Vibration monitoring and analysis with wireless sensor network (WSN) to classify vehicles types

1. Vibration monitoring and analysis with wireless sensor network (WSN) to classify vehicles types Cluster head Relay nodes General nodes Project has been partially supported by Kentucky Science and Technology Corporation: KSTC 144-401-08-032 and National Science Foundation (NSF) under Grant No. 0814194. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF P. Garrity, S. Bhattacharyya, and D. Dawadi (Kentucky State University) B. Panja (Morehead State University) Motivation Programming sensors/ Application System Design What is WSN? • To research on cheap easily available technology to classify heavy vehicles • from lighter ones. • General Aviation (GA) cannot afford recent sophisticated technology as it is expensive • Prediction of potential vehicle movement or flight landing on GA airport runways. • Record and analyze ambient conditions such temperature, • humidity, atmospheric pressure and seismic activity/vibration using Iris motes. • Wireless sensor network  tiny sensor nodes. • Sensing capabilities: seismic, acoustic, magnetic, light and temperature. • Limited hardware. • Limited energy. • Frequent changing behavior. TinyOS operating system networked embedded systems. nesC  applications are built out of components with well-defined, bidirectional interfaces. Moteview Tool to monitor and deploy applications on WSN Visual Basic To develop the connection with the database and generate alerts • Real time condition based monitoring • Event classification normal/ abnormal • Less response time between event and relevant action • Unavailability of sophisticated technology because of the expense at general aviation which is highest percentage of airports in US Experimental setup Topology Architecture of sensor network Calibration Experiments Real Time Software Conclusion and future work Data Analysis algorithm Data Analysis • Developed automated real time monitoring • Developed GUI software to handle data • collection and analysis • Vibration analysis identified difference in vibration to classify type of vehicle • Developed Real time alert generation • Experiments identified the need for different • topologies, equipment and accessories to • capture the occurrence of vibration or • seismic activity • Future experiments to include modified base • and sensor unit to enhance sensitivity Heavier Vehicles • IRIS sensors Gather data (Seismic Activity) • Perform data analysis using WEKA • Identify normal behavior  actual data • Develop real time software using Software engineering concepts for WSN integration and analysis • Generate alerts on detecting abnormal behavior Lighter Vehicles