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A GPS controlled automated soil testing rover

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Abstract

This study proposes A GPS controlled Automated Soil testing Rover to test the soil for agricultural purposes. The contribution of computer science to agriculture is essential for the sustainability of human beings in the world by keeping food production up to a satisfactory level. The automation technology is a suitable and efficient solution to overcome difficulties in agriculture. This technique will increase the productivity and reduces the hardness of human effort in the field. The traditional soil testing mechanism has many difficulties and drawbacks such as time-consuming, poor knowledge of sample collection and variation in laboratory results compared to field results. The proposed GPS controlled Automated Soil testing Rover will be a solid solution to overcome the problems of the traditional soil testing mechanism. The device has a temperature, moisture and pH sensors to measure the soil parameters such as temperature, moisture, electro conductivity, and pH. The GPS controlled Automated Soil testing Rover will be able to navigate in the given area of the field with the guidance of GPS and it is capable of avoiding obstacles in the field. The data sensed will be sent to a website to get visualized and will be stored in a database. Also, the data is used to select the suitable crop based on the parameters sensed.

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References

  1. Al-Faiz MZ, Mahameda GE (2015) GPS-Based navigated autonomous robot. AlNahrain University 4:3

    Google Scholar 

  2. Athani S, Tejeshwar CH, Patil MM, Patil P, Kulkarni R (2017) Soil moisture monitoring using IoT enabled Arduino sensors with neural networks for improving soil management for farmers and predict seasonal rainfall for planning future harvest in North Karnataka - India, in International conference on i-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam

  3. Balakrishna K, Rao M, Anupama KP, Chaitra B, Pooja L (2018) Automatic testing of soil moisture, pH using arduino and selection of specific crop. Int J Comput Sci Eng 6(6):837–841

    Google Scholar 

  4. Boopathy S, Ramkumar N (2016) Controlling the boiler temperature of tea leaves by using android application and arduino UNO. Int J Modern Comput Sci (IJMCS) 4:3

    Google Scholar 

  5. Boopathy S, et al. (2014) Implementation of automatic fertigation system by measuring the plant parameters. Int J Eng Res Technol 3:10

    Google Scholar 

  6. Bugai T, Salmon K, Chiba M (2013) GPS Guided autonomous rover. School of Electrical & Information Engineering, University of the Witwatersrand

  7. Chandramohan J, et al. (2015) Intelligent smart home automation and security system using arduino and Wi−Fi, Department of Electrical and Electronics Engineering, Gnanamani College of Technology, Namakkal, India, Volume 6 Issue 3 March 2017, Page No. 20694-20698, Index Copernicus value: 58.10. https://doi.org/10.18535/ijecs/v6i3.53

  8. Chavan CH, Karande PV (2014) Wireless monitoring of soil moisture, temperature & humidity using zigbee in agriculture. Int J Eng Trends Technol 11:10

    Article  Google Scholar 

  9. Chung W-Y et al (2013) Wireless sensor network-based soil moisture monitoring system design. In: Federated conference on computer science and information systems, pp 79–82

  10. Traunfeld K (2017) Home and garden information center : http://extension.umd.edu/hgic/soils/soil-testing

  11. (2013) Espressif Smart Connectivity Platform: ESP8266. Espressif ystems

  12. Hong Z, Kalbarczyk Z, Iyer RK (2016) A Data-Driven approach to soil moisture collection and prediction. In: IEEE international conference on smart computing (SMARTCOMP), https://doi.org/10.1109/SMARTCOMP.2016.7501673. IEEE, St. Louis, p 2016

  13. Lawlor L (2014) Thingspeak : https://github.com/iobridge/thingspeak/blob/master/README.textile

  14. Nevo A, Oad R, Podmore TH (1994) An integrated expert system for optimal crop planning. Agric Syst 45(1):73–92

    Article  Google Scholar 

  15. Paradkar AD (2016) GPS Guided autonomous robot. California State University, LongBeach

    Google Scholar 

  16. Roser M (2018) Employment in agriculture : ourworldindata.org: https://ourworldindata.org/employment-in-agriculture

  17. Snehal K, Pranaya G, Ashwini T, Pratiksha G, Payal M (2018) Automatic soil detection using sensors. Int J Future Revol Comput Sci Commun Eng 4(3):467–470

    Google Scholar 

  18. Srividyadevi P, Pusphalatha DV, Sharma PM (2013) Measurement of power and energy using arduino, vol 2

  19. Suresh DS, Jyothi Prakash KV, Rajendra CJ (2013) Automated soil testing device. ITSI Trans Electric Electron Eng 1(5):115–117

    Google Scholar 

  20. Yen KS, Lasky TA, Adamu A, Ravani B Application of high-sensitivity GPS for a highly-integrated automated longitudinal travel behavior diary, University of California

  21. Yuksel T, Sezgin A (2005) An implementation of path planning algorithms for mobile robots on a grid based map. Ondokuz Mayis University, Electrical & Electronics Engineering Department, Technical report

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Authors and Affiliations

  1. Department of Physical Science, Vavuniya Campus of the University of Jaffna, Vavuniya, 43000, Sri Lanka

    Parameswaran Kovelan, Thangathurai Kartheeswaran & Nadarajah Thisenthira

Authors
  1. Parameswaran Kovelan
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  2. Thangathurai Kartheeswaran
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  3. Nadarajah Thisenthira
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Correspondence to Thangathurai Kartheeswaran.

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Kovelan, P., Kartheeswaran, T. & Thisenthira, N. A GPS controlled automated soil testing rover. Multimed Tools Appl 80, 1273–1287 (2021). https://doi.org/10.1007/s11042-020-09358-8

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  • DOI: https://doi.org/10.1007/s11042-020-09358-8

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