Online Monitoring of Shrimp Aquaculture in Bangka Island Using Wireless Sensor Network

Yudi Yuliyus Maulana, Goib Wiranto, Dayat Kurniawan, Iqbal Syamsu, Dadin Mahmudin

Abstract


In this paper, it will be described the design and realization of online water quality monitoring system based on wireless sensor network (WSN). The new system has been implemented specifically to monitor parameters Dissolved Oxygen (DO), pH and temperature in one spot shrimp aquaculture in Bangka island. The aim was to create suitable water conditions for shrimp aquaculture and save the cost of energy consumption using an automated aeration system, by maintaining the value of the DO above 5 mg/L. On the other hand, water quality data collected from sensor measurements are sent to a data logger using WSN, and then the data is sent to a data center using cellular network (GPRS) such that this data can be viewed using the website. The experimental results show that the system has great prospects and can be used for shrimp aquaculture by providing information that is relevant and timely. The resulting data the collection can be used for research and analysis.

Keywords


Automatic aeration; GPRS; sensors; shrimp aquaculture; water quality; wireless sensor network

Full Text:

PDF

References


D. Hou, X. Song, G. Zhang, H. Zhang, and H. Loaiciga. An early warning and control system for urban, drinking water quality protection: China’s experience. Environ. Sci. Pollut. Res. 2013,20:4496–4508.

D. D. Ediriweera and I.W. Marshall. Monitoring water distribution systems: Understanding and managing sensor networks. Drink. Water Eng. Sci. 2010,3: 107–113.

Y. Zhang, W. Yang, D. Han, and Y. –I. Kim. An integrated environment monitoring system for underground coal mines—wireless sensor network subsystem with multi-parameter monitoring. Sens. 2014, 14: 13149-13170.

A.Gaddam, M. Al-Hrooby, and W. F.Esmael. Designing a wireless sensors network for monitoring and predicting droughts. Proc. 8th. Int. Conf. Sens. Tech. Liverpool: 2014, pp. 210 – 215.

K.G.Sutar and R.T.Patil. Wireless sensor network system to monitor the fish farm. Int. J. of Eng. Res. and App. 2013, 3 (5): 194 – 197.

S. M. Metev and V. P. Veiko, Laser Assisted Micro technology, 2nd ed., R. M. Osgood, Jr., Ed. Berlin, Germany: Springer-Verlag, 1998.

J. Breckling, Ed., The Analysis of Directional Time Series: Applications to Wind Speed and Direction, ser. Lecture Notes in Statistics. Berlin, Germany: Springer, 1989, vol. 61.

S. Zhang, C. Zhu, J. K. O. Sin, and P. K. T. Mok, “A novel ultrathin elevated channel low-temperature poly-Si TFT,†IEEE Electron Device Lett., vol. 20, pp. 569–571, Nov. 1999.

M. Wegmuller, J. P. von der Weid, P. Oberson, and N. Gisin, “High-resolution fiber distributed measurements with coherent OFDR,†in Proc. ECOC’00, 2000, paper 11.3.4, p. 109.

R. E. Sorace, V. S. Reinhardt, and S. A. Vaughn, “High-speed digital-to-RF converter,†U.S. Patent 5 668 842, Sept. 16, 1997.

(2002) The IEEE website. [Online]. Available: http://www.ieee.org/

M. Shell. (2002) IEEEtran homepage on CTAN. [Online]. Available: http://www.ctan.org/tex-archive/macros/latex/contrib/supported/IEEEtran/

FLEXChip Signal Processor (MC68175/D), Motorola, 1996.

A.Faustine, A. N. Mvuma, H. J. Mongi, M. C. Gabriel, A. J. Tenge,and S. B. Kucel. Wireless sensor networks for water quality monitoring and control within lake Victoria basin: prototype development. Wireless Sens. Net., 2014, 6: 281-290.

P. Jiang, H. Xia, Z. He, and Z. Wang. Design of a water environment monitoring system based on wireless sensor networks. Sens., 2009, 9: 6411-6434.

X. Yang, K. G. Ong, W. R. Dreschel, K.Zeng, C. S. Mungle, and C. A. Grimes. Design of a wireless sensor network for long-term, in-situ monitoring of an aqueous environment. Sens. 2002, 2: 455-472.

D. Sirisha, B. Venkateswaramma, M. Srikanth, and A. A. Babu. Wireless sensor-based remote controlled agriculture monitoring system using zigbee. SSRG Int. J. Elec. Com. Eng. 2015, 2 (4): 32 – 36.

N. Gahlot, V. Gundkal, S. Kothimbire, and A. Thite. Zigbee based weather monitoring system. The Int. J. Eng. Sci. 2015, 4 (4): 61 – 66.

“PDCA12-70 data sheet,†Opto Speed SA, Mezzovico, Switzerland.

A. Karnik, “Performance of TCP congestion control with rate feedback: TCP/ABR and rate adaptive TCP/IP,†M. Eng. thesis, Indian Institute of Science, Bangalore, India, Jan. 1999.

J. Padhye, V. Firoiu, and D. Towsley, “A stochastic model of TCP Reno congestion avoidance and control,†Univ. of Massachusetts, Amherst, MA, CMPSCI Tech. Rep. 99-02, 1999.

Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specification, IEEE Std. 802.11, 1997.




DOI: http://dx.doi.org/10.18517/ijaseit.8.2.2428

Refbacks

  • There are currently no refbacks.



Published by INSIGHT - Indonesian Society for Knowledge and Human Development