"An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture" - Information and Links:

An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture - Info and Reading Options

"An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture" and the language of the book is English.


“An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture” Metadata:

  • Title: ➤  An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture
  • Author: ➤  
  • Language: English

“An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture” Subjects and Themes:

Edition Identifiers:

  • Internet Archive ID: 20-21417-1570751564

AI-generated Review of “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture”:


"An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture" Description:

The Internet Archive:

This research focused on testing with maize, economical crop grown in Phetchabun province, Thailand, by installing a total of 20 sets of internet of things (IoT) devices which consist of soil moisture sensors and temperature and humidity sensors (DHT11). Data science tools such as rapidminer studio was used for data cleansing, data imputation, clustering, and prediction. Next, these data would undergo data cleansing in order to group them to obtain optimization clustering to identify the optimum condition and amount of water required to grow the maize through k-mean technique. From the analysis, the optimization result showed 3 classes and these data were further analyzed through prediction to identify precision. By comparing several algorithms including artificial neural network (ANN), decision tree, naïve bayes, and deep learning, it was found that deep learning algorithm can provide the most accurate result at 99.6% with root mean square error (RMSE)=0.0039. The algorithm obtained was used to write function to control the automated watering system to make sure that the temperature and humidity for growing maize is at appropriate condition. By using the improved watering system, it improved the efficacy of watering system which saves more water by 13.89%.

Read “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture”:

Read “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture” by choosing from the options below.

Available Downloads for “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture”:

"An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture" is available for download from The Internet Archive in "texts" format, the size of the file-s is: 7.39 Mbs, and the file-s went public at Fri Aug 19 2022.

Legal and Safety Notes

Copyright Disclaimer and Liability Limitation:

A. Automated Content Display
The creation of this page is fully automated. All data, including text, images, and links, is displayed exactly as received from its original source, without any modification, alteration, or verification. We do not claim ownership of, nor assume any responsibility for, the accuracy or legality of this content.

B. Liability Disclaimer for External Content
The files provided below are solely the responsibility of their respective originators. We disclaim any and all liability, whether direct or indirect, for the content, accuracy, legality, or any other aspect of these files. By using this website, you acknowledge that we have no control over, nor endorse, the content hosted by external sources.

C. Inquiries and Disputes
For any inquiries, concerns, or issues related to the content displayed, including potential copyright claims, please contact the original source or provider of the files directly. We are not responsible for resolving any content-related disputes or claims of intellectual property infringement.

D. No Copyright Ownership
We do not claim ownership of any intellectual property contained in the files or data displayed on this website. All copyrights, trademarks, and other intellectual property rights remain the sole property of their respective owners. If you believe that content displayed on this website infringes upon your intellectual property rights, please contact the original content provider directly.

E. Fair Use Notice
Some content displayed on this website may fall under the "fair use" provisions of copyright law for purposes such as commentary, criticism, news reporting, research, or educational purposes. If you believe any content violates fair use guidelines, please reach out directly to the original source of the content for resolution.

Virus Scanning for Your Peace of Mind:

The files provided below have already been scanned for viruses by their original source. However, if you’d like to double-check before downloading, you can easily scan them yourself using the following steps:

How to scan a direct download link for viruses:

  • 1- Copy the direct link to the file you want to download (don’t open it yet).
    • (a free online tool) and paste the direct link into the provided field to start the scan.
  • 2- Visit VirusTotal (a free online tool) and paste the direct link into the provided field to start the scan.
  • 3- VirusTotal will scan the file using multiple antivirus vendors to detect any potential threats.
  • 4- Once the scan confirms the file is safe, you can proceed to download it with confidence and enjoy your content.

Available Downloads

  • Source: Internet Archive
  • Internet Archive Link: Archive.org page
  • All Files are Available: Yes
  • Number of Files: 15
  • Number of Available Files: 15
  • Added Date: 2022-08-19 03:53:03
  • Scanner: Internet Archive HTML5 Uploader 1.7.0
  • PPI (Pixels Per Inch): 300
  • OCR: tesseract 5.2.0-1-gc42a
  • OCR Detected Language: en

Available Files:

1- Text PDF

  • File origin: original
  • File Format: Text PDF
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564.pdf
  • Direct Link: Click here

2- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: 20-21417-1570751564_files.xml
  • Direct Link: Click here

3- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: 20-21417-1570751564_meta.sqlite
  • Direct Link: Click here

4- Metadata

  • File origin: original
  • File Format: Metadata
  • File Size: 0.00 Mbs
  • File Name: 20-21417-1570751564_meta.xml
  • Direct Link: Click here

5- Item Tile

  • File origin: original
  • File Format: Item Tile
  • File Size: 0.00 Mbs
  • File Name: __ia_thumb.jpg
  • Direct Link: Click here

6- chOCR

  • File origin: derivative
  • File Format: chOCR
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564_chocr.html.gz
  • Direct Link: Click here

7- DjVuTXT

  • File origin: derivative
  • File Format: DjVuTXT
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564_djvu.txt
  • Direct Link: Click here

8- Djvu XML

  • File origin: derivative
  • File Format: Djvu XML
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564_djvu.xml
  • Direct Link: Click here

9- hOCR

  • File origin: derivative
  • File Format: hOCR
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564_hocr.html
  • Direct Link: Click here

10- OCR Page Index

  • File origin: derivative
  • File Format: OCR Page Index
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564_hocr_pageindex.json.gz
  • Direct Link: Click here

11- OCR Search Text

  • File origin: derivative
  • File Format: OCR Search Text
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564_hocr_searchtext.txt.gz
  • Direct Link: Click here

12- Single Page Processed JP2 ZIP

  • File origin: derivative
  • File Format: Single Page Processed JP2 ZIP
  • File Size: 0.01 Mbs
  • File Name: 20 21417 1570751564_jp2.zip
  • Direct Link: Click here

13- Page Numbers JSON

  • File origin: derivative
  • File Format: Page Numbers JSON
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564_page_numbers.json
  • Direct Link: Click here

14- Scandata

  • File origin: derivative
  • File Format: Scandata
  • File Size: 0.00 Mbs
  • File Name: 20 21417 1570751564_scandata.xml
  • Direct Link: Click here

15- Archive BitTorrent

  • File origin: metadata
  • File Format: Archive BitTorrent
  • File Size: 0.00 Mbs
  • File Name: 20-21417-1570751564_archive.torrent
  • Direct Link: Click here

Search for “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture” downloads:

Visit our Downloads Search page to see if downloads are available.

Find “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture” in Libraries Near You:

Read or borrow “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture” from your local library.

Buy “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture” online:

Shop for “An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture” on popular online marketplaces.



Find "An Optimization Clustering And Classification Based On Artificial Intelligence Approach For Internet Of Things In Agriculture" in Wikipdedia