constituents can be unified in a comprehensive service for the fully rounded IoT development cycle. How are we to imagine this service? That would be a unified, fully integrated IoT development environment. This implies the necessary infrastructure for the management of connected devices, application development, and app deployment. On top of that, we would also have integrations for the collection and analytics of IoT data, plus collaborative capabilities.

The IoT development platform has to be able to support and handle thousands of IoT devices simultaneously. It has to establish and maintain connectivity, with an infrastructure that can sustain a growing number of IoT devices. But one such service will also enable the circulation and free exchange of human capital for human capital, across functions and mindsets, within one single venue. 

This includes the knowledge transfer and collaboration between two specialist groups with distinctly different mindsets: engineers and data scientists. 

Achieving independence without an in-house IoT infrastructure 

A recent article on enumerates the stakes in building an in-house IoT solution from scratch and delves into the complexities of infrastructure challenges. The latter may involve time-consuming and cost-intensive tasks such as scoping the hardware, software, network, and server requirements. It may also involve repurposing resources, not to mention the architecting work itself. 

Managed IoT services are associated with even higher upfront costs. These may involve a local cloud service, an API infrastructure, and several other services. But most importantly, organizations will have to be able to fetch expert help, often externally, to cover all these individual specialty domains. Organizations often do not have all the needed expertise in-house. 

An online IoT cloud platform solution can intervene in constructive ways here in that it takes away the burden of having to set up an in-house IoT infrastructure. An online platform offering would already have a built-in development, deployment, and testing infrastructure. So there will be no need to architect those locally within an organization.

It is our understanding that the IoT development cycle can be covered with one IoT platform solution, where you have the built environment to put together your own solution.

The IoT development studio with data science integrations

The Record Evolution IoT development studio is a fully scalable and lightweight IoT development enabler with a built-in infrastructure for device management, IoT app development, and app deployment over the air. As an IoT self-service platform, it enables users to easily and securely add and manage IoT devices remotely, develop applications in the development platform’s IDE, and deploy code instantly on any number of IoT devices globally. 

The studio is integratable with any platform or data science service for data collection and data analysis. Our in-house solution combines the forces of an IoT development studio and a data science studio to facilitate the creation of multiple IoT solutions for any use case.  

The platform brings data science and IoT together: With the data science studio, you collect and analyze the data coming from connected IoT devices. You also create machine learning models in the cloud. Then you use the IoT development studio to deploy them on IoT devices. The IoT device is sending data back to the data science studio for analysis, allowing for the continuous update and adjustment of machine learning models. IoT development thus comes full circle. 

The fully rounded solution of an IoT studio with integrated data science services offers the following capabilities: 

IoT development studio:

  • Remote management for IoT devices including monitoring, updates, and upgrades;
  • Structuring of growing numbers of smart devices in device groups with their own custom settings;
  • App development in an integrated development environment (cloud IDE);
  • IoT application development using any programming language;
  • IoT product development;
  • Over-the-air (OTA) deployment of your IoT application/logic on IoT endpoints;
  • Bidirectional integrations/application enablement;
  • Support for different industrial devices and protocols;
  • Tangible to both IoT developer(s) and non-technical staff.

Data science studio: 

  • IoT data collection from a variety of heterogeneous sources;
  • Storing and forwarding capabilities from the IoT gateway to the cloud;
  • Data processing capabilities. This helps you handle large volumes of data from ingestion to data cleansing and data transformation;
  • Real-time analytics customizable according to the specific IoT application.

To test these services within the framework of your own IoT initiative or the development of your own IoT product, sign up to connect your IoT devices for free and start setting up your IoT development environment. 

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About Record Evolution

We are a data science and IoT team based in Frankfurt, Germany, that helps companies of all sizes innovate at scale. That’s why we’ve developed an easy-to-use industrial IoT platform that enables fast development cycles and allows everyone to benefit from the possibilities of IoT and AI.