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Soil and Weather Monitoring System with Crop Prediction for Farmers Using Iot and Machine Learning

EasyChair Preprint no. 6913

20 pagesDate: October 22, 2021


Smart agro farm is a low-priced cost soil and weather observing system which analyses  the various soil characteristics and the weather thereby developing a hi-tech smart farm  equipment for farmers. The existing system is not much cost-effective smart irrigation systems, hence the proposed project is aimed to develop a cost-effective Smart Irrigation system. This system consists of two main modules named as soil and weather monitoring module where we can implement the smart irrigation system and machine learning module. First module composes of circuit interconnections and characterization of various soil sensors. Soil moisture is detected by using Soil moisture sensor. The temperature and humidity can be found out by DHT 11 (Digital Humidity Temperature). The second module ( Machine Learning ), that deals with extracting the information from all the above data values gathered from sensor.An android application is developed which provides proper awareness and guidance regarding the cultivation of preferable crops to farmers. Hence, our system is the perfect combination of IoT, Machine Learning and Android Application. Also it is useful for low-income household farmers to intensify into smart climate farming practice. The simulation shows that the Proposed system achieves 98.1818 % of accuracy which out performs the existing state of technique.

Keyphrases: IoT, machine learning, mobile application, Random Forest Algorithm, Sensors

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Velmurugan Sathya Narayanan and Kavin N Raj and Kishore Kumar and Manoj Kumar},
  title = {Soil and Weather Monitoring System with Crop Prediction for Farmers Using Iot and Machine Learning},
  howpublished = {EasyChair Preprint no. 6913},

  year = {EasyChair, 2021}}
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