Research Article
BibTex RIS Cite

Design and Implementation of a Smart Controller in Agriculture for Improved Productivity

Year 2018, Volume: 18 Issue: 1, 45 - 51, 23.02.2018

Abstract

Agricultural produce
significantly depends on many crop parameters such as humidity, pH,
temperature, sunlight, microbial activity, soil ions, air quality, and water
quality. A higher production of crop can be achieved via maintaining all these
parameters in the desired range. A smart system was developed to control the
environmental parameters in the desired range via incorporating a multisensor
to measure the parameters such as humidity, temperature, and sunlight; in
addition, also a suitable controller was designed to control these parameters
in the desired range. Sensors were placed to continuously monitor the field
parameters such as temperature, humidity, sunlight, and soil moisture. All
these parameters were remotely acquired using ZigBee to PC through myRIO boards.
Fuzzy-based controllers were designed to operate the actuators to maintain the
set point. The designed system on implementation was tested on a real-life
model. The results show that the proposed technique maintained the parameters
at the desired state and reduced human intervention and labor.

References

  • 1. X. Xu, X. Li, G. Qi, L. Tang, L. Mukwereza, “Science, Technology, and the politics of knowledge: The case of China’s agricultural technology demonstration centers in Africa”, World Development, vol. 81, pp. 82-91, 2016.
  • 2. J. W. Jones, J. M. Antle, B. Basso, K. J. Boote, R. T. Conant, I. Foster, H. C. J. Godfray, M. Herrero, R. E. Howitt, S. Janssen, B. A. Keating, R. Munoz-Carpena, C. H. Porter, C. Rosenweig, T. R. Wheeler, “Towards a new generation of agriculture system data, models, and knowledge products: State of agriculture systems science, Agriculture Systems, vol. 156, pp. 269-288, 2017.
  • 3. A. Chhetri, P. Aggarwal, P. K. Joshi, S. Vyas, “Farmer’s prioritization of climate-smart agriculture (CSA) technologies”, Agriculture Systems, vol. 151, pp. 184-191, 2017.
  • 4. C. Mwongera, K. M. Shikuku, J. Twyman, P. Laderach, E. Ampaire, P. V. Asten, S. Twomlow, L. A. Winowiecki, “Climate smart agriculture rapid appraisal (CSA-RA): A tool for prioritizing context-specific climate smart agriculture technologies, Agriculture Systems, vol. 154, pp. 192-203, 2017.
  • 5. M. Babulicova, “Enhancing of winter wheat productivity by the introduction of field pea into crop rotation”, Agriculture, vol. 62, no. 3, pp. 101-110, 2016.
  • 6. J. Jones, J. Antle, B. Basso, K. Boote, R. Conant, I. Foster, T. Wheeler, “Brief history of agricultural systems modeling”, Agriculture Systems, vol. 155, pp. 240-254, 2016.
  • 7. S. Far and K. Moghaddam, “Determinants of Iranian agricultral consultant’s intentions toward precision agriculture:Integrating innovativeness to the technology acceptance model”, Journal of the Saudi Society of Agriculture Science., vol. 16, pp. 280-286, 2017.
  • 8. S. Maurya and V. K. Jain, “Energy-efficient network protocol for precision agriculture”, IEEE Consumer Electronics Magazine, vol. 17, pp. 42- 51, 2017.
  • 9. F. Viani, M. Bertolli, M. Salcucci, A. Polp, “Low cost wireless monitoring and decision support for water saving in agriculture”, IEEE Sensors Journal, vol. 17, no. 13, pp. 4299-4309, 2017.
  • 10. S. Askraba, A. Paap, K. Alameh, J. Rowe, C. Miller, “Optimization of an optoelectronics-based plant real-time discrimination sensor for precision agriculture”, Journal of Lightwave Technology, vol. 31, no. 5, pp. 822-829, 2013.
  • 11. M. Roopaei, P. Rad, K. Choo, “Cloud of things in smart agriculture:Intelligent irrigation monitoring by thermal imaging”, IEEE Cloud Computing, vol. 4, no. 1, pp. 10-15, 2017.
  • 12. L. Zhou, N. Chen, Z. Chen, C. Xing, “ROSCC: An efficient remote sensing observation-sharing method based on cloud computing for soil moisture mapping in precsion agriculture”, IEEE Journal of selected topics in applied earth observations and remote sensing, vol. 9, no. 12, pp. 5588-5598, 2016.
  • 13. P. Tokekar, J. Hook, D. Mulla, V. Isler, “Sensor planning for a Symbiotic UAV and UGV sytem for precision agriculture”, IEEE Transactions on Robotics, vol. 32, no. 6, pp. 1498-1511, 2016.
  • 14. Y. Shouyi, L. Leibo, Z. Renyan, S. Zhongfu, W. Shaojun, “Design of wireless multimedia sensor network for precision agriculture”, China Communications, vol. 10, no. 2, pp. 71-88, 2013.
  • 15. C. Deng, K. Wang, J. Li, G. Zhao, Z. Shanggun, “Effect of soil mositure and atmospheric humidity on both plant productivity and diversity of native grassland across the Loess Plateau,China”, Ecological Engineering, vol. 94, pp. 525-531, 2016.
  • 16. Z. Mustaq, S. Sani, K. Hamed, A. Alil, S. Belal, A. Naqvi, “Agricultural land irrigation sysytem by fuzzy logic”, International Conference on Information Science and Control Engineering, pp. 871-875, 2016.
  • 17. S. Revathi, T. Radhakrishnan, N. Sivakumaran, “Climate control in greenhouse using intelligent control algorithms” American Control Conference, pp. 887-892, 2017.
  • 18. J. Hatfield, J. Prueger, “Temperature extremes: Effect on plant growth and development”, Weather and Climate Extremes, vol. 10, pp. 4-10, 2015.
  • 19. K. Barlowa, B. Chirsty, G. O’Leary, P. Riffkin, J. Nuttall, “Simulating the impact of extreme heat and frost events on wheat crop production:A review”, Field Crops Research, vol. 171, pp. 109-119, 2015.
  • 20. S. Dwivedi, S. Kumar, V. Prakash, J. Mishra, “Effect of climate change on growth and physiology of rice-wheat genotypes”, Conservation Agriculture, pp. 527-543, 2016.
  • 21. A. Sharififar, H. Ghorbani, H. Karim, “Integrated land evaluation for sustainable agricultural production by using analytical hierarchy process”, Agriculture, vol. 59, no. 3, pp. 131-140, 2013.
Year 2018, Volume: 18 Issue: 1, 45 - 51, 23.02.2018

