Review and focus of this article
In our last article we described the overall objective of our IOTA PoC to develop a Pay-on-Production (PoP) model. In these models the manufacturer gives a machine to an operator basically without a general leasing or renting fee. All payments are done directly through the use of the machine. This can have advantages for both, the machine operator (customer) and the machine owner (manufacturer).
In the domain of manufacturing, the PoP models have become more and more popular but lack a direct payment model. This model would trigger a payment as each production step is achieved. Our aim is to show that a PoP model can be successfully implemented with the use of IOTA tokens.
To achieve this we developed a technology demonstration platform. The objective for this platform was to operate basic functions of our machines, like e.g. the ability to drive and consume textile, to allow the creation of a real-world showcase for PoP machine payment. One of our machines can be seen under the following link.
The focus of this article is to describe the technology demonstration platform, which is used in the next development steps to showcase the PoP model.
Technology demonstration platform
topocares machines use a roll of plain textile to lay huge sand or earth filled tubes directly on site. These tubes are used for constructions (embankments, levees, etc.) or temporarily to stop floods in cases of emergency.
Figure 1 shows the created technology demonstration platform. The platform has a track system based on an electric drive system. To the rear end of the platform a textile roll (black) is attached. Thus nearly all functions of a real machine can be simulated in reality. This gives us the chance to develop and test the electric and software components on a real system in our office.
The technology demonstration platform can be operated by a control pad (joy pad). The signals generated by the control pad are used to interact with the drive control system. The PoP model will engage in this process based on the positive IOTA funding of the machine to lock or unlock all actions.
To track the status of the machine topocare uses multiple sensors which are connected to the onboard computer (figure 2). The sensor data is collected by the Robot Operating System (ROS) on the onboard computer and will be used to track the production progress as a basis for the IOTA payments. The data is also stored in the IOTA tangle to give all parties an independent overview regarding the use of the machine.
ROS is a software platform to control robots and related machines like ours. The libraries we are using are based on Linux. Main tasks and components are hardware abstraction, device drivers, message exchange between programs and program parts, often reused functionality and package management. ROS is released as open source software.
Robot Operating System - Wikipedia
Robot Operating System ( ROS) is robotics middleware (i.e. collection of software frameworks for robot software…
Specifically, the technology demonstration platform has the following sensors:
· GPS: The GPS-signal receiver tracks the GPS satellites so that we are able to calculate the platforms geographical position.
· Inertial measurement unit (IMU): Measures the speeding, angular rate and magnetic field (compass) of the technology platform.
· Capacitive proximity sensor: The sensor emits an electromagnetic field to check whether there are any changes in the field. Hereby we are able to detect if there is still enough sand in the bunker of the real machine to create a tube.
· Rotary Encoder: This sensor converts the angular position of the textile roll into a digital signal. It is used to track the amount of textile used.
· Laser scan: 2-D LiDAR scan fires rapid pulses of laser light. The reflected light is used to detect objects in front of the vehicle.
In a first step we will use the GPS signal data as well as the rotary encoder for the PoP model. This sensor set will allow us to monitor the use and production of the machine. They check if there are differences between the length of the tube and the driven distance. So you know for example that the machine is stuck if the driven distance is bigger than the length of the tube.
The other sensor data will be integrated later to broaden the view on what the machine is doing to verify the detected production steps.
A signal system was installed on the technology demonstration platform to give the machine operator a direct feedback of the machine status. Figure 3 gives two examples of light combinations. Lights like the green one can be used alone or in a combination with others like the orange one.
Signal lights have been installed to give a feedback about the IOTA wallet status. For example, a positive funding can be displayed by a green light and in consequence the control pad and drive system will be unlocked for usage.
Equally, a pending incoming transaction will be highlighted because only confirmed transactions (≙ positive funding) will be used to unlock the machine.
A deeper understanding of the wallet logic will be given in the next status report, which focuses the software part of the project.