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Two-node Co2 sensor network
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Two-node Co2 sensor network

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Two-node Co2 sensor network Two-node Co2 sensor network Presentation Transcript

  • Low-power Wireless Trace Gas Sensing Network Clinton J. Smith,1 Stephen So,1 Amir Khan,2 Mark A. Zondlo2, and Gerard Wysocki1 1 – Dept. of Electrical Engineering, Princeton University, Princeton, NJ 08544 2 – Dept. of Civil and Environmental Engineering, Princeton University, Princeton, NJ 08544 Motivation Sensor Node Configuration Proof-of-concept Sensor Network  The CO2 impact on the greenhouse gas effect requires global and local Sensor Head VCSEL monitoring capability which would greatly benefit from availability of sensors CO2 Environment Base 0.5m that are lightweight, portable, robust, highly sensitive, and selective. Station 3.3m TEC Detector  For study of the Carbon Cycle, these sensors should also be low- Multi-pass Cell FL Sensor CW Power power/battery operated and capable of being wirelessly networked and Supply autonomous. Temperature GL Sensor Control Amplifiers  Large area wireless networks of laser-based trace-gas sensors will provide Function Generator high spatial resolution of real time concentration data with unprecedented Signal Lock-In sensitivity and selectivity to the target molecular species. Processing  These sensors are expected to maintain a high degree of long-term stability Computer in the field, despite changing environmental conditions. A schematic of the optical configuration and a block diagram of the electrical control systems. For the long term stability test the sensor head (indicated above) was placed in a temperature controlled chamber. Background Sensor Node Long-term Performance  A basic network consisting of two sensor nodes and a base  We have built a laser spectroscopic sensor for CO2 detection and station has been setup in a laboratory demonstrated its performance in preliminary laboratory and field  The network has been operated for 8 hours continuously tests [1]. acquiring CO2 concentration data  These tests revealed a temperature induced drift affecting the  Laboratory activity can be interpreted from this data set.  The high concentration events near 0 hours as shown by the FL long term performance of the sensor. Sensor are caused by the operator working at the base station to  We studied and identified the temperature sensitive components configure the WSN. by performing tests in a well-controlled environment.  The baseline reflects the overall activity in the room while the  To demonstrate wireless sensor network (WSN) capability a two- high short-time concentration spikes refer to individuals working in the vicinity of the sensor. node network similar to [2] for long-term real-time monitoring of  Both at the beginning (hour 0) and at the end (hour 8) the CO2 CO2 has been investigated. concentration exhibits a low baseline level corresponding to low human activity in the lab. Summary and Future Directions CO2 sensor-node. The  While our portable CO2 laser spectroscopic sensor has total size is less than shown excellent short term performance [1], it also has that of a shoebox. evident temperature induced stability issues over long time.  We have demonstrated a proof-of-concept two sensor- node network for long-term real-time CO2 concentration CO2 concentration time series show the degree to which temperature monitoring.References:[1] C. J. Smith, S. So, and G. Wysocki, "Low-Power Portable Laser Spectroscopic Sensor for Atmospheric stabilization improves sensor-node performance. Allan deviation Future directions:CO2Monitoring," in Conference on Laser Electro-Optics: Applications, OSA Technical Digest (CD) (OpticalSociety of America, 2010), paper JThB4. calculation of long term concentration measurements allows  Currently we are developing a real-time calibration[2] S. So, A. A. Sani, Z. Lin, F. Tittel, and G. Wysocki, "Demo abstract: Laser-based trace-gas chemical quantifying the sensor stability. Sensor performance outside the method as the most reliable solution for sensor driftsensors for distributed wireless sensor networks," in Information Processing in Sensor Networks, 2009.IPSN 2009. International Conference on(2009), pp. 427-428. temperature controlled chamber experiences slow drift. Inside the problems.This material is based upon work supported by the National Science Foundation temperature controlled environment, the drift is largely eliminated.  A large area WSN will be deployed in the field for long-under Grant No. EEC-0540832, an NSF MRI award #0723190 for the openPHOTONS systems andNational Science Foundation Grant No. 0903661 “Nanotechnology for Clean Energy IGERT.” term trace-gas monitoring.