Europe Union

SIN-On: Seamless IoT Node Onboarding Application Tool

SIN-On is an onboarding toolchain for IoT Nodes (based on STM32WB55 microcontrollers) designed to be seamless and user-friendly (the user requires NO technical knowledge). It makes the deployment of sensor networks quick and easy.

Key motivations for SIN-On

The toolchain has a management layer in the cloud that is used to manage sensors’ configuration (e.g. sampling frequency). Hence, with some simple operations, the user can decide which sensor has to return its measures and at which frequency. This, in terms of time, is really efficient because the user does not have to “manually” add this information in the configuration files of each sensor and neither re-program the microcontroller to get the actual data.

The tool at the backend manages these operations, reducing the time requested for a single operation. This backend system is based on HTTPS protocol, allowing to easily communicate with each sensor that has subscribed to a specific topic where the messages arrive. The connection between the gateway and backend can also be based on MQTT. In doing so, it can communicate with many sensors at the same time, instead of sending one message to each one of them individually. Hence reducing the response time of the system. In fact, without this tool,the user would need to program the microcontroller to read the data from a specific sensor. Moreover, the user would need to manually set-up the communication interface between the data provider and consumer, which is being automatically orchestrated now. This manual process, taking into account all of the sensors individually, would be time-consuming and possibly frustrating.

State of the art

It is estimated that by 2026, over 64 billion devices will be a part of the IoT ecosystem. As the number of IoT devices grows, the need for integrating the new devices into the IoT network poses several challenges. For instance, Derhamy et al. evaluated the existing IoT frameworks against criteria such as security, protocols, rapid application development support, hardware requirements, architectural approach, interoperability, industry support etc. They found that there is a need to develop a more advanced framework and tool that would help businesses to quickly and seamlessly integrate new IoT nodes/devices into their existing system or IoT Infrastructure. Although Derhamy et al. deduced this in 2015, not much progress was done in this domain as confirmed by Paniagua and  Delsing in 2021. 

The solutions which already existed prior to the development of SIN-On were limited by some or other barrier. Some of them were limited by the number of devices that they could onboard, whereas others were either limited by the type of devices they could onboard or some other dependencies such as manufacturing or distribution. For SIN-On the theoretical limit is known and ranges in a few hundreds of sensors per gateway, however the practical limit is a bit lower. There was also a lot of manual effort required from the user, or a specialist was required each time a new node had to be onboarded to the existing system. Compatibility issue was also quite common in most industries. This amounted to higher cost, and lag time, which was not so beneficial for the businesses.

Hence the main motivations for the development of SIN-On were as follows:

  • Reduction of the engineering costs related to the deployment of wireless sensor network
  • Reduction of involvement of specialists/services personnel 
  • Automated handling of devices credentials throughout the toolchain
  • Ability to remotely manage sensors and gateways
  • Smooth and continuous diagnostics
  • Compatibility/Integration with a larger ecosystem achieved through the Arrowhead Framework

What are the challenges of onboarding new nodes?

The future of IoT

The Solution: How does it work?

The credentials of a node (stored in the secure memory of the Hardware Security Module) are scanned through a phone’s NFC, which takes the user to the onboarding web-app. The onboarding app (after logging in) asks for the name of a node, the gateway to which it should be onboarded, and one of the preset configurations to onboard the node. After that, the data are sent to Cloud Management Interface, which passes the configuration to a particular gateway. The gateway starts to look for the unpaired nodes, and once the node is powered up and in range of the gateway, they pair together, the gateway sends the configuration to the node (through GAP GATT REST API), and the node starts providing the data. The data are passed to influxdb and visualized in real-time. 

This onboarding toolchain makes deploying new sensor networks easily manageable, configurable, and secure. It is compatible with your own embedded or cloud solution, where the measurements can be processed on board or via a distributed application.

IoT Node

  • Expose UUID for the onboarding process.
  • Look for field gateways during the operation.
  • Fetch the configuration.
  • Read data from the attached sensors (through one of the physical interfaces).
  • Provide the certificate to prove its identity.
  • Assure two-way communication with the field gateway (to assure that the data have been received).

Field Gateway

  • Aggregate nodes within a single IoT cloud.
  • Provide configuration for the nodes.
  • Exchange data with the management infrastructure (through the Internet, GPRS, NB-IoT).
  • Authenticate new nodes.
  • Monitor the status of the nodes, and access token expiration dates.
  • Provide its identity on demand.

Mgmt Infrastructure

  • Update the list of admitted nodes for particular field gateways.
  • Manage multiple IoT clouds.
  • Dynamically configure nodes.
  • Manage firmware updates.
  • Visualize the data.
  • Serve as a connection to data storage.
DAC Logo

Example Application.

BARTI (Balancing Automation of Returnable Transport Items) is a decentralized IT solution for the smart balancing of Returnable Transport Items (RTIs). The solution’s goal is to improve the circulation process of RTIs to reduce the physical turnover of packaging and documentation by digitizing the flow of information.

BARTI fosters an ecosystem for balancing RTIs among all the stakeholders involved in an operation. All the updates related to balances are stored in a smart contract on the Ethereum-compatible blockchain. To increase the user experience, BARTI also features a filtering mechanism on a map, where all the ecosystem participants are shown with their balances.