Real-Time Monitoring of Agricultural Land with Crop Prediction and Animal Intrusion Prevention using Internet of Things and Machine Learning at Edge

EasyChair Preprint 3016

Abstract

Agriculture is considered as a foundation of life, since the primary source of food and other raw materials is from the agriculture. It plays a crucial part in the country's economic development. Agricultural growth is very critical for the improvement of our country's economic situation. Sadly, many farmers cultivate their land using the conventional methods. As water availability in today's world is becoming scarce and there is an urgent need to follow smart forms of irrigation. Most irrigation system in India is run manually. we should replace these obsolete techniques with advanced techniques. The paper describes how the use of the Internet of Things [IOT] and machine learning techniques can be combined to make irrigation smart. The proposed system saves time, avoiding problems like constant vigilance, crop prediction and does the animal intrusion prevention when wild animals enter the field to destroy the crops. It also helps in water conservation by supplying the plants / field with water automatically, depending on the water requirements. and finally, both SMS and Email notification will be sent to the farmer mobile phone during the abnormal conditions of his farm. The proposed system can be used for the for-edge decisions in real time using edge computing.

Keyphrases: Automation, Edge analytics, Internet of Things, Sensors, image processing, machine learning

@booklet{EasyChair:3016,
  author    = {R Nikhil and B S Anisha and P Ramakanth Kumar},
  title     = {Real-Time Monitoring of Agricultural Land with Crop Prediction and Animal Intrusion Prevention using Internet of Things and Machine Learning at Edge},
  howpublished = {EasyChair Preprint 3016},
  year      = {EasyChair, 2020}}