PatternIQ Mining (PIQM) Sahara Digital Publications · eISSN 3006-8894

Original Research Open access

IoT-BASED ROBOTIC SYSTEMS INTEGRATING ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE CROP PROTECTION IN AGRICULTURE

R KRISHNAMOORTHY and C.MANOJKUMAR

PatternIQ Mining 2024;1(3):1–11 · https://doi.org/10.70023/piqm24301

Abstract

Advancements in technology, including the Internet of Things (IoT) and Artificial Intelligence (AI), greatly impact agriculture. The study investigates the statistical applications of AI-driven robotic devices based on the IoT as a basic emphasis. Using manual effort and chemical fertilizers, traditional farming can be highly attributed to inefficiency, health problems and environmental effects. The paper proposes an AgriBotIQ, a revolutionary platform that uses robotics based on IoT to monitor and analyse with accurate participation in plant management. Autonomous robots can collect information based on plants and their habitats by using imaging devices and sensors like soil moisture, humidity, temperature, and many others. Machine learning (ML) algorithms search the database for anomaly detection, threats, and crop trends. To identify the crops that are diseased or healthy, ML is integrated with computer vision. The suggested AgriBotIQ also eliminated weeds, boosting the output by neglecting unneeded waste and chemicals. The emerging IoTs have allowed better remote plant monitoring in more versatile and précised. Overall productivity and protection of crops are possible by statistical analysis and real-time notifications of the proactive decisionmaking outcomes. By combining IoT and AI, the future agricultural crop security will improve greatly.

Keywords :

Artificial intelligence, Robotics, Internet of Things, Remote control, Smart sensors, Crop Protection, Precision farming.

How to cite

KRISHNAMOORTHY, R., & MANOJKUMAR, C. (2024). IoT-BASED ROBOTIC SYSTEMS INTEGRATING ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE CROP PROTECTION IN AGRICULTURE. PatternIQ Mining, 1(3), 1–11. https://doi.org/10.70023/piqm24301

Copyright and licence

Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

© 2024 The Author(s). Published by Sahara Digital Publications. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) licence. This licence allows others to copy, redistribute, remix, adapt and build upon the work for non-commercial purposes, provided that the authors and the original publication are credited. The authors retain copyright. See Copyright and Licensing.