Smart irrigation based on the IoT

Document Type : Review

Authors

1 Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.

2 Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

Abstract

Today, despite the idea that people may have about agriculture, it is a complex, time-consuming, and expensive process. Still, the reality is that today's agriculture industry is data-driven, accurate, smarter, and even easier. It has changed more compared to the past. All these cases have been formed with the help of a new concept called the Internet of Things in the agricultural industry. The Internet of Things is a huge network of people and things and the increasing expansion of the Internet and the reduction of its costs have provided the ground for the creation of the Internet of Things. Such changes have caused a great revolution in the field of agricultural industry, which has shaken the existing agricultural methods and can create new opportunities in the present and future. Determining the users of the Internet of Things will play an effective role in determining its prospects. However, the implementation of the Internet of Things is associated with challenges, and the Internet of Things needs standards to continue its work. So far, a lot of research has been done on the challenges of the Internet of Things and ways to solve them. Also, standards have been defined for the Internet of Things. In this article, we intend to examine the concept and applications of the Internet of Things in agriculture and irrigation, then the challenges and ways to solve them, and the architectures and standards proposed in the field of the Internet of Things. Also, this paper highlights the potential of wireless sensors and IoT in agriculture, as well as the challenges that are expected to be faced when integrating this technology with traditional agricultural practices. On the other hand, IoT devices and communication techniques related to wireless sensors encountered in agricultural applications and sensors available for specific agricultural applications, such as soil preparation, crop status, irrigation, insect and pest detection, as well as How to use this technology by the producers, which will help them to carry out the stages of cultivation, from planting to harvesting, packaging and transportation, has been explained. Advanced IoT-based architectures and platforms used in smart irrigation are also highlighted wherever appropriate. Finally, based on this comprehensive review, we identify the current and future trends of the Internet of Things in smart irrigation and highlight potential research challenges.

Keywords

Main Subjects

EXTENDED ABSTRACT

 

Introduction:

Today, despite the idea that people may have about agriculture, it is a complex, time-consuming, and expensive process, but the reality is that today's agriculture industry is data-driven, accurate, smarter, and even easier. It has changed more compared to the past. All these cases have been formed with the help of a new concept called the Internet of Things in the agricultural industry.

Definition and Applications:

The Internet of Things is a huge network of people and things and the increasing expansion of the Internet and the reduction of its costs have provided the ground for the creation of the Internet of Things. Such changes have caused a great revolution in the field of agricultural industry, which has shaken the existing agricultural methods and can create new opportunities in the present and future. Determining the users of the Internet of Things will play an effective role in determining its prospects. However, the implementation of the Internet of Things is associated with challenges, and the Internet of Things needs standards to continue its work.

Objectives:

So far, a lot of research has been done on the challenges of the Internet of Things and ways to solve them. Also, standards have been defined for the Internet of Things. In this article, we intend to examine the concept and applications of the Internet of Things in agriculture and irrigation, then the challenges and ways to solve them, and the architectures and standards proposed in the field of the Internet of Things. Also, this paper highlights the potential of wireless sensors and IoT in agriculture, as well as the challenges that are expected to be faced when integrating this technology with traditional agricultural practices.

Results:

On the other hand, IoT devices and communication techniques related to wireless sensors encountered in agricultural applications and sensors available for specific agricultural applications, such as soil preparation, crop status, irrigation, insect and pest detection, as well as How to use this technology by the producers, which will help them to carry out the stages of cultivation, from planting to harvesting, packaging and transportation, has been explained. Advanced IoT-based architectures and platforms used in agriculture are also highlighted wherever appropriate. Finally, based on this comprehensive review, we identify the current and future trends of the Internet of Things in agriculture and highlight potential research challenges.

Conclusion:

Now the question arises, what are the reasons for the efficiency of these intelligent systems based on the Internet of Things (IoT)? Communication with different parts of the world through communication tools, quick access to information, efficiency of time and human activity, and efficient communication will answer this question.

Author Contributions:

M.P.A: Data Preparation and Review, Software, Resources, Results Interpretation, Writing-Original Draft Preparation, Visualization, Project Administration. I.H: Methodology, Formal Analysis and Investigation, Final Review, Funding Acquisition. K.A: Conceptualization, Results Interpretation, Review and Editing, Final report review. A.L: Investigation, Data Curation, Validation, Writing—Review. Results Interpretation, Supervision.

Data Availability Statement

Not applicable.

Acknowledgements

The authors would like to thank all participants of the present study.

Ethical considerations:

The author declares that there is no conflict of interest regarding the publication of this manuscript. In addition, the ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, and redundancies have been completely observed by the author.

