editedbook
Area/Stream: Artificial Intelligence,
Authors: Charles Rajesh Kumar. J, Mary Arunsi. B, M. A. Majid,D.Vinod Kumar,D.Baskar
Keywords: Wireless Sensor Networks(WSN); Energy efficiency; Internet of Things (IoT); Precision agriculture (PA); Machine Learning (ML); K-Nearest Neighbor (K-NN); Naive Bayes (NB); Support Vector Machines (SVM).
Book Name /series: Futuristic Trends in Artificial Intelligence,Volume 2, Book 17, Part 1, Chapter 5
Publication: IIP Proceedings Year: 2022, Month: November Page No: 29-49, ISSN/ISBN: 978-93-95632-81-2, DOI/Link: https://rsquarel.org/assets/docupload/rsl20237105295EBF00345.pdf
ENERGY-EFFICIENT AND HIGH-PERFORMANCE IOT-BASED WIRELESS SENSOR NETWORK ARCHITECTURE FOR PRECISION AGRICULTURE MONITORING USING MACHINE LEARNING TECHNIQUES
Area/Stream: Artificial Intelligence,
Authors: Charles Rajesh Kumar. J, Mary Arunsi. B, M. A. Majid,D.Vinod Kumar,D.Baskar
Keywords: Wireless Sensor Networks(WSN); Energy efficiency; Internet of Things (IoT); Precision agriculture (PA); Machine Learning (ML); K-Nearest Neighbor (K-NN); Naive Bayes (NB); Support Vector Machines (SVM).
Book Name /series: Futuristic Trends in Artificial Intelligence,Volume 2, Book 17, Part 1, Chapter 5 Publication: IIP Proceedings Year: 2022, Month: November Page No: 29-49, ISSN/ISBN: 978-93-95632-81-2, DOI/Link: https://rsquarel.org/assets/docupload/rsl20237105295EBF00345.pdf
Abstract:
An automated irrigation system is developed to maximize the utilization of irrigation water for crops. Automation irrigation systems are designed using the Internet of Things (IoT), wireless sensor networks (WSN), and Machine Learning (ML) techniques and help in precision agriculture (PA). In this research, the IoT and WSN are innovatively coupled to create an intelligent remote crop monitoring system to use water in farming land space effectively. Appropriate sensors are used to measure the temperature and moisture of the root area. Two groups have been formed with the sensor information such as “require water” and “not require water” and saved on the server. The device intelligently determines whether the field needs water and automatically turns "ON" or "OFF" the motor, saving the farmer's time and human labor. ML Classifiers such as K-NN, Naive Bayes, and SVM decide if watering is required. ML classification performance measures demonstrate that the K-NN classifier outperforms the other two models considered for this investigation.
Cite this: Charles Rajesh Kumar. J, Mary Arunsi. B, M. A. Majid,D.Vinod Kumar,D.Baskar ,"ENERGY-EFFICIENT AND HIGH-PERFORMANCE IOT-BASED WIRELESS SENSOR NETWORK ARCHITECTURE FOR PRECISION AGRICULTURE MONITORING USING MACHINE LEARNING TECHNIQUES", Futuristic Trends in Artificial Intelligence,Volume 2, Book 17, Part 1, Chapter 5 , November, 2022, 29-49, 978-93-95632-81-2, https://rsquarel.org/assets/docupload/rsl20237105295EBF00345.pdf
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