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Internet of Green Things with autonomous wireless wheel robots against green houses and farms

C. Ram,S. Ravimaran,R. Krishnan,E. G. Julie,Y. H. Robinson,Raghvendra Kumar,Le Hoang Son,Pham Huy Thong,Nguyen Quang Thanh,Mahmoud M. Ismail

Published 2020 in Int. J. Distributed Sens. Networks

ABSTRACT

Nowadays, smart farming involves the integration of advanced technologies that incorporate low-cost robots to meet the required knowledge and maintain the health of plants in farming. Technologies like precision agriculture are also used to optimize resources based on the field condition. Internet of Green Things is also one of the technologies to integrate and share the information between people and healthy farm things. Internet of Green Things gives the information like soil moisture, temperature, humidity, and nutrient level by means of respective sensors. Monitoring and information gathering in green houses with the help of robots is a tedious and expensive process. In this connection, information is shared among low-cost robots encouraging data availability of the current state of a plant with other robots. This will emphasize the monitoring of green houses in a well-organized way. In this article, a Flask-based framework through Raspberry Pi is proposed for interoperability among the low-cost ESP8266 robots. Data gathering is performed by smart robots that are accessible through Message Queuing Telemetry Transport subscribes by means of Representational State Transfer Application Programming Interface. A cloud-like database server is provided to stock up the data. The integration of robotics with Internet of Green Things gains more advantage in gathering about spatial information data that are connected with the irrigation. Visualization techniques and perspectives based on Internet of Green Things for precision agriculture in the field of farming are highlighted.

PUBLICATION RECORD

  • Publication year

    2020

  • Venue

    Int. J. Distributed Sens. Networks

  • Publication date

    2020-06-01

  • Fields of study

    Agricultural and Food Sciences, Computer Science, Engineering, Environmental Science

  • Identifiers
    DOI 10.1177/1550147720923477
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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