Conflict of interest:

The author declares no conflict of interest. 

References

Aayog, N. I. T. I. (2015). Raising agricultural productivity and making farming remunerative for farmers.
Abbasi‐Kesbi, R., Nikfarjam, A., & Nemati, M. (2020). Developed wireless sensor network to supervise the essential parameters in greenhouses for internet of things applications. IET Circuits, Devices & Systems, 14(8), 1258-1264.
Abdalla, Z. F., El-Sawy, S., El-Bassiony, A. E. M., Zhaojun, S., Okasha, A., Bayoumi, Y., ... & Prokisch, J. (2022). Is the Smart Irrigation the Right Strategy under the Global Water Crisis? A Call for Photographical and Drawn Articles. Environment, Biodiversity and Soil Security, 6(2022), 207-221.
Abioye, E. A., Hensel, O., Esau, T. J., Elijah, O., Abidin, M. S. Z., Ayobami, A. S., ... & Nasirahmadi, A. (2022). Precision irrigation management using machine learning and digital farming solutions. AgriEngineering, 4(1), 70-103.
Agrowetter Irrigation Advice. Geisenheim Research Centre. Available online: https://www.dwd.de/DE/leistungen/agrowetter prognose/agroprog.html (accessed on 21 September 2021).
Algeeb, A., Albagul, A., Asseni, A., Khalifa, O., & Jomah, O. S. (2010). Design and fabrication of an intelligent irrigation control system. Advances In Sensors Signals And Materials, 2, 370-375.
Al-Ghobari, H. M., & Mohammad, F. S. (2011). Intelligent irrigation performance: evaluation and quantifying its ability for conserving water in arid region. Applied Water Science, 1(3), 73-83.
Alves, R. G., Maia, R. F., & Lima, F. (2023). Development of a Digital Twin for smart farming: Irrigation management system for water saving. Journal of Cleaner Production, 135920.
Ammar, M., Haleem, A., Javaid, M., Bahl, S., Garg, S. B., Shamoon, A., & Garg, J. (2022). Significant applications of smart materials and Internet of Things (IoT) in the automotive industry. Materials Today: Proceedings, 68, 1542-1549.
Amro, A. (2020). IoT Vulnerability Scanning: A State of the Art. Computer Security, 84-99.
Andales, A. A. (2014, February). Colorado irrigation scheduler. In Proceedings of the 26th Annual Central Plains Irrigation Conference, Burlington, CO (pp. 26-32).
Andales, A. A. (2017, February). Tactical irrigation management using the wise online tool. In Proceedings of the 29th Annual Central Plains Irrigation Conference, Burlington, CO, USA (pp. 21-22).
Angelopoulos, C. M., Nikoletseas, S., & Theofanopoulos, G. C. (2011, October). A smart system for garden watering using wireless sensor networks. In Proceedings of the 9th ACM international symposium on Mobility management and wireless access (pp. 167-170).
AshifuddinMondal, M., & Rehena, Z. (2018). Iot based intelligent agriculture field monitoring system. In 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (pp. 625-629). IEEE.
Atta, R., Boutraa, T., & Akhkha, A. (2011). Smart irrigation system for wheat in Saudi Arabia using wireless sensors network technology. International Journal of Water Resources and Arid Environments, 1(6), 478-482.
Ayaz, M., Ammad-Uddin, M., Sharif, Z., Mansour, A., & Aggoune, E. H. M. (2019). Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk. IEEE access, 7, 129551-129583.
Bagaria, R. (2019). Smart Irrigation and Farm Field monitoring System using Internet of Things. In Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur-India.
Barkunan, S. R., Bhanumathi, V., & Sethuram, J. (2019). Smart sensor for automatic drip irrigation system for paddy cultivation. Computers & Electrical Engineering, 73, 180-193.
Baudoin, W., Nono-Womdim, R., Lutaladio, N., Hodder, A., Castilla, N., Leonardi, C., ... & Duffy, R. (2013). Good agricultural practices for greenhouse vegetable crops: principles for mediterranean climate areas. Fao.
Bersani, C., Ruggiero, C., Sacile, R., Soussi, A., & Zero, E. (2022). Internet of Things Approaches for Monitoring and Control of Smart Greenhouses in Industry 4.0. Energies, 15(10), 3834.
Biswas, A. K., & Tortajada, C. (2019). Water crisis and water wars: myths and realities. International Journal of Water Resources Development, 35(5), 727-731.
