Internet of things technology in agricultural crop monitoring
DOI:
https://doi.org/10.35290/ro.v4n3.2023.939Keywords:
data processing, agricultural crops, agromatics, monitoringAbstract
Internet of Things (IoT) plays an important role in the agricultural sectors because it provides benefits such as crop development and production improvement. As there are various articles that show their usefulness, the purpose of this work is to systematically analyze them to extract data on IoT systems focused on monitoring agricultural crops. As part of the review protocol, four questions were posed aimed at learning more about the way in which monitoring is carried out, the components used, the functionalities, and the data collected by the devices. Using four of the popular databases in the area, 41 articles were selected. From the data extraction it was possible to know the use of IoT devices with a certain preference towards mobile applications and a tendency to use the following components: ESP8266, YL-69, DTH-1 and Arduino. In addition, among the identified functionalities we can mention the soil monitoring, the growth and the crop yield, the invasion of animals, automatic irrigation, among others. Finally, several tens of types of data collected by the devices such as environmental parameters and soil characteristics were found. All these data help in the characterization of the IoT systems of interest and can serve as a basis for the development of others.
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Abbassi, Y., & Benlahmer, H. (2021). The Internet of Things at the service of tomorrow’s agriculture. Procedia Computer Science, 191, 475–480. https://doi.org/10.1016/J.PROCS.2021.07.060 DOI: https://doi.org/10.1016/j.procs.2021.07.060
Al-Atwan, N., & Nitulescu, M. (2020). Design and Test an Intelligent Irrigation System for Small Surfaces. 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020. https://doi.org/10.1109/ICECCE49384.2020.9179269 DOI: https://doi.org/10.1109/ICECCE49384.2020.9179269
Anitha, A., Sampath, N., & Jerlin, M. (2020). Smart Irrigation system using Internet of Things. International Conference on Emerging Trends in Information Technology and Engineering, Ic-ETITE 2020. https://doi.org/10.1109/IC-ETITE47903.2020.271 DOI: https://doi.org/10.1109/ic-ETITE47903.2020.271
Audrey, D., Stanley, Tabaraka, K., Lazaro, A., & Budiharto, W. (2021). Monitoring Mung Bean’s Growth using Arduino. Procedia Computer Science, 179, 352–360. https://doi.org/10.1016/J.PROCS.2021.01.016 DOI: https://doi.org/10.1016/j.procs.2021.01.016
Baldovino, R., Valenzuela, I., & Dadios, E. (2019). Implementation of a low-power wireless sensor network for smart farm applications. 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2018. https://doi.org/10.1109/HNICEM.2018.8666262 DOI: https://doi.org/10.1109/HNICEM.2018.8666262
Bazán-Vera, W., Bermeo-Almeida, O., Samaniego-Cobo, T., Alarcón-Salvatierra, A., Rodríguez-Méndez, A., & Bazán-Vera, V. (2017). “The current state and effects of agromatic: a systematic literature review”. In Valencia-García, R., Lagos-Ortiz, K., Alcaraz-Mármol, G., Del Cioppo, J., Vera-Lucio, N., Bucaram-Leverone, M. (Eds.). Technologies and Innovation. CITI 2017. Communications in Computer and Information Science, 749, (pp. 269–281). Springer. https://doi.org/10.1007/978-3-319-67283-0_20 DOI: https://doi.org/10.1007/978-3-319-67283-0_20
Borah, S., Kumar, R., & Mukherjee, S. (2020). Study of RTPPS algorithm in UWB communication medium for a surveillance system to protect agricultural crops from wild animals. Proceedings - 2020 6th IEEE International Symposium on Smart Electronic Systems, ISES 2020, 121–126. https://doi.org/10.1109/ISES50453.2020.00036 DOI: https://doi.org/10.1109/iSES50453.2020.00036
Chandra, R., & Collis, S. (2021). Digital agriculture for small-scale producers. Communications of the ACM, 64(12), 75–84. https://doi.org/10.1145/3454008 DOI: https://doi.org/10.1145/3454008
Dahiya, S., Gulati, T., & Gupta, D. (2022). Performance analysis of deep learning architectures for plant leaves disease detection. Measurement: Sensors, 24. https://doi.org/10.1016/J.MEASEN.2022.100581 DOI: https://doi.org/10.1016/j.measen.2022.100581
