DEVELOPMENT OF A LOW POWER CONSUMPTION SMART EMBEDDED WIRELESS SENSOR NETWORK FOR THE UBIQUITOUS ENVIRONMENTAL MONITORING USING ZIGBEE MODULE
Abstract
An emerging ubiquitous technology has called for the development of a Smart Embedded Wireless Sensor Networks (SEWSN), which has gained a tremendous attention over the years but has a shortcoming including power consumption, mobility, and end-to-end communication. The ability of environmental conditions monitoring is fundamental to research about climate variability in the greenhouse, gardens, zoology, pharmaceutical process and others. Being able to document a baseline and changes in environmental parameters monitoring and weather condition in a real-time at a remote location is increasingly essential which has not been addressed totally. In this paper, we proposed the development of an experimental Smart Sensing Platform (SSP) for a real-time monitoring of environmental parameters using ZigBee module (IEEE 802.15.4). It also introduces an approach to achieved low power consumption in a wireless sensor system. The embedded system consists of a digital humidity and temperature sensor (DHT11) for acquiring the environmental parameters, the XBee module for RF transmitter and receiver, ATmega328 for control unit and so on. The practical results show that the system achieved a real-time data acquisition, efficient energy management and ends-to-ends communication, which capable of storing data and dynamically plot the graphical information for statistical analysis. The transmitting current of the module is determined to be 25.8 (mA), the sleeping mode current is at 1 (µA) and the current used in listening mode was 31.5 (mA).
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Aboaba A. A. Amoo L. A. & Ajao L. A., (2015). “Design of an Automatic Temperature Controlled Switch for Air-Conditioning Systemsâ€, ATBU, Journal of Science, Technology & Education (JOSTE); Vol. 3 (2), pg. 157-168.
Liu, L., Wang, R., & Xiao, F. (2012), Topology control algorithm for underwater wireless sensor networks using GPS-free mobile sensor nodes, Journal of Network and Computer Applications, vol. 35, no. 6, pp. 1953–1963.
Xiao, F., Wu, M., Huang, H., Wang, R., & Wang, S. (2012), Novel node localization algorithm based on nonlinear weighting least square for wireless sensor networks, International Journal of Distributed Sensor Networks, vol. 2012, Article ID 803840, 6
pages, 2012.
Jia, J., Zhang, G., Wu, X., Chen, J., Wang, X., & Yan, X. (2013), On the problem of energy balanced relay sensor placement in wireless sensor networks, International Journal of Distributed Sensor Networks, vol. 2013, Article ID 342904, 9 pages, 2013.
Ye, W., Heidemann, J., & Estrin, D. (2004), Medium access control with coordinated adaptive sleeping for wireless sensor networks, IEEE/ACM Transactions on Networking, vol. 12, no. 3, pp. 493–506.
Van, D. T., & Langendoen, K., (2003), An adaptive energy-efcient MAC protocol for wireless sensor networks, Proceedings of the 1st International Conference on Embedded Networked Sensor Systems(SenSys’03), pp. 171–180, ACM, Los Angeles, Calif, USA, November 2003.
El-Hoiydi, A., & Decotignie J., (2004), Wise MAC: An Ultra-Low power MAC protocol for multi-hop wireless sensor networks, ALGOSENSORS, LNCS 3121, pp. 18–31,
Li, Z., Chen, Q., Zhu, G., Choi, Y., & Sekiya, H., (2015), A low latency, energy efficient MAC protocol for wireless sensor networks, International Journal of Distributed Sensor Networks, pg. 1-9.
Eduardo, C., Jose M. C., & Gonzalo C., (2010), Modeling of current consumption in 802.15.4/ZigBee Sensor Motes, MDPI Sensor, pg.5443-5468, doi:10.3390/s100605443.
Krishna, Y. B., & Nagendram, S., (2012), Zigbee based voice control system for smart home, international journal computer technology & applications, vol. 3, no. 1, pp.163-168.
Anusha, K. & Balakrishna K., (2013), An adaptive embedded system for monitoring patients, International Journal of Application or Innovation in Engineering & Management (IJAIEM), Volume 2, Issue 7.
Arduino Nano, (2016), Revision history of Arduino Nano ePro Labs, Retreived April, 2016, from https://wiki.eprolabs.com/index.php.
Luca, B., Davide, D. P., Giovanni C., & Gianfranco M., (2007), Wireless sensor networks for on-field agricultural management process, Nestens S. r. l., Italy, pg. 1-18.
Texas Instruments. CC2420 Single-Chip 2.4 GHz IEEE 802.15.4 Compliant and ZigBee Ready RF Transceiver. Retrieved January 28, 2010, from http://focus.ti.com/docs/prod/folders/print/cc2420.
Texas Instruments, CC2480A1 Status (Z-Accel 2.4 GHz ZigBee Processor) datasheet. Retrieved January 28, 2010, from http://focus.ti.com/docs/prod/folders/print/cc2480a1
Texas Instruments, CC2520 (Second generation 2.4 GHz ZigBee/IEEE 802.15.4 RF transceiver). Retrieved January 28, 2010, from http://focus.ti.com/docs/prod/folders/print/cc2520.
Ember Corporation, EM260 802.15.4 and ZigBee Compliant Network Co-processor datasheet. Retrieved January 28, 2010, from http://www.ember.com/pdf/ember-EM260.pdf.
Jennic, Application Note: JN-AN-1001, Calculating JN5121 Power Consumption. Retrieved January 28, 2010, http://www.jennic.com/files/support_files/JN-AN-1001-Power-Estimation-1v3.pdf.
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