AGRIBOT: Energetic Agricultural Field Monitoring Robot Based on IoT Enabled Artificial Intelligence Logic

Babu Loganathan, Ganesh and S.Mahdi, Qaysar and Hadi Salih, Idris (2022) AGRIBOT: Energetic Agricultural Field Monitoring Robot Based on IoT Enabled Artificial Intelligence Logic. International Conference on Emerging Technology Trends in Internet of Things and Computing.

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In these modern days agriculture is one of the major concern to take out from the loss and need to be improvised in next level of production ratio. The latest technologies such as Internet of Things and Artificial Intelligence are associated with many applications to improve the standards as well as provide a drastic support to customers to achieve their communication needs. In this paper, a new agricultural robot is designed called as agriBOT, in which it is used to monitor the entire agricultural field and the associated crops in an intelligent manner by using Artificial Intelligence logic. The agriBOT has a provision to act like a drone to survey all fields in an intelligent manner. This provision allows the robot to move in all fields even the crops are in so dense, in which the agriBOT is integrated with many smart sensors to monitor the crop details well such as Soil Moisture Level Identifier, Crop Leaf Image Accumulator, Rain Identification Sensor and Surrounding Temperature level Identification Sensor. These sensors are associated with the proposed agriBOT to make the robot as powerful and robust in association with Artificial Intelligence and Internet of Things (IoT) strategies. The Internet of Things is used to carry the local sensor data from the agriBOT to the remote server for processing as well as the data available into the remote server can easily be monitored by the respective farmer from anywhere in the world at any time. The alert is utilized over the proposed agriBOT to pass the emergency condition alerts to the respective farmers instantly as well as the Global Positioning System (GPS) is utilized to retrieve the location details of the crop and report that to the server immediately by using IoT. This paper introduced a new machine learning strategy to analyze the server data, in which it is called as Modified Convolutional Neural Scheme (MCNS). This approach of MCNS provides the facility to predict the climate conditions and the associated crop details instantly based on the data which is collected already and stored into the server. With the association of these two strategies made the proposed approach of agricultural field monitoring system too robust and efficient to analyze the crop related details as well as the plant lea disease is also identified by using this approach based on the images captured by the agriBOT in an intellectual manner. All these details are experimentally tested and the resulting section provides the proper proof for the mentioned things.

Item Type: Article
Uncontrolled Keywords: Smart sensors agriBOT Modified convolutional neural scheme MCNS IoT
Subjects: S Agriculture > S Agriculture (General)
Engineering > Computer engineering
Engineering > Mechatronics engineering and machinery
Engineering > TK Electrical engineering
Engineering > TL Motor vehicles. Aeronautics. Astronautics
Depositing User: TIU ePrints Admin
Date Deposited: 25 Oct 2022 08:46
Last Modified: 05 Dec 2022 07:56

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