Bodkhe, U., Tanwar, S., Bhattacharya, P., & Kumar, N. (2022). Blockchain for precision irrigation: Opportunities and challenges. Transactions on Emerging Telecommunications Technologies, 33(10), e4059.
Bröring, A., Echterhoff, J., Jirka, S., Simonis, I., Everding, T., Stasch, C., ... & Lemmens, R. (2011). New generation sensor web enablement. Sensors, 11(3), 2652-2699.
Brunel, G., Pichon, L., Taylor, J., & Tisseyre, B. (2019). Easy water stress detection system for vineyard irrigation management. In Precision agriculture’19 (pp. 112-120). Wageningen Academic Publishers.
Cardenas-Lailhacar, B., Dukes, M. D., & Miller, G. L. (2010). Sensor-based automation of irrigation on bermudagrass during dry weather conditions. Journal of irrigation and drainage engineering, 136(3), 184-193.
Cays, J. (2021). The Energy Essential: Physical Forces Animate All Things. In An Environmental Life Cycle Approach to Design (pp. 15-38). Springer, Cham.
Cheema, S. M., Khalid, M., Rehman, A., & Sarwar, N. (2019). Plant irrigation and recommender system–iot based digital solution for home garden. In Intelligent Technologies and Applications: First International Conference, INTAP 2018, Bahawalpur, Pakistan, October 23-25, 2018, Revised Selected Papers 1 (pp. 513-525). Springer Singapore.
Cranmer, E. E., Papalexi, M., tom Dieck, M. C., & Bamford, D. (2022). Internet of Things: Aspiration, implementation and contribution. Journal of Business Research, 139, 69-80.
Dagar, R., Som, S., & Khatri, S. K. (2018). Smart farming–IoT in agriculture. In 2018 International Conference on Inventive Research in Computing Applications (ICIRCA) (pp. 1052-1056). IEEE.
Dahane, A., Kechar, B., Meddah, Y., & Benabdellah, O. (2019, October). Automated irrigation management platform using a wireless sensor network. In 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS) (pp. 610-615). IEEE.
Dahnill, D. P., Hood, Z., Adam, A., Ab Razak, M. Z., & Ismail, A. G. (2021). Drip irrigation detection for power outage-prone areas with internet-of-things smart fertigation managemant system. International Journal of Advanced Computer Science and Applications, 12(7).
Dantas, R. A. S., da Gama Neto, M. V., Zyrianoff, I. D., & Kamienski, C. A. (2020, November). The swamp farmer app for iot-based smart water status monitoring and irrigation control. In 2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor) (pp. 109-113). IEEE.
Dlodlo, N., & Kalezhi, J. (2015). The internet of things in agriculture for sustainable rural development. In 2015 international conference on emerging trends in networks and computer communications (ETNCC) (pp. 13-18). IEEE.
Dokhande, A., Bomble, C., Patil, R., Khandekar, P., Dhone, N., & Gode, C. (2019). A review paper on IOT based smart irrigation system. International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), 191-196.
Dong, Y. (2022). Irrigation Scheduling Methods: Overview and Recent Advances. Irrigation and Drainage-Recent Advances.
Dursun, M., & Ozden, S. (2011). A wireless application of drip irrigation automation supported by soil moisture sensors. Scientific Research and Essays, 6(7), 1573-1582.
Elijah, O., Rahman, T. A., Orikumhi, I., Leow, C. Y., & Hindia, M. N. (2018). An overview of Internet of Things (IoT) and data analytics in agriculture: Benefits and challenges. IEEE Internet of things Journal, 5(5), 3758-3773.
Evans, R. G., Iversen, W. M., & Kim, Y. (2011). Integrated decision support, sensor networks, and adaptive control for wireless site-specific sprinkler irrigation. Applied engineering in agriculture, 28(3), 377-387.
Falkenberg, N. R., Piccinni, G., Cothren, J. T., Leskovar, D. I., & Rush, C. M. (2007). Remote sensing of biotic and abiotic stress for irrigation management of cotton. Agricultural water management, 87(1), 23-31.
Farooq, M. S., Riaz, S., Abid, A., Abid, K., & Naeem, M. A. (2019). A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming. Ieee Access, 7, 156237-156271.