Abstract

References

  • 1. X. Xu, X. Li, G. Qi, L. Tang, L. Mukwereza, “Science, Technology, and the politics of knowledge: The case of China’s agricultural technology demonstration centers in Africa”, World Development, vol. 81, pp. 82-91, 2016.
  • 2. J. W. Jones, J. M. Antle, B. Basso, K. J. Boote, R. T. Conant, I. Foster, H. C. J. Godfray, M. Herrero, R. E. Howitt, S. Janssen, B. A. Keating, R. Munoz-Carpena, C. H. Porter, C. Rosenweig, T. R. Wheeler, “Towards a new generation of agriculture system data, models, and knowledge products: State of agriculture systems science, Agriculture Systems, vol. 156, pp. 269-288, 2017.
  • 3. A. Chhetri, P. Aggarwal, P. K. Joshi, S. Vyas, “Farmer’s prioritization of climate-smart agriculture (CSA) technologies”, Agriculture Systems, vol. 151, pp. 184-191, 2017.
  • 4. C. Mwongera, K. M. Shikuku, J. Twyman, P. Laderach, E. Ampaire, P. V. Asten, S. Twomlow, L. A. Winowiecki, “Climate smart agriculture rapid appraisal (CSA-RA): A tool for prioritizing context-specific climate smart agriculture technologies, Agriculture Systems, vol. 154, pp. 192-203, 2017.
  • 5. M. Babulicova, “Enhancing of winter wheat productivity by the introduction of field pea into crop rotation”, Agriculture, vol. 62, no. 3, pp. 101-110, 2016.
  • 6. J. Jones, J. Antle, B. Basso, K. Boote, R. Conant, I. Foster, T. Wheeler, “Brief history of agricultural systems modeling”, Agriculture Systems, vol. 155, pp. 240-254, 2016.
  • 7. S. Far and K. Moghaddam, “Determinants of Iranian agricultral consultant’s intentions toward precision agriculture:Integrating innovativeness to the technology acceptance model”, Journal of the Saudi Society of Agriculture Science., vol. 16, pp. 280-286, 2017.
  • 8. S. Maurya and V. K. Jain, “Energy-efficient network protocol for precision agriculture”, IEEE Consumer Electronics Magazine, vol. 17, pp. 42- 51, 2017.
  • 9. F. Viani, M. Bertolli, M. Salcucci, A. Polp, “Low cost wireless monitoring and decision support for water saving in agriculture”, IEEE Sensors Journal, vol. 17, no. 13, pp. 4299-4309, 2017.
  • 10. S. Askraba, A. Paap, K. Alameh, J. Rowe, C. Miller, “Optimization of an optoelectronics-based plant real-time discrimination sensor for precision agriculture”, Journal of Lightwave Technology, vol. 31, no. 5, pp. 822-829, 2013.
  • 11. M. Roopaei, P. Rad, K. Choo, “Cloud of things in smart agriculture:Intelligent irrigation monitoring by thermal imaging”, IEEE Cloud Computing, vol. 4, no. 1, pp. 10-15, 2017.
  • 12. L. Zhou, N. Chen, Z. Chen, C. Xing, “ROSCC: An efficient remote sensing observation-sharing method based on cloud computing for soil moisture mapping in precsion agriculture”, IEEE Journal of selected topics in applied earth observations and remote sensing, vol. 9, no. 12, pp. 5588-5598, 2016.
  • 13. P. Tokekar, J. Hook, D. Mulla, V. Isler, “Sensor planning for a Symbiotic UAV and UGV sytem for precision agriculture”, IEEE Transactions on Robotics, vol. 32, no. 6, pp. 1498-1511, 2016.
  • 14. Y. Shouyi, L. Leibo, Z. Renyan, S. Zhongfu, W. Shaojun, “Design of wireless multimedia sensor network for precision agriculture”, China Communications, vol. 10, no. 2, pp. 71-88, 2013.
  • 15. C. Deng, K. Wang, J. Li, G. Zhao, Z. Shanggun, “Effect of soil mositure and atmospheric humidity on both plant productivity and diversity of native grassland across the Loess Plateau,China”, Ecological Engineering, vol. 94, pp. 525-531, 2016.
  • 16. Z. Mustaq, S. Sani, K. Hamed, A. Alil, S. Belal, A. Naqvi, “Agricultural land irrigation sysytem by fuzzy logic”, International Conference on Information Science and Control Engineering, pp. 871-875, 2016.
  • 17. S. Revathi, T. Radhakrishnan, N. Sivakumaran, “Climate control in greenhouse using intelligent control algorithms” American Control Conference, pp. 887-892, 2017.
  • 18. J. Hatfield, J. Prueger, “Temperature extremes: Effect on plant growth and development”, Weather and Climate Extremes, vol. 10, pp. 4-10, 2015.
  • 19. K. Barlowa, B. Chirsty, G. O’Leary, P. Riffkin, J. Nuttall, “Simulating the impact of extreme heat and frost events on wheat crop production:A review”, Field Crops Research, vol. 171, pp. 109-119, 2015.
  • 20. S. Dwivedi, S. Kumar, V. Prakash, J. Mishra, “Effect of climate change on growth and physiology of rice-wheat genotypes”, Conservation Agriculture, pp. 527-543, 2016.
  • 21. A. Sharififar, H. Ghorbani, H. Karim, “Integrated land evaluation for sustainable agricultural production by using analytical hierarchy process”, Agriculture, vol. 59, no. 3, pp. 131-140, 2013.
There are 21 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

