Three-node Co2 Sensor Network

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Three-node Co2 Sensor Network

  1. 1. Wireless Sensor Network for Environmental CO2 Monitoring Clinton J. Smith1*, Wen Wang1, Stephen So1,2, and Gerard Wysocki1** 1) Dept. of Electrical Engineering, Princeton University, Princeton, NJ 08544 2) Sentinel Photonics Inc., Monmouth Junction, NJ 08852, USA * clintons@princeton.edu; ** gwysocki@princeton.edu Motivation Sensor Node Long-Term Performance Two-Node Sensor Network Monitoring  The CO2 impact on the greenhouse gas effect requires global and In-Lab Activity local monitoring capability which would greatly benefit from availability of sensors that are lightweight, portable, robust, highly 0.5m Base sensitive, and selective. Station 3.3m  For study of the Carbon Cycle, these sensors should also be low- FL Sensor power/battery operated and capable of being wirelessly networked and autonomous. GL Sensor  Large area wireless networks of laser-based trace-gas sensors will provide high spatial resolution of real time concentration data with unprecedented sensitivity and selectivity to the target molecular species.  These sensors are expected to maintain a high degree of long-term stability in the field, despite changing environmental conditions. Background CO2 concentration time series show the degree to which temperature  We have built a laser spectroscopic sensor for CO2 detection and correction improves sensor-node performance. Allan deviation demonstrated its performance in preliminary laboratory and field calculation of long term concentration measurements allows quantifying  Laboratory activity can be interpreted from this data tests [1]. the sensor long-term stability. Adaptive linear regression to remove set. sensor temperature dependence enables potentially indefinite assurance  The high concentration events near 0 hours as shown by the  The sensor achieves higher long-term sensitivity by locking to of short term (<10 sec.) sensitivity. FL Sensor are caused by the operator working at the base the targeted absorption line. station to configure the WSN.  We identified environmental temperature as a main source of drift Multi-Node Long-Term Cross-Correlation Performance  The baseline reflects the overall activity in the room while and applied a linear regression technique to correct for it. the high short-time concentration spikes refer to  To demonstrate wireless sensor network (WSN) capability, both a individuals working in the vicinity of the sensor. two-node and a three-node network similar to [2] for long-term  Both at the beginning (hour 0) and at the end (hour 8) the real-time monitoring of CO2 have been investigated. CO2 concentration exhibits a low baseline level Base corresponding to low human activity in the lab.  The multi-node sensor cross-correlation was calculated. Station Wireless Sensor Network & Deployment Summary and Future Directions Node 1 Node 2 Node 3 E-QUAD at Princeton University  We have demonstrated a two and a three sensor-node 350 m range directional antennas are used network for long-term real-time CO2 concentration monitoring.  Sensor node cross-correlation is comparable to that of commercial products  A temperature correction technique was demonstrated Test Sight: Crop field in Princeton, NJ to remove the temperature impact on sensor drift. Future directions: Three calibrated sensor nodes are placed in one box and sample  A large area WSN is being deployed in the field for long- Three locations selected to monitor term trace-gas monitoring. approximately the same air sample. Continuous CO2 measurement was coupled local environments: performed over a period of 10 hours. The cross-node correlation R2 values 1. Adjacent to the local road: car traffic CO2 sensor-node. The 2. In the inner courtyard: local between the three nodes while line-locking (120 min. – 550 min.) are: References: total size is less than [1] C. J. Smith, S. So, and G. Wysocki, "Low-Power Portable Laser Spectroscopic Sensor vegetation that of a shoebox.  Node1, Node2 = 0.87 Standard deviation among the for Atmospheric CO2Monitoring," in Conference on Laser Electro-Optics: 3. On the roof of the building Applications, OSA Technical Digest (CD) (Optical Society of America, 2010), paperAcknowledgements: This material is based upon work supported by the National Science Foundation  Node1, Node3 = 0.94 nodes ranges from 2 to 6 ppmv JThB4.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.”  Node2, Node3 = 0.93 [2] S. So, A. A. Sani, Z. Lin, F. Tittel, and G. Wysocki, "Demo abstract: Laser-based trace- gas chemical sensors for distributed wireless sensor networks," in Information Processing

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