The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Fuzzy Logic based Smart Irrigation System using Internet of Things
Abstract
Abstract Traditional agricultural systems require huge amount of power for field watering. This paper proposes a smart irrigation system that helps farmers water their agricultural fields using Global System for Mobile Communication (GSM). This system provides acknowledgement messages about the job’s statuses such as humidity level of soil, temperature of surrounding environment, and status of motor regarding main power supply or solar power. Fuzzy logic controller is used to compute input parameters (e.g. soil moisture, temperature and humidity) and to produce outputs of motor status. In addition, the system also switches off the motor to save the power when there is an availability of rain and also prevents the crop using panels from unconditional rain. The comparison is made between the proposed system, drip irrigation and manual flooding. The comparison results prove that water and power conservation are obtained through the proposed smart irrigation system.
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Citations
Cites
Fuzzy Logic with Engineering Applications
Ross, T. J. (2010) · Wiley eBooks · doi:10.1002/9781119994374 · Cited by 6,597
Salemink, K., Strijker, D., & Bosworth, G. (2017) · Journal of Rural Studies · doi:10.1016/j.jrurstud.2015.09.001 · Cited by 1,101
Automated Irrigation System Using a Wireless Sensor Network and GPRS Module
Gutierrez, J., Villa-Medina, J. F., Nieto-Garibay, A., & Porta-Gandara, M. A. (2014) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2013.2276487 · Cited by 914
An IoT based smart irrigation management system using Machine learning and open source technologies
Goap, A., Sharma, D., Shukla, A. K., & Rama Krishna, C. (2018) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2018.09.040 · Cited by 676
Decision support tools for agriculture: Towards effective design and delivery
Rose, D. C., Sutherland, W. J., Parker, C., Lobley, M., Winter, M., Morris, C., Twining, S., Ffoulkes, C., Amano, T., & Dicks, L. V. (2016) · Agricultural Systems · doi:10.1016/j.agsy.2016.09.009 · Cited by 528
Philip, L., Cottrill, C., Farrington, J., Williams, F., & Ashmore, F. (2017) · Journal of Rural Studies · doi:10.1016/j.jrurstud.2016.12.002 · Cited by 347
A decision support system for managing irrigation in agriculture
Navarro-Hellín, H., Martínez-del-Rincon, J., Domingo-Miguel, R., Soto-Valles, F., & Torres-Sánchez, R. (2016) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2016.04.003 · Cited by 318
Applications of Smartphone-Based Sensors in Agriculture: A Systematic Review of Research
Pongnumkul, S., Chaovalit, P., & Surasvadi, N. (2015) · Journal of Sensors · doi:10.1155/2015/195308 · Cited by 223
A Novel Framework for Trash Classification Using Deep Transfer Learning
Vo, A. H., Son, L. H., Vo, M. T., & Le, T. (2019) · IEEE Access · doi:10.1109/access.2019.2959033 · Cited by 222
Self-citationSon, L. H., Kumar, A., Sangwan, S. R., Arora, A., Nayyar, A., & Abdel-Basset, M. (2019) · IEEE Access · doi:10.1109/access.2019.2899260 · Cited by 206
Self-citation
Cited by
Sarker, I. H. (2022) · SN Computer Science · doi:10.1007/s42979-022-01043-x · Cited by 1,208
Metadata
- Authors
- Krishnan, R. S., Julie, E. G., Robinson, Y. H., Raja, S., Kumar, R., Thong, P. H., & Son, L. H.
- Venue
- Journal of Cleaner Production
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 252
- Pages
- 119902
- ISSN
- 0959-6526 (ISSN-L)
- OpenAlex
- W2998133044
- Cited by
- 269
- References
- 34
- FWCI
- 18.83
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
