Abstract
AgriGenius is a high-tech smart farm application that is able to revolutionize the traditional methods of agriculture by combining modern technologies with the use of Artificial Intelligence (AI) and Machine Learning (ML), Internet of Things (IoT) and real-time data analytics. The ultimate goal of the system is to improve agricultural productivity and sustainability, as well as decision-making efficiency by offering farmers with precise and data-driven information. The suggested system gathers real-time information of the IoT-enabled sensors positioned in the fields that are used in agriculture, and the sensors will record data on soil moisture, temperature, humidity, pH levels and nutrient content. Besides a ground-level sensing process, a comprehensive picture of crops state includes satellite imagery, historical data on agriculture, and the system developed. Machine learning algorithms allow the processing and analysis of these various sources of data to find patterns, predict results and generate actionable recommendations. AgriGenius provides various intelligent modules, such as crop health control, image processing-based disease control, irrigation control (according to the soil and weather conditions), and pest infestation forecasting. Predictive capacity of the system is further improved by adopting weather forecasting APIs, which enable farmers to be proactive with their agricultural activities. The system is also highly accurate by using convolutional neural networks (CNNs) and predictive analytics to detect diseases of crops and prescribe suitable treatment. The app will have a friendly mobile interface that will allow farmers, regardless of their technical knowledge, to access it. The system facilitates precision farming methods that would allow the effective utilization of resources like water, fertilizers, and pesticides hence lowering the cost of operation and resulting in less environmental cost. The scientific findings prove the newly introduced AgriGenius system to be more efficient and effective than the traditional farming techniques and already existing smart agriculture systems based on their accuracy, efficiency, and reliability. Having this system helps to make the agricultural industry more sustainable through enhancement of crop productivity, lowering the rate of resource wastage, as well as enlightening sound decision-making.
Keywords
Precision Agriculture, Crop monitoring, Smart Farming, IoT, Artificial Intelligence (AI), Machine Learning (ML), Data analytics, Crop disease detection, Irrigation control, Sustainable Agriculture.
Citations
IRE Journals:
Pulluri Ruthvik, Velagandula Sri Ram Sanju, Pallerla Aman Kumar, D. Rambabu "Transplant Track: AgriGenius: The Ultimate Smart Farming App" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 2158-2166 https://doi.org/10.64388/IREV9I10-1716604
IEEE:
Pulluri Ruthvik, Velagandula Sri Ram Sanju, Pallerla Aman Kumar, D. Rambabu
"Transplant Track: AgriGenius: The Ultimate Smart Farming App" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716604
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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