Integration of the Mobile Robot and Internet of Things to Collect Data from the Agricultural Fields

Robotics and Internet of Things (IoT) are two hot topics in the research area. There are studies in the literature that combine these two topics. In this study, robotics and IoT are used for the agricultural fields. Because, with the technology becoming more available on agriculture; food security, crop yield will be increased and the environmental hazards will be decreased. But this can be achieved by strictly monitoring the agricultural fields and greenhouses. For these purposes, static sensors or sensor networks, and mobile agents are used. IoT forms the backbone of such systems because there are too many units in different places and a lot of data is coming out from these units. Also, processing this data reveals the big data problem. Purpose of this work is integrating the mobile robot platform to gather data from the agricultural fields or greenhouses and then post this gathered data to the web application. So that, data can be stored, processed, and classified on the web application or cloud. This study proposes a design scheme for the mobile internet of things concept where the client or the agent is the mobile robot whether it is autonomous or not. Furthermore, the design structure is not limited to the mobile ground vehicle. Any type of unmanned vehicle or static sensor can be integrated into the system. Internet connection is not limited to only Wi-Fi, there is also a cellular connection in the system. With this study, mobile data acquisition and transferring this acquired data to the web application can be done. Also, the infrastructure of the mobile agent-based internet of things system is shown. On the robot side, autonomy can be added to the system.

• Publication year

  2019

• Venue

  International Conference on Agro-Geoinformatics

• Publication date

  2019-07-16

• Fields of study

  Agricultural and Food Sciences, Computer Science, Engineering

• Identifiers
  DOI 10.1109/Agro-Geoinformatics.2019.8820578
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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