American Journal of Electrical and Electronic Engineering
ISSN (Print): 2328-7365 ISSN (Online): 2328-7357 Website: Editor-in-chief: Naima kaabouch
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American Journal of Electrical and Electronic Engineering. 2019, 7(4), 105-115
DOI: 10.12691/ajeee-7-4-4
Open AccessArticle

Design and Development of an IoT Based Intelligent Controller for Smart Irrigation

H.G.C.R. Laksiri1, , J.V. Wijayakulasooriya2 and H.A.C. Dharmagunawardhana2

1Department of Mechanical Engineering, University of Peradeniya, KY 20400, Sri Lanka

2Department of Electrical and Electronic Engineering, University of Peradeniya, KY 20400, Sri Lanka

Pub. Date: November 22, 2019

Cite this paper:
H.G.C.R. Laksiri, J.V. Wijayakulasooriya and H.A.C. Dharmagunawardhana. Design and Development of an IoT Based Intelligent Controller for Smart Irrigation. American Journal of Electrical and Electronic Engineering. 2019; 7(4):105-115. doi: 10.12691/ajeee-7-4-4


Internet of Things (IoT) is a rapidly developing area in the world because users can enormously benefit from real-time monitoring and controlling of remotely located devices over the internet, without being physically present at the location of the device. In the field of agriculture, development of efficient IoT based smart irrigation systems are similarly a valuable requirement for farmers, because they can remotely monitor crops and remotely control parameters in the field such as water supply to plants and collect data for further research purposes. In this research, a low cost IoT and weather based intelligent controller system is developed. First, an efficient drip irrigation system which can automatically control the water supply to plants based on soil moisture conditions is developed. This system brings greater benefits in terms of saving water, compared to traditional pre-scheduled watering systems. Next, this water efficient irrigation system is given IoT based communication capabilities to remotely monitor soil moisture conditions and to manually control water supply by a remote user with different features. Further, temperature, humidity and rain drop sensors are integrated to the system and is upgraded to provide monitoring of these parameters by the remote user via internet. These weather parameters of the field are saved in real time in a remote database. Finally, a weather prediction algorithm is implemented to control the water supply according to the existing weather condition. The proposed IoT based intelligent controller system will provide an effective method to irrigate farmer¡¯s cultivation.

IoT (Internet of Things) smart irrigation drip irrigation soil moisture condition weather prediction

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[1]  Priyadharsnee, K.S. and Rathi, S., 2017. Iot based smart irrigation system. Int J Sci Eng Res, 8(5), pp.44-51.
[2]  Rawal, S., 2017. IOT based smart irrigation system. International Journal of Computer Applications, 159(8), pp.7-11.
[3]  Marshall, R.H., 1988, February. Environmental factors affecting plant productivity in. In Fort Keogh research symposium (Vol. 1, pp. 27-32).
[4]  Nagarajapandian, M., Ram Prasanth, U., Selva Kumar, G. and Tamil Selvan, S., 2015. Automatic irrigation system on sensing soil moisture content. International Journal of Innovative Research in Electrical, Electronics, Instrumentation and Control Engineering, 3(1), pp.96-98.
[5]  Parmar, B., Chokhalia, J. and Desarda, S., 2019. Terrace Garden Monitoring System Using Wireless Sensor Networks. Research Journal of Engineering Technology and Management (ISSN), 2(01).
[6]  Devkar, P., Kumari, A., Choudhari, S. and Dhanawate, H., 2017. Automated Irrigation System using IoT. System, 159(8).
[7]  Saraf, S.B. and Gawali, D.H., 2017, May. IoT based smart irrigation monitoring and controlling system. In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 815-819). IEEE.
[8]  Zografos, A., 2014. Wireless Sensor-based Agricultural Monitoring System.
[9]  Thaker, T., 2016, March. ESP8266 based implementation of wireless sensor network with Linux based web-server. In 2016 Symposium on Colossal Data Analysis and Networking (CDAN) (pp. 1-5). IEEE.
[10]  Susmitha, A., Alakananda, T., Apoorva, M.L. and Ramesh, T.K., 2017, August. Automated Irrigation System using Weather Prediction for Efficient Usage of Water Resources. In IOP Conference Series: Materials Science and Engineering (Vol. 225, No. 1, p. 012232). IOP Publishing.
[11]  Rao, D.V.N.K., Anusha, M., Babu, P.N., Sri, M.D., Rajesh, N. and Kumar, K.S., 2015. Prognostication of Climate Using Sliding Window Algorithm. International Journal of u-and e-Service, Science and Technology, 8(4), pp. 225-232.
[12]  Kapoor, P. and Bedi, S.S., 2013. Weather forecasting using sliding window algorithm. ISRN Signal Processing, 2013.
[13]  Robertson, A.W., Kirshner, S. and Smyth, P., 2004. Downscaling of daily rainfall occurrence over northeast Brazil using a hidden Markov model. Journal of climate, 17(22), pp.4407-4424.
[14]  Khiatani, D. and Ghose, U., 2017, October. Weather forecasting using hidden Markov model. In 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN) (pp. 220- 225). IEEE.
[15]  Khadr, M., 2016. Forecasting of meteorological drought using Hidden Markov Model (case study: The upper Blue Nile river basin, Ethiopia). Ain Shams Engineering Journal, 7(1), pp.47-56.
[16]  Joshi, J.C., Tankeshwar, K. and Srivastava, S., 2017. Hidden Markov Model for quantitative prediction of snowfall and analysis of hazardous snowfall events over Indian Himalaya. Journal of Earth System Science, 126(3), p.33.
[17]  Zou, W., Yao, F., Zhang, B., He, C. and Guan, Z., 2017. Verification and predicting temperature and humidity in a solar greenhouse based on convex bidirectional extreme learning machine algorithm. Neurocomputing, 249, pp.72-85.