Fatkhulloev, A., Gafarova, A., & Hamraqulov, J. (2019, November). The importance of mobile applications in the use of standard water measurements. In 2019 International Conference on Information Science and Communications Technologies (ICISCT) (pp. 1-3). IEEE.
García, L., Parra, L., Jimenez, J. M., Lloret, J., & Lorenz, P. (2020). IoT-based smart irrigation systems: An overview on the recent trends on sensors and IoT systems for irrigation in precision agriculture. Sensors, 20(4), 1042.
Goap, A., Sharma, D., Shukla, A. K., & Krishna, C. R. (2018). An IoT based smart irrigation management system using Machine learning and open source technologies. Computers and electronics in agriculture, 155, 41-49.
Gonçalves, J. M., Nunes, M., Ferreira, S., Jordão, A., Paixão, J., Eugénio, R., ... & Bahcevandziev, K. (2022). Alternate Wetting and Drying in the Center of Portugal: Effects on Water and Rice Productivity and Contribution to Development. Sensors, 22(10), 3632.
Gonzalez-Dugo, V., Zarco-Tejada, P., Nicolás, E., Nortes, P. A., Alarcón, J. J., Intrigliolo, D. S., & Fereres, E. J. P. A. (2013). Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard. Precision Agriculture, 14(6), 660-678.
GS Campos, N., Rocha, A. R., Gondim, R., Coelho da Silva, T. L., & Gomes, D. G. (2019). Smart & green: An internet-of-things framework for smart irrigation. Sensors, 20(1), 190.
Gutiérrez, J., Villa-Medina, J. F., Nieto-Garibay, A., & Porta-Gándara, M. Á. (2013). Automated irrigation system using a wireless sensor network and GPRS module. IEEE transactions on instrumentation and measurement, 63(1), 166-176.  
Hedley, C. B., Roudier, P., Yule, I. J., Ekanayake, J., & Bradbury, S. (2013). Soil water status and water table depth modelling using electromagnetic surveys for precision irrigation scheduling. Geoderma, 199, 22-29.
Hillyer, C. C., & Sayde, C. (2010). A web based advisory service for optimum irrigation management. In 5th National Decennial Irrigation Conference Proceedings, 5-8 December 2010, Phoenix Convention Center, Phoenix, Arizona USA (p. 1). American Society of Agricultural and Biological Engineers.
Hossein Motlagh, N., Mohammadrezaei, M., Hunt, J., & Zakeri, B. (2020). Internet of Things (IoT) and the energy sector. Energies, 13(2): 494.
Hundal, G. S., Laux, C. M., Buckmaster, D., Sutton, M. J., & Langemeier, M. (2023). Exploring Barriers to the Adoption of Internet of Things-Based Precision Agriculture Practices. Agriculture, 13(1), 163.
Işık, M. F., Sönmez, Y., Yılmaz, C., Özdemir, V., & Yılmaz, E. N. (2017). Precision irrigation system (PIS) using sensor network technology integrated with IOS/Android application. Applied Sciences, 7(9), 891.
Izzuddin, T. A., Johari, M. A., Rashid, M. Z. A., & Jali, M. H. (2018). Smart irrigation using fuzzy logic method. ARPN Journal of Engineering and Applied Sciences, 13(2), 1819-6608.
Jagüey, J. G., Villa-Medina, J. F., López-Guzmán, A., & Porta-Gándara, M. Á. (2015). Smartphone irrigation sensor. IEEE Sensors journal, 15(9), 5122-5127.
Jalilvand, E., Tajrishy, M., Hashemi, S. A. G. Z., & Brocca, L. (2019). Quantification of irrigation water using remote sensing of soil moisture in a semi-arid region. Remote Sensing of Environment, 231, 111226.
Jonard, F., Weihermuller, L., Jadoon, K. Z., Schwank, M., Vereecken, H., & Lambot, S. (2011). Mapping field-scale soil moisture with L-band radiometer and ground-penetrating radar over bare soil. IEEE Transactions on Geoscience and Remote Sensing, 49(8), 2863-2875.
Jones, A. S., Andales, A. A., Burzynski, A., Chávez, J. L., David, O., Fletcher, S. J., ... & Smith, G. E. (2020, January). Integrative Hydrometeorological Applications with Precipitation, Soil Moisture, and Water Vapor Using Phone Apps, GIS, and Data Assimilation. In 100th American Meteorological Society Annual Meeting. AMS.
Jyothipriya, A. N., & Saravanabava, T. P. (2013). Design of embedded systems for drip irrigation automation. Int. J. Engr. Sci. Invention, 2(4), 34-37.
Kelly, B. F. J., Acworth, R. I., & Greve, A. K. (2011). Better placement of soil moisture point measurements guided by 2D resistivity tomography for improved irrigation scheduling. Soil Research, 49(6), 504-512.
