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Irrigation Monitoring and Prediction System Using Machine Learning

Publication Type : Conference Paper

Publisher : 2020 International Conference for Emerging Technology (INCET)

Source : 2020 International Conference for Emerging Technology (INCET), 2020

Url : https://ieeexplore.ieee.org/document/9153993

Keywords : Bolt IoT module, NRF2401, bolt-cloud, Arduino, Integromat, machine learning, Twilio, mailgun, telegram-bot

Campus : Amritapuri

Center : Humanitarian Technology (HuT) Labs

Year : 2020

Abstract : This research work intends to help farmers' effective crop harvests by technology-aided irrigation. For that purpose, we propose an easily accessible IoT based monitoring, wireless controlled rover irrigation system. Through this IoT system data, farmers can irrigate their crops according to moisture and temperature values and see that every plant is getting sufficient water and sunlight. This wireless rover system uses a microcontroller unit as the master controller. Joysticks are used to control the rover using wireless interface. The sensor unit which is part of the rover system consists of moisture sensor and a temperature sensor, for detection of the moisture and temperature respectively in close proximity of plants. We have used Google-assistant bolt IoT, Integromat, telegram bot and mail gun, for data analysis. We also used a bolt WiFi module for connecting it to the internet. We have used the bolt cloud platform for data transferring and storing and predictions.

Cite this Research Publication : R. K. Megalingam, G. Kishore Indukuri, D. S. Krishna Reddy, E. Dilip Vignesh and V. K. Yarasuri, "Irrigation Monitoring and Prediction System Using Machine Learning," 2020 International Conference for Emerging Technology (INCET), Belgaum, India, 2020, pp. 1-5, doi: 10.1109/INCET49848.2020.9153993.

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