Kanchi Raghavendra Rao

Work place: Sri Krishnadevaraya University, Anantapur, 515003, India

E-mail: kanchiraghavendrarao@gmail.com


Research Interests: Models of Computation, Mathematics of Computing


P.Divya Vani completed M.Sc in Sri Krishnadevaraya University and pursuing Ph.D as a DSTINSPIRE program at Sri Krishnadevaraya University. She published 5 papers which are indexed in Scopus and IEEE journals. Currently, she is working on Internet of Things and Cloud Computing Technology.

Author Articles
Implementation of Smart Agriculture using CloudIoT and its Geotagging on Android Platform

By Palle Divya Vani Kanchi Raghavendra Rao

DOI: https://doi.org/10.5815/ijem.2019.02.04, Pub. Date: 8 Mar. 2019

Agriculture is the backbone of several countries like India and most of the economy depends directly or indirectly on agriculture for a living. But these days several crops are significantly low and farmers are difficult to analyze the variations of soil moisture on yield in every day. The solution of the mentioned problem is to place the sensors in the yield and to collect the readings of moisture in every day by implementing the technologies: Internet of Things (IoT), Cloud Computing technology and GSM (Global Service Message) communication. In this paper, explain how these technologies and GSM will help the farmers in areas where there is an acute water problem or where water conservation is essential. The system is used Wi-Fi and GSM-based communications to send the sensor data to Cloud and mobile phones. The hardware is developed using TI’s First Wi-Fi on-chip microcontroller: CC3200 LaunchPad, SIM900A GSM module, soil moisture sensor, motor and mobile phone. The software is developed using Energia IDE. Thing Speak Cloud Computing technology is used in this work for storing the sensor values in. CSV format and also shows the graphical representation of the real-time variation of moisture on mobile using mobile application and Laptop, SIM 900A module is used sent the moisture levels to the farmer’s registered mobile numbers. The system also automatically turns ON/OFF the motor based on the variation of moisture on yields. The whole system is easily implemented on yields and gets the moisture information even in remote areas in the world.

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