Khan, N. A., Qijie, G., Sertse, S. F., Nabi, M. N., & Khan, P. (2020). Farmers’ use of mobile phone-based farm advisory services in Punjab, Pakistan. Information Development, 36(3), 390-402.
Khriji, S., El Houssaini, D., Kammoun, I., & Kanoun, O. (2021). Precision irrigation: an IoT-enabled wireless sensor network for smart irrigation systems. In Women in precision agriculture (pp. 107-129). Springer, Cham.
Kim, Y., Evans, R. G., & Iversen, W. M. (2008). Remote sensing and control of an irrigation system using a distributed wireless sensor network. IEEE transactions on instrumentation and measurement, 57(7), 1379-1387.
Kodali, R. K., Jain, V., & Karagwal, S. (2016). IoT based smart greenhouse. In 2016 IEEE region 10 humanitarian technology conference (R10-HTC) (pp. 1-6). IEEE.
Krishnan, R. S., Julie, E. G., Robinson, Y. H., Raja, S., Kumar, R., & Thong, P. H. (2020). Fuzzy logic based smart irrigation system using internet of things. Journal of Cleaner Production, 252, 119902.
Kseneman, M., Gleich, D., & Potočnik, B. (2012). Soil-moisture estimation from TerraSAR-X data using neural networks. Machine Vision and Applications, 23(5), 937-952.
Leh, N. A. M., Kamaldin, M. S. A. M., Muhammad, Z., & Kamarzaman, N. A. (2019). Smart irrigation system using internet of things. In 2019 IEEE 9th International Conference on System Engineering and Technology (ICSET) (pp. 96-101). IEEE.
Leinonen, I., & Jones, H. G. (2004). Combining thermal and visible imagery for estimating canopy temperature and identifying plant stress. Journal of experimental botany, 55(401), 1423-1431.
Levidow, L., Zaccaria, D., Maia, R., Vivas, E., Todorovic, M., & Scardigno, A. (2014). Improving water-efficient irrigation: Prospects and difficulties of innovative practices. Agricultural Water Management, 146, 84-94.
Levorato, A. (2017). The Internet of Things in the agroindustrial sector: John Deere case study.
Li, Z., Wang, J., Higgs, R., Zhou, L., & Yuan, W. (2017). Design of an intelligent management system for agricultural greenhouses based on the internet of things. In 2017 IEEE international conference on computational science and engineering (CSE) and IEEE international conference on embedded and ubiquitous computing (EUC) (Vol. 2, pp. 154-160). IEEE.
Li, Z., Wang, J., Higgs, R., Zhou, L., & Yuan, W. (2017). Design of an intelligent management system for agricultural greenhouses based on the internet of things. In 2017 IEEE international conference on computational science and engineering (CSE) and IEEE international conference on embedded and ubiquitous computing (EUC) (Vol. 2, pp. 154-160). IEEE.
Li, Z., Wang, N., Hong, T., Franzen, A., & Li, J. (2011). Closed-loop drip irrigation control using a hybrid wireless sensor and actuator network. Science China Information Sciences, 54(3), 577-588.
Maiga, J., Suyoto, S., & Pranowo, P. (2021, March). Mobile app design for sustainable agriculture in Mali-West Africa. In IOP Conference Series: Materials Science and Engineering (Vol. 1098, No. 3, p. 032037). IOP Publishing.
Maiga, J., Suyoto, S., & Pranowo, P. (2021, March). Mobile app design for sustainable agriculture in Mali-West Africa. In IOP Conference Series: Materials Science and Engineering (Vol. 1098, No. 3, p. 032037). IOP Publishing.
Mani Sai Jyothi, P., & Nandan, D. (2020). Utilization of the internet of things in agriculture: possibilities and challenges. Soft Computing: Theories and Applications, 837-848.
Manonmani, R., & Rose, R. S. (2017). Participatory GIS for irrigation management in periyar main canal command area—A case study of kumaram village, madurai district. Int. J. Sci. Res. Sci. Technol, 3, 865-875.
Mbabazi, D., Migliaccio, K. W., Crane, J. H., Fraisse, C., Zotarelli, L., Morgan, K. T., & Kiggundu, N. (2017). An irrigation schedule testing model for optimization of the Smartirrigation avocado app. Agricultural Water Management, 179, 390-400.
Migliaccio, K. W., Andreis, J. D., Fraisse, C., Morgan, K. T., & Vellidis, G. (2013). Smartirrigation Apps: Urban Turf: AE499, 10/2013. EDIS, 2013(9).
