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@article{155634,
        author = {R. Vibhish and S. Saravanan and G. Praveenraj and G.C. Jagan},
        title = {IoT BASED PRECISION FARMING USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {1415-1420},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155634},
        abstract = {The scarcity of easy water sources around the globe has generated a need for their ultimate utilization. Internet of Things (IoT) solutions, primarily based on the software unique sensors, facts acquisition and smart processing are bridging the gaps between the cyber and physical worlds. IoT based clever irrigation management systems can help in reaching highest quality water-resource utilization. This paper gives an open-source technology based clever gadget to predict the irrigation necessities of a area the use of the sensing of floor parameter like soil moisture, temperature, and environmental conditions along with the weather forecast information from the Internet. The intelligence of the proposed gadget is primarily based on a clever algorithm, which considers sensed facts along with the weather forecast parameters like precipitation, air temperature, humidity, wind velocity and UV for the close to future. The entire machine has been developed and deployed on a pilot scale, where the sensor node statistics is wirelessly gathered over the cloud the use of web-services and a web-based facts visualization and decision assist system gives the real-time statistics insights based totally on the evaluation of sensors information and weather forecast data. The paper describes the gadget and discusses in detail the information processing effects of 4 days information based totally on the proposed algorithm of our project.},
        keywords = {Internet of Things (IoT), Irrigation System, Weather Forecast, Pilot Scale.},
        month = {},
        }