IoT based Automatic Fertilizer Mixer and Sprinkler System
In the traditional agriculture system, the farmers are analyzing the temperature, soil moisture, soil fertility, and plant nutrient availability, which are the climate and soil variables that most growers pay the most attention to. Farmers find that applying fertilizer and irrigation using traditional methods takes a lot of time. Energy and water consumption in farming can be increased by over-irrigation, fertilizer leaching below the root zone, erosion, and the movement of soil and chemical particles to the drainage ditches. Farming will be far less expensive and time-consuming with a single system that combines fertilization and irrigation. Granular and watersoluble fertilizers are the two types of fertilizers offered to home gardeners. Granular fertilizers often release nutrients more gradually than water-soluble fertilizers, but they can also last longer. This work will create an automated system for fertilizing and watering plantations using a NPK sensor to determine the amounts of potassium (K), phosphorus (P), and nitrogen (N). The microcontroller is an Arduino. The information is then processed by the microcontroller, which also controls the irrigation and fertilization pumps that provide the field’s sprinkler system with water and fertilizer. The user will receive any input via the system. On the other hand, manual or conventional field management of these variables will not give producers a clear picture of the amounts available to meet plant requirements according to developmental stages. Therefore, the most effective use of inputs, such as water and fertilizers, will be made possible by continuous automated monitoring and control of these soil nutrient elements, ensuring high crop production potential while upholding safe environmental conditions. The purpose of this work is to develop an automated sprinkler and fertilizer mixer system based on the internet of things (IoT) that will benefit farmers in terms of time and cost.
Authors
- N. Rajkumar
- S. Durai (ORCID: https://orcid.org/0000-0002-6140-0791)
- Kishore Kumar K (ORCID: https://orcid.org/0000-0002-3821-8297)
- Brahmaji Godi
Institutions
- Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN)
Publication Details
- Published
- 2024-10-23
- DOI
- https://doi.org/10.1109/icssas64001.2024.10760690
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.60