Migliaccio, K. W., Morgan, K. T., Vellidis, G., Zotarelli, L., Fraisse, C., Rowland, D. L., ... & Zurweller, B. A. (2015). Smartphone apps for irrigation scheduling. In 2015 ASABE/IA Irrigation Symposium: Emerging Technologies for Sustainable Irrigation-A Tribute to the Career of Terry Howell, Sr. Conference Proceedings (pp. 1-16). American Society of Agricultural and Biological Engineers.
Miraz, M. H., Ali, M., Excell, P. S., & Picking, R. (2015). A review on Internet of Things (IoT), Internet of everything (IoE) and Internet of nano things (IoNT). 2015 Internet Technologies and Applications (ITA), 219-224.
Munir, M. S., Bajwa, I. S., & Cheema, S. M. (2019). An intelligent and secure smart watering system using fuzzy logic and blockchain. Computers & Electrical Engineering, 77, 109-119.
Munir, M. S., Bajwa, I. S., Ashraf, A., Anwar, W., & Rashid, R. (2021). Intelligent and smart irrigation system using edge computing and IoT. Complexity, 2021.
Muñoz-Carpena, R., & Dukes, M. D. (2005). Automatic Irrigation Based on Soil Moisture for Vegetable Crops: ABE356/AE354, 6/2005. EDIS, 2005(8).
Mustafa, M., Abbas, A., Bsoul, Q., & Shabbir, A. (2021). Smart Irrigation System Based on the Internet of Things and the Cloud.
Nagajayanthi, B. (2022). Decades of Internet of Things Towards Twenty-first Century: A Research-Based Introspective. Wireless Personal Communications, 123(4), 3661-3697.
Navarro, E., Costa, N., & Pereira, A. (2020). A systematic review of IoT solutions for smart farming. Sensors, 20(15), 4231.
Nawandar, N. K., & Satpute, V. R. (2019). IoT based low cost and intelligent module for smart irrigation system. Computers and electronics in agriculture, 162, 979-990.
Nikolidakis, S. A., Kandris, D., Vergados, D. D., & Douligeris, C. (2015). Energy efficient automated control of irrigation in agriculture by using wireless sensor networks. Computers and Electronics in Agriculture, 113, 154-163.
Obaideen, K., Yousef, B. A., AlMallahi, M. N., Tan, Y. C., Mahmoud, M., Jaber, H., & Ramadan, M. (2022). An overview of smart irrigation systems using IoT. Energy Nexus, 100124.
Ogidan, O. K., & Afia, K. R. (2019, September). Smart irrigation system with an android-based remote logging and control. In 2019 IEEE AFRICON (pp. 1-4). IEEE.
Ogubuike, R., Adib, A., & Orji, R. (2021, October). Masa: AI-adaptive mobile app for sustainable agriculture. In 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (pp. 1064-1069). IEEE.
Okolie, C. C., Danso-Abbeam, G., Groupson-Paul, O., & Ogundeji, A. A. (2023). Climate-Smart Agriculture Amidst Climate Change to Enhance Agricultural Production: A Bibliometric Analysis. Land, 12(1), 50.
Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033.
O'Shaughnessy, S. A., & Evett, S. R. (2010). Canopy temperature based system effectively schedules and controls center pivot irrigation of cotton. Agricultural Water Management, 97(9), 1310-1316.
Pardossi, A., Incrocci, L., Incrocci, G., Malorgio, F., Battista, P., Bacci, L., ... & Balendonck, J. (2009). Root zone sensors for irrigation management in intensive agriculture. Sensors, 9(4), 2809-2835.
Patel, V. B., Thakkar, R. G., & Ahuja, D. S. (2014). Agricultural android application. Int. J. Comput. Sci. Technol, 5, 326-328.
Patil, V. C., Al-Gaadi, K. A., Biradar, D. P., & Rangaswamy, M. (2012). Internet of things (Iot) and cloud computing for agriculture: An overview. Proceedings of agro-informatics and precision agriculture (AIPA 2012), India, 292-296.
Perea, R. G., García, I. F., Arroyo, M. M., Díaz, J. R., Poyato, E. C., & Montesinos, P. (2017). Multiplatform application for precision irrigation scheduling in strawberries. Agricultural Water Management, 183, 194-201.
Pérez-Castro, A., Sánchez-Molina, J. A., Castilla, M., Sánchez-Moreno, J., Moreno-Úbeda, J. C., & Magán, J. J. (2017). cFertigUAL: A fertigation management app for greenhouse vegetable crops. Agricultural water management, 183, 186-193.
Peters, R. T., & Evett, S. R. (2008). Automation of a center pivot using the temperature-time-threshold method of irrigation scheduling. Journal of irrigation and drainage engineering, 134(3), 286-291.
Playán, E., & Mateos, L. (2006). Modernization and optimization of irrigation systems to increase water productivity. Agricultural water management, 80(1-3), 100-116.
Pourgholam-Amiji, M. (2021). The Benefits, Applications, and Challenges of the IoT in Irrigation. Water Management in Agriculture, 7(2), 47-66.
Rajalakshmi, P., & Mahalakshmi, S. D. (2016). IOT based crop-field monitoring and irrigation automation. In 2016 10th International Conference on Intelligent Systems and Control (ISCO) (pp. 1-6). IEEE.
Rajurkar, C., Prabaharan, S. R. S., & Muthulakshmi, S. (2017, March). IoT based water management. In 2017 International Conference on Nextgen Electronic Technologies: Silicon to Software (ICNETS2) (pp. 255-259). IEEE.
Rayhana, R., Xiao, G., & Liu, Z. (2020). Internet of things empowered smart greenhouse farming. IEEE Journal of Radio Frequency Identification, 4(3), 195-211.
Riezzo, E. E., Zippitelli, M., Impedovo, D., Todorovic, M., Cantore, V., & Buono, V. (2013). Hydro‐Tech: an integrated decision support system for sustainable irrigation management (II): software and hardware architecture. CIGR Proceedings, 1(1), 443-486.
Roopaei, M., Rad, P., & Choo, K. K. R. (2017). Cloud of things in smart agriculture: Intelligent irrigation monitoring by thermal imaging. IEEE Cloud computing, 4(1), 10-15.
Rowshon, M. K., Amin, M. S. M., Lee, T. S., & Shariff, A. R. M. (2009). GIS-integrated rice irrigation management information system for a river-fed scheme. Water resources management, 23(14), 2841-2866.
Rusdi, J. F., Salam, S., Abu, N. A., Sunaryo, B., Naseer, M., Rismayadi, D. A., ... & Shanono, N. M. (2021, April). Field reporting irrigation system via smartphone. In Journal of Physics: Conference Series (Vol. 1807, No. 1, p. 012012). IOP Publishing.
Salam, A. (2020). Internet of things in agricultural innovation and security. In Internet of Things for Sustainable Community Development (pp. 71-112). Springer, Cham.
Salih, J. M., Adom, A. H., & Shaakaf, A. M. (2012). Solar Powered automated fertigation control system for cucumis melo L. cultivation in green house. APCBEE procedia, 4, 79-87.
Samreen, T., Ahmad, M., Baig, M. T., Kanwal, S., & Nazir, M. Z. (2023). Remote Sensing in Precision Agriculture for Irrigation Management. Environmental Sciences Proceedings, 23(1), 1-4.
Serra, P. M. D., & Espírito-Santo, A. (2021). Sourcing power with microbial fuel cells: A timeline. Journal of Power Sources, 482, 228921.
Sharma, D., Bhondekar, A. P., Ojha, A., Shukla, A. K., & Ghanshyam, C. (2016). A technical assessment of IOT for Indian agriculture sector. Int. J. Comput. Applic.
Sheikh, J. A., Cheema, S. M., Ali, M., Amjad, Z., Tariq, J. Z., & Naz, A. (2021). IoT and AI in precision agriculture: Designing smart system to support illiterate farmers. In Advances in Artificial Intelligence, Software and Systems Engineering: Proceedings of the AHFE 2020 Virtual Conferences on Software and Systems Engineering, and Artificial Intelligence and Social Computing, July 16-20, 2020, USA (pp. 490-496). Springer International Publishing.
Shi, X., An, X., Zhao, Q., Liu, H., Xia, L., Sun, X., & Guo, Y. (2019). State-of-the-art internet of things in protected agriculture. Sensors, 19(8), 1833.
Simionesei, L., Ramos, T. B., Palma, J., Oliveira, A. R., & Neves, R. (2020). IrrigaSys: A web-based irrigation decision support system based on open source data and technology. Computers and Electronics in Agriculture, 178, 105822.
Simionesei, L., Ramos, T. B., Palma, J., Oliveira, A. R., & Neves, R. (2020, March). IrrigaSys–a decision support system for irrigation management in the Sorraia Valley region, Portugal. In EGU General Assembly Conference Abstracts (p. 9488).
Singh, T., Verma, A., & Singh, M. (2021). Development and implementation of an IOT based instrumentation system for computing performance of a tractor-implement system. Journal of Terramechanics, 97, 105-118.
Sinha, B. B., & Dhanalakshmi, R. (2022). Recent advancements and challenges of Internet of Things in smart agriculture: A survey. Future Generation Computer Systems, 126, 169-184.