Deivakani, M., Singh, C., Bhadane, J., Ramachandran, G., & Sanjeev Kumar, N. (2021). ANN Algorithm based Smart Agriculture Cultivation for Helping the Farmers. Proceedings - 2nd International Conference on Smart Electronics and Communication, ICOSEC 2021. https://doi.org/10.1109/ICOSEC51865.2021.9591713 DOI: https://doi.org/10.1109/ICOSEC51865.2021.9591713
Dholu, M., & Ghodinde, K. A. (2018). Internet of Things (IoT) for Precision Agriculture Application. Proceedings of the 2nd International Conference on Trends in Electronics and Informatics, ICOEI 2018, 339–342. https://doi.org/10.1109/ICOEI.2018.8553720. DOI: https://doi.org/10.1109/ICOEI.2018.8553720
Dos Santos, U., Pessin, G., da Costa, C., & da Rosa Righi, R. (2019). AgriPrediction: A proactive internet of things model to anticipate problems and improve production in agricultural crops. Computers and Electronics in Agriculture, 161, 202–213. https://doi.org/10.1016/J.COMPAG.2018.10.010. DOI: https://doi.org/10.1016/j.compag.2018.10.010
Dragulinescu, A., Balaceanu, C., Osiac, F., Roscaneanu, R., Chedea, V., Suciu, G., Paun, M., & Bucuci, S. (2021). IoT-based Smart Water Management Systems. 2021 IEEE 27th International Symposium for Design and Technology in Electronic Packaging, SIITME 2021 - Conference Proceedings, 51–56. https://doi.org/10.1109/SIITME53254.2021.9663611 DOI: https://doi.org/10.1109/SIITME53254.2021.9663611
El Mezouari, A., El Fazziki, A., & Sadgal, M. (2022). Smart Irrigation System. IFAC-PapersOnLine, 55(10), 3298–3303. https://doi.org/10.1016/J.IFACOL.2022.10.125 DOI: https://doi.org/10.1016/j.ifacol.2022.10.125
Farooq, M. S., Riaz, S., Abid, A., Abid, K., & Naeem, M. (2019). A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming. IEEE Access, 7, 156237–156271. https://doi.org/10.1109/ACCESS.2019.2949703 DOI: https://doi.org/10.1109/ACCESS.2019.2949703
Farooq, M. S., Riaz, S., Abid, A., Umer, T., & Zikria, Y. (2020). Role of iot technology in agriculture: A systematic literature review. Electronics2020, 9(2). https://doi.org/10.3390/electronics9020319 DOI: https://doi.org/10.3390/electronics9020319
Gamal, Y., Gadallah, S., Osama, A., Soltan, A., & Madian, A. (2022). IOT-based air quality monitoring system for agriculture. 2022 - 4th Novel Intelligent and Leading Emerging Sciences Conference (Niles), 206–210. https://doi.org/10.1109/NILES56402.2022.9942441 DOI: https://doi.org/10.1109/NILES56402.2022.9942441
Gans, R., Ubacht, J., & Janssen, M. (2020). Self-sovereign Identities for Fighting the Impact of COVID-19 Pandemic. Digital Government: Research and Practice, 2(2), 1–4. https://doi.org/10.1145/3429629 DOI: https://doi.org/10.1145/3429629
Guerrero-Ulloa, G., Andrango-Catota, A., Abad-Alay, M., Hornos, M., & Rodríguez-Domínguez, C. (2023a). Development and Assessment of an Indoor Air Quality Control IoT-Based System. Electronics2023, 12(3), 608. https://doi.org/10.3390/electronics12030608 DOI: https://doi.org/10.3390/electronics12030608
Guerrero-Ulloa, G., Méndez-García, A., Torres-Lindao, V., Zamora-Mecías, V., Rodríguez-Domínguez, C., & Hornos, M. (2023b). Internet of Things (IoT)-based indoor plant care system. Journal of Ambient Intelligence and Smart Environments, 15(1), 47–62. https://doi.org/10.3233/AIS-220483 DOI: https://doi.org/10.3233/AIS-220483
Guerrero-Ulloa, G., Rodríguez-Domínguez, C., & Hornos, M. (2023c). Agile Methodologies Applied to the Development of Internet of Things (IoT)-Based Systems: A Review. Sensors2023, 23(2). 790. https://doi.org/10.3390/s23020790 DOI: https://doi.org/10.3390/s23020790
Gupta, A., & Nahar, P. (2023). Classification and yield prediction in smart agriculture system using IoT. Journal of Ambient Intelligence and Humanized Computing, 14(8), 10235–10244. https://doi.org/10.1007/s12652-021-03685-w DOI: https://doi.org/10.1007/s12652-021-03685-w
Hernández-Morales, C., Luna-Rivera, J., & Pérez-Jiménez, R. (2022). Design and deployment of a practical IoT-based monitoring system for protected cultivations. Computer Communications, 186, 51–64. https://doi.org/10.1016/J.COMCOM.2022.01.009 DOI: https://doi.org/10.1016/j.comcom.2022.01.009
