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Wireless sensor networks consist of physically distributed autonomous sensor nodes that cooperatively monitor physical or environmental conditions. One of the greatest benefits of wireless sensor networks is that they are capable of generating a more complete view of the sensed environment by acquiring larger quantities of correlated data than independent sensor monitors. The aircraft cabin is a highly dynamic environment which necessitates the use of more advanced sensing systems. It is with the motivation of painting a better picture of the aircraft cabin environment that such a wireless sensor network is being designed and prototyped. This paper discusses the design considerations required for wireless sensor networks in the aircraft cabin environment, as well as an overview of past and present systems developed for use in aircraft cabin environmental sensing. In addition to the sensor network, supporting tools are also discussed to enable analysis of the data collected. The primary goal of this research is to provide sensing tools to enable better characterization of the aircraft cabin environment.

The semi-enclosed and pressurized nature of the aircraft cabin results in a highly dynamic environment. The dynamic conditions establish spatiotemporal dependent environmental characteristics. Characterization of aircraft cabin environmental and bleedair conditions have traditionally been done with stand-alone measurement systems which, by their very nature, cannot provide the necessary sensor coverage in such an environment. To this purpose, a prototype wireless sensor network system has been developed that can be deployed in the aircraft cabin environment. Each sensor node in the system incorporates the ability to measure common aircraft contaminants such as particulate matter and carbon dioxide, along with other key environmental factors such as temperature, air pressure, humidity, and sound pressure level. The wireless sensor network enables the collection of time-correlated results from the aircraft cabin, passing sensor data to a central collection point for storage or real-time monitoring. This paper discusses the results of testing this sensor system in a mockup of the Boeing 767 aircraft cabin environment. In this series of tests, both particulate matter and carbon dioxide were introduced into the simulated aircraft environment and measured using an array of 16 wirelessly connected sensor nodes. Two different arrangements of sensor nodes targeted both a two-dimensional plane across the aircraft cabin space and a localized three-dimensional space centered on two rows of the cabin. The test results show successful simultaneous tracking of the particulate matter and carbon dioxide concentrations as they disperse over time.

This paper describes a hands-on introductory embedded systems course, which continues from the first microprocessor course. Instead of using an off-the-shelf microcontroller development board, it shows how students can build one from scratch and add components when required for assignments or as the need arises. The course begins with wiring a microcontroller system from scratch, continues through interfacing to various sensors, and culminates in a final project. The course also focuses on embedded systems code layering concepts and enforces their usage. Lectures on practical analog interfacing circuits, such as op-amp circuitry, were presented. There were two written tests and seven hands-on laboratory assignments. The course reviews indicated students like this approach tremendously.