Sustainable and Autonomous Soil Irrigation: Agro Smart Solution

Sustainable and Autonomous Soil Irrigation: Agro Smart Solution

Copyright: © 2023 |Pages: 21
DOI: 10.4018/978-1-6684-9039-6.ch017
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Water scarcity is probably one of the most serious problems that humanity will have to face globally. For that reason, it will certainly be urgent to try to define practices and find solutions that, in a first phase, allow to mitigate the problem, but whose ultimate objective will be to overcome the situation. This chapter presents an irrigation system set on an internet of things platform, able to act in real time according to the atmospheric conditions. Through parameterized and automated systems, it is possible to stop the irrigation. Later, using sensors, the system may or may not be activated in case the levels of soil moisture and luminosity do not respond to the parameterized needs. It is an efficient and sustainable solution that is available for all agriculture irrigation systems. To test the proposed solution, unit tests were conducted, and a group of tests with all sensors connected was also considered. This system implements an alternative method for the data flow and its monitoring, including the fact that the system is aware of the user.
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State Of The Art

The implementation of technology in agriculture is not a recent topic. And areas such as precision agriculture, and especially smart irrigation, could be the way to the solution (Bwambale et al., 2022). Over the years, models have been designed and projected to increase efficiency and minimize human labor. No system is ideal, so the study of different contributions, complementarities, and improvements of the developed work becomes essential. This section will address the study of related solutions, comparing strengths and weaknesses of the work developed by other researchers.

Key Terms in this Chapter

Data Analytics: The act of analyzing, cleaning, modifying and modeling data to extract conclusions, find useful patterns and trends.

Machine Learning: An approach to artificial intelligence (AI) that makes it possible for systems to learn and grow from data and experiences without being explicitly programmed, resulting in behavior that is more intelligent and adaptable.

Ubiquitous System: Alludes to a framework that is available and coordinated into the climate consistently, offering ceaseless types of assistance and communications.

Mobile Application: Software with particular features and functions that is made to run on mobile devices like smartphones and tablets.

Internet of Things: A concept that describes how physical objects can connect to the Internet to exchange data and communicate with each other and other devices.

Sensor: A device that converts physical or environmental stimuli into electrical signals or measurable data and responds to them.

Actuators: Components or devices that turn electrical signals or data into physical actions or responses, like turning irrigation systems on and off or displaying data on OLED screens.

LoRaWAN: A long-range, low-power communication protocol, using LoRa technology, designed for devices with low data rates and low power. It is used in IoT applications, such as wireless sensor networks.

Context-Awareness: The ability of a structure to understand and adjust to the specific situation or environment in which it operates, taking into account variables such as the client's area, preferences, and surrounding conditions, with the ability to adapt behaviors in conformity with the environment.

Autonomous System: Is a system that, in a changing environment, can obtain information about the environment and make decisions, for a long period of time, without requiring human control or interaction.

Sensor network: A set of interconnected sensors that collect and transmit environmental data to a place where it can be stored, visualized, and analyzed.

Sustainable System: A system that focuses on preserving natural resources while also promoting energy efficiency and minimizing environmental impact.

Smart Irrigation: A framework that uses sensors and algorithms to analyze and control the water system process that considers weather and soil conditions to optimize the process. This means that the system is optimized for each specific area that is being watered, which saves water and optimizes crop growth.

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