Optimized design for data processing and power consumption for wireless sensor node

  • Authors

    • Muhammed Sabri Salim Lecturer in Alnahrain university, Mechatronics Eng., PhD
    2019-02-15
    https://doi.org/10.14419/ijet.v7i4.24674
  • Smart Sensor Node, IEEE 802.15.4, ZigBee PRO, Greenhouses, Smart Algorithm
  • The primary processing of data collected in the sensor node is a major aspect of the performance of wireless sensor networks. This paper provides an experimental description of a smart algorithm in which the sensitivity node operates. The specification is based on measuring the current that is discharged from the power source in data transmissions. The measurements allow for the definition of an analytical model for the number of data packets to be sent from the terminal sensor node, a function of sensor operation and the level of change of sensor data. Conventional sensor nodes are not effective in terms of productivity, flexibility, energy consumption and work interference. The sensor node is programmed according to the conventional method, which sends the data every minute, and then reprogrammed according to the intelligent algorithm in which the transmitter unit is activated when there is a difference between the averages of ten readings in one minute with the previous average reading. Temperature and humidity were measured over a 12-hour period. The conventional sensor node needed to send 60 packets of data within an hour, which could be repeated data. The use of the smart node algorithm improved current consumption by 93% compared to the commercial node. The integration of the wireless sensor node with the smart algorithm has several advantages, such as the number of packet data sent is lower and of high accuracy, the total power consumed for the node is lower. In addition to the possibility of increasing the number of sensor nodes in the wireless sensor network.

     

     

  • References

    1. [1] Xia, F., Y.C. Tian, Y. Li and Y. Sung, 2007. Wireless Sensor/actuator network design for mobile control applications. Sensors, 7, 2157-2173. https://doi.org/10.3390/s7102157.

      [2] Rezgui, A. and M. Eltoweissy, 2007. Service-oriented sensor-actuator networks: Promises, challenges, and the road ahead. Comput. Commun, 30: 2627-2648. https://doi.org/10.1016/j.comcom.2007.05.036.

      [3] Tik, L.B., C.T. Khuan and S. Palaniappan, 2009. Monitoring of an aeroponic greenhouse with a sensor network. IJCSNS, 9: 240-246.

      [4] Narasimhan, V.L., A.A. Arvind and K. Bever, 2007. Greenhouse asset management using wireless sensor actor networks. Proceedings of IEEE International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, Nov. 4-9, Papeete, French Polynesia, pp: 9-14,

      [5] Park, D. H., Kang, B. J., Cho, K. R., Shin, C. S., Cho, S. E., Park, J. W., & Yang, W.M. (2011). A study on greenhouse automatic control system based on wireless sensor network. Wireless Personal Communications, 56(1), 117–130. https://doi.org/10.1007/s11277-009-9881-2.

      [6] Zadeh, L.A., 1993. The role of fuzzy logic and soft computing in the conception and design of intelligent systems. Proceedign of the 8th Austrian Artificial Intelligence Conference on Fuzzy Logic in Artificial Intelligence, (FLAI’93), Springer-Verlag London, UK, pp: 1-1. https://doi.org/10.1007/3-540-56920-0_1.

      [7] Naseer Sabri , S. A. Aljunid , R. B. Ahmad , M.F. Malek , Abid Yahya , R. Kamaruddin , M.S. Salim. Smart Prolong Fuzzy Wireless Sensor-Actor Network for Agricultural Application. Journal of Information Science and Engineering. 28(2), 295-316, 2011.

      [8] Auda Raheemah, Naseer Sabri, MS Salim, Phaklen Ehkan, R Badlishah Ahmad. New empirical path loss model for wireless sensor networks in mango greenhouses. Computers and Electronics in Agriculture, vol.127, 553-560. https://doi.org/10.1016/j.compag.2016.07.011.

      [9] Korner, O. and H. Challa, 2003. Process-based humidity control regime for greenhouse crops. Comput. Electron. Agric., 39: 173-192. https://doi.org/10.1016/S0168-1699(03)00079-6.

      [10] Wang, N., N. Zhang and M. Wang, 2006. Wireless sensors in agriculture and food Industry-Recent development and future perspective. Comput. Electron. Agric., 50: 1-14. https://doi.org/10.1016/j.compag.2005.09.003.

      [11] Chiu, M.C., 2010. An automatic thermal control for a greenhouse using network remote control system. J. Applied Sci., 10: 1944-1950. https://doi.org/10.3923/jas.2010.1944.1950.

      [12] Soto-Zarazua, G.M., B.A. Romero-Archuleta, A. Mercado-Luna, M. Toledano-Ayala, E. Rico-Garcia, R.R. Peniche-Vera and G. Herrera-Ruiz, 2011. Trends in automated systems development for greenhouse horticulture. Int. J. Agric. Res., 6: 1-9. https://doi.org/10.3923/ijar.2011.1.9.

      [13] Salazar, R., U. Schmidt, C. Huber, A. Rojano and I. Lopez, 2010. Neural networks models for temperature and CO2 control. Int. J. Agric. Res., 5: 191-200. https://doi.org/10.3923/ijar.2010.191.200.

      [14] Rico-Garcia, E., I.L. Lopez-Cruz, G. Herrera-Ruiz, G.M. Soto-Zarazua and R. Castaneda-Miranda, 2008. Effect of temperature on greenhouse natural ventilation under hot conditions: Computational fluid dynamics simulations. J. Applied Sci., 8: 4543-4551. https://doi.org/10.3923/jas.2008.4543.4551.

      [15] Rodriguez, F., J.L. Guzman, M. Berenguel and M.R. Arahal, 2008. Adaptive hierarchical control of greenhouse crop production. Int. J. Adap. Cont. Signal Process, 22: 180-197. https://doi.org/10.1002/acs.974.

      [16] Pawlowski, A., J.L. Guzman, F. Rodriguez, M. Berenguel, J. Sanchez and S. Dormido, 2009. Simulation of greenhouse climate monitoring and control with wireless sensor network and Event-based control. Sensors, 9: 232-252. https://doi.org/10.3390/s90100232.

      [17] Eduardo Casilari, Jose M. Cano-García and Gonzalo Campos-Garrido, Modeling of Current Consumption in 802.15.4/ZigBee Sensor Motes, Sensors, Vol (10), pp (5443-5468), 2010.

      [18] Chris Baumann, The Importance of sleep mode power consumption in ZigBee/802.15.4 applications. https://www.eetimes.com/document.asp?doc_id=1274011.

  • Downloads

  • How to Cite

    Sabri Salim, M. (2019). Optimized design for data processing and power consumption for wireless sensor node. International Journal of Engineering & Technology, 7(4), 4801-4804. https://doi.org/10.14419/ijet.v7i4.24674