WHAT IS THE INDUSTRIAL IOT?

To understand what Industrial IoT is, let’s first take a step back and explain  in a nutshell what we mean when we say the “Internet of Things”.

In 1999 Kevin Ashton, a researcher at MIT in Boston, described the Internet of Things as a set of technologies that allows to control, monitor and transfer information by connecting a device to the Internet.

The Industrial Internet of Things, usually abbreviated with IIoT, is therefore a verticalization of the broader concept of IoT, focused on the industrial ecosystem and enabled by technologies such as cybersecurity, cloud and edge computing, big-data analysis, artificial intelligence and machine learning.

IIoT MARKET

According to a report signed by IndustryARC, the Industrial IoT market will reach 124 billion dollars by 2021 and should exceed 771 billion dollars by 2026. The CAGR (compound annual growth rate) in the period forecast 2018-2026, is instead estimated at 24.3%.

The key to this growth lies in the fact that data obtained in real time not only allows better management of the production process, but also better management of all company assets, offering a clear and immediate picture of the company’s performance in all its areas.

IIoT SYSTEM ARCHITECTURE

The ordinary structure of an IIoT system is a modular architecture organized in 4 Levels:

  1. Device Level: is the physical component of the IIoT system: IT hardware, machinery and sensors;
  2. Network Level: it consists of communication protocols, cloud computing and wifi networks that collect data and transfer them to the next level;
  3. Service Level: made up of functional applications and software for analysis as well as the  transformation of data into information that can be displayed on the driver’s dashboard;
  4. Content Level: it is the last layer of the stack and is formed by user interface devices.

ADVANTAGES OF INDUSTRIAL IOT

The wide availability of data collected makes it possible to monitor and maintain (also in a predictive manner) strategic infrastructures, by utilizing AI and machine learning algorithms, we are able to generate estimates, forecasts on possible risks and suggest measures to be taken before failures occur.

For example, in the infrastructure sector, IoT sensors and predictive algorithms could allow the continuous monitoring of:

  • Tunnels: to assess their deformations and convergence;
  • Bridges: to check its inclinations and deflection measures;
  • Buildings: to measure static deformations on buildings and verify their structural integrity;
  • Sewage systems: to evaluate the speed and flow of waves;

The result of industrial IoT projects is the reduction of energy and maintenance costs, as well as the general improvement of business productivity and the employees work quality.

CRITICALITY OF THE IIoT 

  • Cyber ​​security: The existing IT security measures for IoT devices are far lower, and the risks are sometimes underestimated, compared to the existing measures for more traditional computers and devices. The risk of connecting a device to a network  makes it a potential target of a cyber attack.
  • Lack of standardization in communication protocols: industrial communication protocols are the conditio sine qua non for interconnection and data exchange between machine and software. In most companies the hardware is extremely varied in age, manufacturer and technology used. This heterogeneity often requires the use of different communication protocols thus making the interconnection operation complex and expensive.

However, these critical issues must not discourage investments in IIoT projects. The long-term benefits are extremely superior to the short-term efforts in terms of human and economic resources.

IIoT IN GREENVULCANO

Well before the IoT became a research trend, GreenVulcano had already developed its own solution to offer to customers.

Leading  the integration market thanks to an experience of over 10 years, GreenVulcano has recently put Sibyl (its IoT platform) on the market: . Sibyl is a cloud based (but can also be used on premise), plug and play, dedicated to the management, remote control and predictive maintenance solution to monitor complex infrastructure systems.

Find out which could be the right solution for the needs of your company and don’t hesitate to write us for further information.

To learn more about Greenvulcano’s IoT solution visit our website and don’t miss the next article.

In the first post related to the IoT platform we talked about some introductory aspects:

  • The importance of using an IoT platform for disaster prediction, showing a real project for monitoring the structure of bridges and tunnels (NTSG partner)
  • The meaning of IoT data storm (how much data are we talking about)
  • That importance of choosing an appropriate IoT platform and an experienced service provider before starting an IoT project.

In this and future posts, we will describe many aspects of the IoT world and how the GV IoT platform addresses them, using as a real scenario for the discussion a project for monitoring the structural deformations of a highway tunnel subject to landslides. This scenario will be used as the background to the narration for all GV IoT platform posts.

