Agricultural Advancements through IoT and Machine Learning


Authors : Shilpi Kulshrestha; Lokesh Lodha

Volume/Issue : Volume 8 - 2023, Issue 11 - November

Google Scholar : https://tinyurl.com/3968cbr7

Scribd : https://tinyurl.com/mz53d335

DOI : https://doi.org/10.5281/zenodo.10142508

Abstract : A Smart Agriculture system employs sensor technology and data analytics to enhance agricultural practices, leading to increased crop yields and reduced waste. Various sensors such as soil moisture, temperature, humidity, and light intensity detectors are utilized to monitor and analyze data for optimal crop growth and improved farming techniques including irrigation, fertilization, and pesticide management. These systems find application in diverse agricultural environments like open fields, orchards, and greenhouses, providing valuable insights for informed decision- making. Some systems integrate sensor-based technologies for enhanced efficiency, offering cost- effective and easily implementable solutions. This paper aims to compare and comprehend existing smart farming models, presenting a novel approach to integrating Machine Learning and Internet of Things (IoT) in real- time agricultural settings.

Keywords : Precision Agriculture, Smart Irrigation, Crop Management, Water Management, Digital Agriculture, Smart Agriculture, Machine Learning.

A Smart Agriculture system employs sensor technology and data analytics to enhance agricultural practices, leading to increased crop yields and reduced waste. Various sensors such as soil moisture, temperature, humidity, and light intensity detectors are utilized to monitor and analyze data for optimal crop growth and improved farming techniques including irrigation, fertilization, and pesticide management. These systems find application in diverse agricultural environments like open fields, orchards, and greenhouses, providing valuable insights for informed decision- making. Some systems integrate sensor-based technologies for enhanced efficiency, offering cost- effective and easily implementable solutions. This paper aims to compare and comprehend existing smart farming models, presenting a novel approach to integrating Machine Learning and Internet of Things (IoT) in real- time agricultural settings.

Keywords : Precision Agriculture, Smart Irrigation, Crop Management, Water Management, Digital Agriculture, Smart Agriculture, Machine Learning.

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe