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
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 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: