Futuristic IoT based Smart Precision Agriculture: Brief Analysis

Authors

  • Iwin Thanakumar Joseph Swamidason Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, Andhrapradesh, India
  • Shanthini Pandiyarajan Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamilnadu, India
  • Karunakaran Velswamy Department of Computer Science and Engineering (AI & ML) and (Cybersecurity), Jain University, Bengaluru, Karnataka, India
  • P. Leela Jancy Department of Information Technology, Sri Sai Ram Institute of Technology, Chennai, Tamilnadu, India

DOI:

https://doi.org/10.13052/jmm1550-4646.18323

Keywords:

Precision Agriculture, Internet of Things (IoT), Sensors, Drones, Irrigation

Abstract

Agriculture is considered as the backbone of any nation across the globe. With the advent of modern technologies, smart tools and techniques are used in the agriculture/farming to build on the quantity as well as quality of the agriculture production to feed the basic necessity of the humans. Smart technology such as Internet of Things play a vital role in monitoring and analyzing various environmental parameters such as water level, humidity, soil moisture, air quality, UV level, rain etc. which are highly essential to ensure the fruitful yield of any nutritious crops. In this research article, precision agriculture concepts are investigated widely with the focus of improving the productivity level and also the effective utilization of resources with the minimal cost while compared with the conventional methodologies.

Downloads

Download data is not yet available.

Author Biographies

Iwin Thanakumar Joseph Swamidason, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, Andhrapradesh, India

Iwin Thanakumar Joseph Swamidason is an Assistant Professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vijayawada, Andhrapradesh, India. He has 13 plus years of teaching experience as well as research experience. He has done his Ph.D in the Department of Computer Science and Engineering in Annamalai University, Chidambaram, Tamilnadu, India.

His Research interest includes Artificial Intelligence, Machine Learning, Image Processing, Internet of Things. He published good number of research articles in this research area. He is a lifetime member of ISTE professional community.

Researchgate id: https://www.researchgate.net/profile/Iwin-Thanakumar-Joseph-Swamidason

Shanthini Pandiyarajan, Department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamilnadu, India

Shanthini Pandiaraj completed her B.E in Electronics and Communication Engineering from Government College of Technology, Coimbatore in the year 1987 and M.E in Applied Electronics from Bharathiar University, Coimbatore in 2003. She was awarded her PhD degree by Anna University, Chennai in the year 2015, where she specialized in Speaker Recognition. She has over 25 years of teaching experience. She is working as Associate Professor in the department of Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India. Her areas of interest include Speech Technology, IoT and Machine Learning.

Karunakaran Velswamy, Department of Computer Science and Engineering (AI & ML) and (Cybersecurity), Jain University, Bengaluru, Karnataka, India

Karunakaran Velswamy received his BE Degree from Mahindra Engineering College, Salem and ME Degree from National Engineering College, Kovilpatti, Tamilnadu, India. He completed PhD Degree from Anna University, Chennai, India. Currently, he is working as an Associate Professor in the Department of Computer Science and Engineering (AI & ML) and Cybersecurity, Jain University, Bengaluru. His area of interest is in the field of data mining, machine learning and big data analytics.

P. Leela Jancy, Department of Information Technology, Sri Sai Ram Institute of Technology, Chennai, Tamilnadu, India

P. Leela Jancy is an Assistant Professor in the Department of Information Technology, Sri Sai Ram Institute of Technology, Chennai, Tamil Nadu, India since 2009. She has 14 plus years of teaching Experience. She has published several papers in International/National Conferences and Journals. Her Research interest includes Artificial Intelligence, Block chain, Deep learning, computer vision and Image Processing.

References

Ahmad, Nisar, Ali Hussain, Ihsan Ullah, and Bizzat Hussain Zaidi. “IOT based wireless sensor network for precision agriculture.” In 2019 7th International Electrical Engineering Congress (iEECON), pp. 1–4. IEEE, 2019.

Andrew, Richard Charles, Reza Malekian, and Dijana Capeska Bogatinoska. “IoT solutions for precision agriculture.” In 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 0345–0349. IEEE, 2018.

Dholu, Manishkumar, and K. A. Ghodinde. “Internet of things (IoT) for precision agriculture application.” In 2018 2nd International conference on trends in electronics and informatics (ICOEI), pp. 339–342. IEEE, 2018.

Dolci, Rob. “IoT solutions for precision farming and food manufacturing: artificial intelligence applications in digital food.” In 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), vol. 2, pp. 384–385. IEEE, 2017.

Grimblatt, Victor, Guillaume Ferré, Francois Rivet, Christophe Jego, and Nicolas Vergara. “Precision agriculture for small to medium size farmers—an IoT approach.” In 2019 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1–5. IEEE, 2019.

Marcu, Ioana M., George Suciu, Cristina M. Balaceanu, and Alexandru Banaru. “IoT based System for Smart Agriculture.” In 2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), pp. 1–4. IEEE, 2019.

Rekha, P., Venkata Prasanna Rangan, Maneesha V. Ramesh, and K. V. Nibi. “High yield groundnut agronomy: An IoT based precision farming framework.” In 2017 IEEE Global Humanitarian Technology Conference (GHTC), pp. 1–5. IEEE, 2017.

Suciu, George, Ioana Marcu, Cristina Balaceanu, Marius Dobrea, and Elena Botezat. “Efficient IoT system for precision agriculture.” In 2019 15th International Conference on Engineering of Modern Electric Systems (EMES), pp. 173–176. IEEE, 2019.

Wiangtong, Theerayod, and Phaophak Sirisuk. “IoT-based versatile platform for precision farming.” In 2018 18th International Symposium on Communications and Information Technologies (ISCIT), pp. 438–441. IEEE, 2018.

Saraf, Shweta B., and Dhanashri H. Gawali. “IoT based smart irrigation monitoring and controlling system.” In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), pp. 815–819. IEEE, 2017.

Anitha, A., Nithya Sampath, and M. Asha Jerlin. “Smart Irrigation system using Internet of Things.” In 2020 Interntional Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE), pp. 1–7. IEEE, 2020.

Laksiri, H. G. C. R., H. A. C. Dharmagunawardhana, and J. V. Wijayakulasooriya. “Design and Optimization of IoT Based Smart Irrigation System in Sri Lanka.” In 2019 14th Conference on Industrial and Information Systems (ICIIS), pp. 198–202. IEEE, 2019.

Bhanu, K. N., H. S. Mahadevaswamy, and H. J. Jasmine. “IoT based Smart System for Enhanced Irrigation in Agriculture.” In 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC), pp. 760–765. IEEE, 2020.

Mogili, UM Rao, and B. B. V. L. Deepak. “Review on application of drone systems in precision agriculture.” Procedia computer science 133 (2018): 502–509.

Maddikunta, Praveen Kumar Reddy, Saqib Hakak, Mamoun Alazab, Sweta Bhattacharya, Thippa Reddy Gadekallu, Wazir Zada Khan, and Quoc-Viet Pham. “Unmanned aerial vehicles in smart agriculture: Applications, requirements, and challenges.” IEEE Sensors Journal (2021).

Kour, Vippon Preet, and Sakshi Arora. “Recent Developments of the Internet of Things in Agriculture: A Survey.” IEEE Access 8 (2020): 129924–129957.

Kim, Jeongeun, Seungwon Kim, Chanyoung Ju, and Hyoung Il Son. “Unmanned aerial vehicles in agriculture: A review of perspective of platform, control, and applications.” IEEE Access 7 (2019): 105100–105115.

Daponte, Pasquale, Luca De Vito, Luigi Glielmo, Luigi Iannelli, Davide Liuzza, Francesco Picariello, and Giuseppe Silano. “A review on the use of drones for precision agriculture.” In IOP Conference Series: Earth and Environmental Science, vol. 275, no. 1, p. 012022. IOP Publishing, 2019.

Kulbacki, Marek, Jakub Segen, Wojciech Knieć, Ryszard Klempous, Konrad Kluwak, Jan Nikodem, Julita Kulbacka, and Andrea Serester. “Survey of drones for agriculture automation from planting to harvest.” In 2018 IEEE 22nd International Conference on Intelligent Engineering Systems (INES), pp. 000353–000358. IEEE, 2018.

Naik, Neha S., Virendra V. Shete, and Shruti R. Danve. “Precision agriculture robot for seeding function.” In 2016 International Conference on Inventive Computation Technologies (ICICT), vol. 2, pp. 1–3. IEEE, 2016.

Eaton, Ray, Jay Katupitiya, Kheng Wah Siew, and Blair Howarth. “Autonomous farming: Modelling and control of agricultural machinery in a unified framework.” International journal of intelligent systems technologies and applications 8, no. 1–4 (2010): 444–457.

Nielsen, Kirsten Mølgaard, Palle Andersen, Tom Søndergaard Pedersen, Thomas Bak, and J. D. Nielsen. “Control of an autonomous vehicle for registration of weed and crop in precision agriculture.” In Proceedings of the International Conference on Control Applications, vol. 2, pp. 909–914. IEEE, 2002.

Duckett, Tom, Simon Pearson, Simon Blackmore, Bruce Grieve, Wen-Hua Chen, Grzegorz Cielniak, Jason Cleaversmith et al. “Agricultural robotics: the future of robotic agriculture.” arXiv preprint arXiv:1806.06762 (2018).

Gonzalez-de-Santos, Pablo, Roemi Fernández, Delia Sepúlveda, Eduardo Navas, Luis Emmi, and Manuel Armada. “Field Robots for Intelligent Farms—Inhering Features from Industry.” Agronomy 10, no. 11 (2020): 1638.

https://www.javatpoint.com/iot-smart-agriculture-domain

https://www.scenario.co.za/en-ZA/News/Article/View/basic-concepts-of-precision-farming

Velliangiri, S., Sekar, R., and Anbhazhagan, P. (2020). Using MLPA for smart mushroom farm monitoring system based on IoT. International Journal of Networking and Virtual Organisations, 22(4), 334–346.

Velliangiri, S., and Alagumuthukrishnan, S. (2019). A review of dimensionality reduction techniques for efficient computation. Procedia Computer Science, 165, 104–111.

Downloads

Published

2022-02-04

How to Cite

Swamidason, I. T. J. ., Pandiyarajan, S. ., Velswamy, K. ., & Jancy, P. L. . (2022). Futuristic IoT based Smart Precision Agriculture: Brief Analysis. Journal of Mobile Multimedia, 18(03), 935–956. https://doi.org/10.13052/jmm1550-4646.18323

Issue

2022: Vol 18 Iss 3

Section

Computer Vision and its Application in Agriculture