Download PDFOpen PDF in browser

Crop Health Management Using Internet of Things

EasyChair Preprint no. 4968

13 pagesDate: February 4, 2021

Abstract

  Machine learning is everywhere throughout the whole growing and harvesting cycle. It begins with a seed planted in the soil, soil preparation, seeds breeding and water feed measurement and it even ends when robots pick up the harvest determining the ripeness with the help of computer vision. One of the machine learning algorithms is Deep Learning. It is one of the major techniques for image processing and data analysis with promising results and large potentials. Deep learning provides high accuracy, outperforming existing commonly used image processing techniques. Agriculture is the backbone of developing countries like India; hence this field should be given the utmost care and attention using the latest technological advancements like the Internet of Things (IoT). Implementation of smart ways for better agriculture has paved way for this emerging field of Smart Agriculture. Smart Agriculture enables farmers to do agriculture by monitoring the field for pests, insects, a sudden change in the environment due to global warming, etc from remote areas like their houses. Internet of Things (IoT) based solutions are being developed to automatically maintain and monitor agricultural farms with minimal human involvement. The article presents the importance of crop and its control and verifies the crop with the pesticides at the initial stage. The retrieved data will be stored in the cloud and this information is gathered through communication between the sensor and the base station. The experimental framework and simulation design suggest that the basic functions of the monitoring system of the Internet of Things (IoT) for agriculture can be realized.

Keyphrases: Agriculture, IoT, Raspberry Pi, Sensors., ThingSpeak

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:4968,
  author = {Janardhanam S N Kalyan Srinivas and Tiruvaipati Dolika Sreelalitha and M Vishnu Vardhan Reddy and Jammalamadaka Rajasekhar},
  title = {Crop Health Management Using Internet of Things},
  howpublished = {EasyChair Preprint no. 4968},

  year = {EasyChair, 2021}}
Download PDFOpen PDF in browser