Predictive Model for Reservoir Level of Peruvannamuzhi Dam in India
Shyju. S1, Lini Mathew2

1Shyju. S*, Scholar, Department of Electrical Engineering, National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh under Punjab University, Punjab, India.
2Dr. Lini Mathew, Professor, Department of Electrical Engineering, National Institute of Technical Teachers Training and Research (NITTTR), Chandigarh, Punjab, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 23, 2020. | Manuscript published on March 10, 2020. | PP: 2402-2408 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2631039520/2020©BEIESP | DOI: 10.35940/ijitee.E2631.039520
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Abstract: Peruvannamuzhi Dam is built on the Kuttiady River at Kozhikode district, Kerala, India. The main purpose of the dam is to store water safely for irrigation and to control flood at the downstream area. Hydroelectric power plant is not associated with this Dam. At present, the basic dam operation parameters like reservoir level, rain data, and outflow rate are measured manually. There is no provision for inflow measurement. Most of the state reservoirs are almost full when heavy rainfall occurs during monsoon. The opening and closing of the gates of the dam depend only on the current water level of the reservoir. So the dam operators are forced to open suddenly all the shutters of the dam when water reaches Full Reservoir Level and this is a compensatory procedure. The sudden release of water simultaneously from different reservoirs caused flood in Kerala. This paper presents Internet of Things based automatic monitoring of different parameters for dam management and predict reservoir level after a particular period, say 2 hours. The above specified dam parameters is measured with different sensors like ultrasonic sensor and rain sensor. NodeMCU upload the measured data to cloud. Thing speak IoT platform provide these data to user. Thing speak provide MATLAB link and which analyze and predict reservoir level. These data and predictions are easily available to dam authorities, dam researchers, farmers and public through their mobile phone or Personal Computer. With the help of this prediction, the operator can open the shutter in an anticipatory manner. This predictive model can be used for flood control. 
Keywords: Internet of Things, Dam automation, Thingspeak, Ultrasonic sensor, NodeMCU, Prediction.
Scope of the Article: Probabilistic Models and Methods