Soumyalatha, S. G. H. (2016, May). Study of IoT: understanding IoT architecture, applications, issues and challenges. In 1st International Conference on Innovations in Computing & Net-working (ICICN16), CSE, RRCE. International Journal of Advanced Networking & Applications (Vol. 478).
Stanghellini, C. (2013). Horticultural production in greenhouses: efficient use of water. In International Symposium on Growing Media and Soilless Cultivation 1034 (pp. 25-32).
Stočes, M., Vaněk, J., Masner, J., & Pavlík, J. (2016). Internet of things (iot) in agriculture-selected aspects. Agris on-line Papers in Economics and Informatics, 8(665-2016-45107), 83-88.
Stokke, A. F. (2019). The use of mobile phones in the extension and advisory service in Rwanda (Doctoral dissertation).
Subashini, M. M., Das, S., Heble, S., Raj, U., & Karthik, R. (2018). Internet of things based wireless plant sensor for smart farming. Indonesian Journal of Electrical Engineering and Computer Science, 10(2), 456-468.
Talekar, P. S., Kumar, A., Kumar, A., Kumar, M., & Hashmi, M. I. (2021). Smart irrigation monitoring system using Blynk app. Int. J. Innov. Sci. Res. Technol, 6, 1353-1355.
Todorovic, M., Riezzo, E. E., Buono, V., Zippitelli, M., Galiano, A., & Cantore, V. (2016). Hydro-Tech: An automated smart-tech Decision Support Tool for eco-efficient irrigation management. Int. Agric. Eng. J, 25(2), 44-45.
Tzounis, A., Katsoulas, N., Bartzanas, T., & Kittas, C. (2017). Internet of Things in agriculture, recent advances and future challenges. Biosystems engineering, 164, 31-48.
Vaishali, S., Suraj, S., Vignesh, G., Dhivya, S., & Udhayakumar, S. (2017, April). Mobile integrated smart irrigation management and monitoring system using IOT. In 2017 international conference on communication and signal processing (ICCSP) (pp. 2164-2167). IEEE.
Vaitheeka, N., & Kumar, S. M. (2018). Cognitive intelligence of internet of things (IoT) in agriculture industry-a primer study on smart farming. International Journal of Pure and Applied Mathematics, 118(20), 1835-1841.
Vellidis, G., Liakos, V., Andreis, J. H., Perry, C. D., Porter, W. M., Barnes, E. M., ... & Migliaccio, K. W. (2016). Development and assessment of a smartphone application for irrigation scheduling in cotton. Computers and Electronics in Agriculture, 127, 249-259.
Vellidis, G., Liakos, V., Perry, C., Tucker, M., Collins, G., Snider, J., ... & Barnes, E. (2014, January). A smartphone app for scheduling irrigation on cotton. In Proceedings of the 2014 Beltwide Cotton Conference, New Orleans, LA, USA (Vol. 7).
Vuolo, F., Essl, L., & Atzberger, C. (2015). Costs and benefits of satellite-based tools for irrigation management. Frontiers in Environmental Science, 3, 52.
Zajac, Z., Gomez, O., Gelati, E., van der Velde, M., Bassu, S., Ceglar, A., ... & Fumagalli, D. (2022). Estimation of spatial distribution of irrigated crop areas in Europe for large-scale modelling applications. Agricultural Water Management, 266, 107527.
Zaragoza, C. A., Perea, R. G., García, I. F., Poyato, E. C., & Díaz, J. A. R. (2020). Open source application for optimum irrigation and fertilization using reclaimed water in olive orchards. Computers and electronics in agriculture, 173, 105407.
Zhang, H., & Li, M. (2025). Towards an intelligent and automatic irrigation system based on internet of things with authentication feature in VANET. Journal of Information Security and Applications, 88, 103927.
Zhang, S., Guo, Y., Li, S., Ke, Z., Zhao, H., Yang, J., ... & Zhang, Z. (2022). Investigation on environment monitoring system for a combination of hydroponics and aquaculture in greenhouse. Information Processing in Agriculture, 9(1), 123-134.
Zhu, X., Chikangaise, P., Shi, W., Chen, W. H., & Yuan, S. (2018). Review of intelligent sprinkler irrigation technologies for remote autonomous system. International Journal of Agricultural & Biological Engineering, 11(1), 23-30.
Iranian Journal of Soil and Water Research
Volume 55, Issue 9
November 2024
Pages 1647-1678

Files

Share

How to cite

Statistics