Irrigation Intelligence - Proposed System Design

What is it about?

Advanced sensor technology, especially those that incorporate artificial intelligence (AI), has been recognized as increasingly important in various contemporary applications, including navigation, automation, water under imaging, environmental monitoring, and robotics. Data-driven decision-making and higher efficiency have enabled more excellent infrastructure thanks to integrating AI with sensors. The agricultural sector is one such area that has seen significant promise from this technology using the Internet of Things (IoT) capabilities. This paper describes an intelligent system for monitoring and analyzing agricultural environmental conditions, including weather, soil, and crop health, that uses internet-connected sensors and equipment. This work makes two significant contributions. It first makes it possible to use sensors linked to the IoT to accurately monitor the environment remotely. Gathering and analyzing data over time may give us valuable insights into daily fluctuations and long-term patterns. The second benefit of AI integration is the remote control; it provides for essential activities like irrigation, pest management, and disease detection. The technology can optimize water usage by tracking plant development and health and adjusting watering schedules accordingly. Intelligent Control Systems (Matlab/Simulink Ver. 2022b) use a hybrid controller that combines fuzzy logic with standard PID control to get high-efficiency performance from water pumps. In addition to monitoring crops, smart cameras allow farmers to make real-time adjustments based on soil moisture and plant needs. Potentially revolutionizing contemporary agriculture, this revolutionary approach might boost production, sustainability, and efficiency.

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Why is it important?

The proposed system is a cost-effective monitoring solution for the environment that functions in a computing environment based on volunteer labor. Excel, The processing of data, and remote monitoring, collection, and monitoring are only some potential benefits that could be gained. ML technology is used to obtain analytics based on the data that has been gathered. Installation, operating, and maintenance costs for such a portable multi-processor platform are significantly lower when compared to those of conventional physical models and commercial weather forecasting equipment. One of the most important conclusions of this work is that measuring environmental factors remotely has been done with very high accuracy, with the possibility of implementing remote control by operating and controlling the smart irrigation system, in addition to the possibility of combating agricultural pests and early detection of plant diseases. Making meteorological data accessible to a broader audience can be accomplished by strategically placing Internet of Things sensors in the appropriate locations. This is based on measuring the level of moisture the soil's moisture level, and it depends on measuring the temperature of the cultivated area, this is also very useful for monitoring the cultivated areas. All of you can detect diseases that may infect plants of the application of the prototype of the proposed system showed that it is possible to control the watering of crops in several different ways, including by relying on the plant's need for water.

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