V Sravani This is me

Santhosh K V

Sanjay Bhargava This is me

Verina D’almeida This is me

Publication Date February 23, 2018
Published in Issue Year 2018 Volume: 18 Issue: 1

Cite

APA Sravani, V., K V, S., Bhargava, S., D’almeida, V. (2018). Design and Implementation of a Smart Controller in Agriculture for Improved Productivity. Electrica, 18(1), 45-51.
AMA Sravani V, K V S, Bhargava S, D’almeida V. Design and Implementation of a Smart Controller in Agriculture for Improved Productivity. Electrica. February 2018;18(1):45-51.
Chicago Sravani, V, Santhosh K V, Sanjay Bhargava, and Verina D’almeida. “Design and Implementation of a Smart Controller in Agriculture for Improved Productivity”. Electrica 18, no. 1 (February 2018): 45-51.
EndNote Sravani V, K V S, Bhargava S, D’almeida V (February 1, 2018) Design and Implementation of a Smart Controller in Agriculture for Improved Productivity. Electrica 18 1 45–51.
IEEE V. Sravani, S. K V, S. Bhargava, and V. D’almeida, “Design and Implementation of a Smart Controller in Agriculture for Improved Productivity”, Electrica, vol. 18, no. 1, pp. 45–51, 2018.
ISNAD Sravani, V et al. “Design and Implementation of a Smart Controller in Agriculture for Improved Productivity”. Electrica 18/1 (February 2018), 45-51.
JAMA Sravani V, K V S, Bhargava S, D’almeida V. Design and Implementation of a Smart Controller in Agriculture for Improved Productivity. Electrica. 2018;18:45–51.
MLA Sravani, V et al. “Design and Implementation of a Smart Controller in Agriculture for Improved Productivity”. Electrica, vol. 18, no. 1, 2018, pp. 45-51.
Vancouver Sravani V, K V S, Bhargava S, D’almeida V. Design and Implementation of a Smart Controller in Agriculture for Improved Productivity. Electrica. 2018;18(1):45-51.