Instrumentation and Communication (IaC)

A system of wireless sensors allow quick and easy instrumentation for the measurement of noise, vibration, acceleration, (wheel) angles, climate parameters and driver parameters (such as steering and braking) with CAN-logging.

Test data is stored in the vehicle for later analysis. Dynamically selected subsets of the test data sent in real time via wireless transmission for immediate analysis. The wireless transmission is also used as a wireless Internet connection (has been tested with success the 2011 season on Colmis named HOTSPOT on Ice).

The system of wireless sensors for instrumentation and communication are based largely on existing technology. To achieve good function and performance, the system should be built with the latest technologies that improve with research connected to the challenges of wireless sensors for measurement.

The system will use infrastructure solution HOTSPOT on Ice. The working name of the system is ”Fast Instrumentation for Testing (FIT) for ICE, FIT4ICE".

Project leader: Ulf Bodin

Research Engineer: Krzysztof Wolosz

Vehicle Measurement System

The first part of the project aims at developing a system inside the vehicle with modern wireless components. The Mulle sensor is used as wireless node. It collects and processes the data from different kind of sensors e.g. thermometers, accelerometers, vibration sensors, gyroskope, compass, Road Eye sensor, CAN on-board diagnostics (OBD) etc.

The ZigBee standard is used for the communication between nodes. It provides low data rates and support low battery consumption. The additional Bluetooth 2.0 wireless technology enables communicating the data to mobile phones, tablets or laptops. 

The Constrained Application Protocol (CoAP) is used for the system to achieve easy configuration. All of the data collected can be presented in real-time on a smartphone or tablet equipped with the Android operating system. For further analyze the data is stored on a CoAP server.

The system is going to be used as the interaction between drivers and sensors of the car during vehicle testing on the frozen lake tests areas in the north of the Sweden. The cooperation with the Intelligent Road project using Road Eye sensor aims to characterize winter road conditions and to give essential feedback for the driver.

Adaptive System inside the Car

The second part of the project concerns the distributed control system, which explores the wireless transmission parameter behavior. This is to find the most efficient parameter setting for the varying traffic and demand in the wireless network. 

The physical parameters of the transmission e.g. RSSI and LQI as well as data link parameters e.g. throughput and end-to-end delay are analyzed to predict the communication capacity. The goal is to control and balance the load and find the best parameter settings to achieve the highest possible throughput and reliable transmission. All of the experiments are executed in real benchmark application and in the discrete-event network simulator NS3. 

One of the wireless sensor networks (WSN) common solution is ZigBee, especially when low power consumption is demanded. ZigBee may however provide unpredictable throughput although transmission distances are short. This is especially evident in difficult environments with complicated reflections and various materials through which radio signals need to pass through.


Distributed scheduling based on cognitive networking principles may improve both network predictability and overall throughput. We intend to design a dynamic system that changes configuration based on the analyzed parameters to automatically adapt to its current usage and location of nodes.

The following results were achieved until now:

  • it was found transmit power, distance, message size and number of nodes impacts the link capacity and resulting throughput
  • it was observed the behaviour of application (throughput, undelivered packets), MAC (queue occupancy, packet lost due to full queue) and physical layer parameters (packet loss, retransmissions, duplicate packets) for overloaded channel
  • throughput is correlated with RSSI and LQI, which indicates that throughput can be predicted from those parameters and may hence prove useful in designing a cognitive and distributed scheduler
  • it is designed the cognitive load-control system for congested Wireless Sensor Network channel, it  distributes the load using Utility Function and Fuzzy Logic - the simulations in NS3

 

List of publications

  • Wolosz, Krzysztof and Bodin, Ulf and Osipov Evgeny and Jens Eliasson, "Cognitive load-control for congested Wireless Sensor Network channels", 2013 IFIP Wireless Days, IEEE, Valencia 2013
  • Wolosz, Krzysztof and Bodin, Ulf and Riliskis, Laurynas, "A Measurement Study for Predicting Throughput from LQI and RSSI", Multiple Access Communications, Springer Berlin Heidelberg, Dublin 2012

The IaC research project is funded by the European Regional Development Fund's AVTEC project.

Page Editor and Contact: Ted Karlsson

Published: 20 January 2012

Updated: 26 November 2013

Luleå University of Technology