IDEAS home Printed from https://ideas.repec.org/a/epw/comput/v1y2021i5id10026.html

Smart Irrigation System Using Intelligent Robotics

Author

Listed:
  • Pratiksha Pradip Pandao

    (LeenaBOT Robotics pvt Ltd, India)

  • Abhi Rathi

    (LeenaBOT Robotics Pvt Ltd, India)

  • Prince Patel

    (Charotar University of Science and Technology Gujarat, India)

Abstract

To optimize water use for agricultural crops while also verifying water scarcity in the field, an automated irrigation system was developed. Weed management and control are critical for high-yielding, high-quality crops, and developments in weed control technologies have had a significant impact on agricultural output. Any weed control method that is effective must be both durable and versatile. Despite the variety in field circumstances, robust weed control technologies will successfully manage weeds. Weed control technology that is adaptable can change its strategy in response to changing weed populations, genetics, and environmental conditions. The system includes a distributed wireless network of soil-moisture and temperature sensors, as well as conductive sensors in the plant's root zone. Agate way unit also manages sensor data, triggers actuators, and sends data to an Android mobile device. To control water quantity, an algorithm with temperature and soil moisture threshold values was developed and programmed into a microcontroller-based gateway. The added future of this research is that we are utilising a robot to monitor the condition of the crop to see if it is affected by insects or not. The robot will move around the field, and we will be able to track the crop's health on our device.

Suggested Citation

Handle: RePEc:epw:comput:v:1:y:2021:i:5:id:10026
DOI: 10.24018/compute.2021.1.5.26
as

Download full text from publisher

File URL: https://eu-opensci.org/index.php/compute/article/view/10026
File Function: Abstract page
Download Restriction: no

File URL: https://eu-opensci.org/index.php/compute/article/download/10026/1785
File Function: Full text
Download Restriction: no

File URL: https://libkey.io/10.24018/compute.2021.1.5.26?utm_source=ideas
LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
---><---

More about this item

Keywords

;
;
;
;

Statistics

Access and download statistics

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:epw:comput:v:1:y:2021:i:5:id:10026. See general information about how to correct material in RePEc.

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

We have no bibliographic references for this item. You can help adding them by using this form .

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Support Team (email available below). General contact details of provider: https://eu-opensci.org/index.php/compute .

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.