To simplify the exposition of the GV IoT platform, in terms of what it is and how it addresses some of the top IoT issues (amount of data to elaborate, security, scalability, storage and analytics), we will describe the trip of a single measurement from Things to Humans and the back trip of a command from Humans to Things.

 

We now begin describing the monitoring scenario and immediately after we will begin the narration from the Thing, the real protagonist of this story.

The scenarios that will be used during the trip into the GV IoT platform

Reference scenario: Monitoring structural deformation of a tunnel

 

The scenario consists in monitoring the health of a tunnel, in term of structural deformations that may damage the tunnel itself and put Humans in danger.

Natural causes that affect the structure of a tunnel:

  • Landslides
  • Earthquakes
  • Wind
  • Infiltrations
  • Temperature
  • Etc.

Human causes that affect the structure of a tunnel:

  • Traffic
  • Heavy vehicles
  • Accidents
  • Etc.

But how do you actually prepare a tunnel to be monitored for deformations?

We can use a FS22 Industrial BraggMETER (picture 1) and wire the entire tunnel with the fiber cable (picture 2) and strain sensors (picture 3).

Source: NTSG Val di Sambro: “3 lines of sensors have been installed along the whole tunnel, while the thermal sensors have been installed at distances previously set. This to compensate the effects, on the readings, of thermal variations and to obtain a pure mechanical deformation. It is possible to control the longitudinal movements of the tunnel, and verify if the tunnel keeps the initial shape as designed.”

  • Number of sensors: 780
  • Sampling rate: 10 Hz
  • Wiring: 30 km of optical fiber
  • Packet dimension: 6 bytes (single sensor) – 30 bytes header for all
  • PLE: 4 (working platform, lifting)
  • Working time: 24/24h, 365d/year

We have:

  • 780 sensors * 10 Hz * 10 bytes * 60 seconds * 60 minutes * 24 hours
    • ~46 Kb per second
    • 161,7 MB per hour
    • 3,78 GB per day
    • 10 messages (~4,6 kb each message) per second to send over the internet

 

Many information about the IoT technology can be found here: https://www.hbm.com/en.

 

(1) FS22: Industrial BraggMETER

(2) Fibre cable: can be very long

(3) Strain sensor

(4) BraggMONITOR application

(5) BraggMONITOR application

(6) Other sensors

 

 

 

 

The picture 4 of the BraggMONITOR application (window application that connects via LAN to the Industrial BraggMETER) shows all strain sensors that start from the Industrial BraggMETER, that in this case has four fiber cables doors.

 

(7) The tunnel from one of the working platform (PLE)

(8) The FS22 + switches

(9) The fibre cable

(10) Wiring elements

(11) Switch + wiring elements

(12) Wiring elements

 

The trip from Things to Humans: sensed data and analytics

The story begins with a strain sensor SS01 at t1 that is measuring a wavelength of 1572.52 nm (nanometer = one billionth of a meter). Actually, it is not just that sensor that is measuring the wavelength, but all 780 sensors at a common frequency of 10 Hz.

 

At 2018-Set-10 10:10:20.1 (.1 = 1/10 of a sec)

Wavelength = 1572.52 nm

 

Here are some initial questions to answer if you want to use the BraggMETER:

  • How can we read this importation out of the BraggMETER?
  • How is the information coded? Binary, ASCII?
  • Can we read a single value at a time or can we read in continuous mode (at 10 Hz)?
  • Do I need a special communication protocol to use the BraggMETER?
  • etc.

Fortunately, the BraggMETER has an ethernet door and a user manual that can be retrieved here:

To make this story short, here are the answers:

  • If you open a socket with the command port and send a particular command to it, the BraggMETER can send pieces of information back to you in continuous mode on another port. You can also decide if you want the information in binary or ASCII mode
  • The FS22 talks the “skippy” language:
  • Each package (binary in this example) that you receive has a header of 30 bytes and 6 bytes for each sensor. In total (780 sensors * 6 bytes) + 30 bytes = 4710 bytes

The output of the BraggMETER (every 1/10 of sec = 10 Hz):

  • “<header><ch0:s1>,1572.52,…,<ch0:sn>,…,<ch3:s1>,<ch3:s2>,…,<ch3:sn>”

Conclusions

The first part of our journey ends here.

In the following Blog post, we will see the data leave the sensor and travel in all its phases up to the view from the human being.

If you want to deepen some topics do not hesitate to leave us a comment below, just to let us know your opinion.

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