Hyunjin, C., & Sainan, H. (2021). A study on the design and operation method of plant factory using artificial intelligence. Nanotechnology for Environmental Engineering, 6(3), 1–5. https://link.springer.com/article/10.1007/s41204-021-00136-x DOI: https://doi.org/10.1007/s41204-021-00136-x
Kelebekler, E. (2021). Monitoring and recording system of laboratory environmental conditions as ISO/IEC 17025 requirement. 2021 International Conference on INnovations in Intelligent SysTems and Application ( INISTA). https://doi.org/10.1109/INISTA52262.2021.9548498 DOI: https://doi.org/10.1109/INISTA52262.2021.9548498
Khan, P., & Karna, L. (2021). Green House System Design Using IOT. Proceedings of the 5th International Conference on Electronics, Communication and Aerospace Technology ( ICECA), 522–526. https://doi.org/10.1109/ICECA52323.2021.9676064 DOI: https://doi.org/10.1109/ICECA52323.2021.9676064
Lekbangpong, N., Muangprathub, J., Srisawat, T., & Wanichsombat, A. (2019). Precise Automation and Analysis of Environmental Factor Effecting on Growth of St. John’s Wort. IEEE Access, 7, 112848–112858. https://doi.org/10.1109/ACCESS.2019.2934743 DOI: https://doi.org/10.1109/ACCESS.2019.2934743
Lova Raju, K., & Vijayaraghavan, V. (2022). A Self-Powered, Real-Time, NRF24L01 IoT-Based Cloud-Enabled Service for Smart Agriculture Decision-Making System. Wireless Personal Communications, 124(1), 207–236. http://dx.doi.org/10.21203/rs.3.rs-586227/v1 DOI: https://doi.org/10.1007/s11277-021-09462-4
Malhotra, A., Som, S., & Khatri, S. (2019). IOT Aided Techniques for Agriculture. 2019 4th International Conference on Information Systems and Computer Network (ISCON), 129–133. https://doi.org/10.1109/ISCON47742.2019.9036174 DOI: https://doi.org/10.1109/ISCON47742.2019.9036174
Mazo-Zuluaga, I. (2020). Identificación del volcamiento en un cultivo experimental de maíz, a partir de imágenes RGB adquiridas con una aeronave remotamente tripulada, en el departamento de caldas [Tesis de Maestría, Universidad Católica de Manizales]. https://repositorio.ucm.edu.co/handle/10839/3367
Mekala, M., & Viswanathan, P. (2019). CLAY-MIST: IoT-cloud enabled CMM index for smart agriculture monitoring system. Measurement, 134, 236–244. https://doi.org/10.1016/J.MEASUREMENT.2018.10.072 DOI: https://doi.org/10.1016/j.measurement.2018.10.072
Mekala, M., & Viswanathan, P. (2020). Sensor Stipulation with THAM Index for Smart Agriculture Decision-Making IoT System. Wireless Personal Communications, 111(8), 1909–1940. https://doi.org/10.1007/S11277-019-06964-0/METRICS DOI: https://doi.org/10.1007/s11277-019-06964-0
Mohammad EL-Basioni, B., Mohamed, E., Belal, A., Jalhoum, M., Abd EL-Kader, S., & Zahran, M. (2022). A case study of a real-time internet of things system for site-specific potato crop management in El-Salhia Area-Egypt. Scientific Reports, 12(1), 1–29. https://doi.org/10.1038/S41598-022-22690-3/FIGURES/29 DOI: https://doi.org/10.1038/s41598-022-22690-3
Mondal, A., & Dutta, P. (2022). Boltuino Platform Based Cognitive Irrigation System with Weather Adaptability for Efficient Water Use. International Conference on ICT for Smart Society (ICISS). https://doi.org/10.1109/ICISS55894.2022.9915196 DOI: https://doi.org/10.1109/ICISS55894.2022.9915196
Moreno, B., Muñoz, M., Cuellar, J., Domancic, S., & Villanueva, J. (2018). Revisiones Sistemáticas: definición y nociones básicas. Revista Clínica de Periodoncia, Implantología y Rehabilitación Oral, 11(3), 184–186. https://doi.org/10.4067/s0719-01072018000300184 DOI: https://doi.org/10.4067/S0719-01072018000300184
Muangprathub, J., Boonnam, N., Kajornkasirat, S., Lekbangpong, N., Wanichsombat, A., & Nillaor, P. (2019). IoT and agriculture data analysis for smart farm. Computers and Electronics in Agriculture, 156, 467–474. https://doi.org/10.1016/J.COMPAG.2018.12.011 DOI: https://doi.org/10.1016/j.compag.2018.12.011
Oliveira-JR, A., Resende, C., Gonçalves João, Soares Filipe., & Moreira Waldir. (2020). IoT Sensing Platform for e-Agriculture in Africa. 2020 IST-Africa Conference (IST-Africa). https://ieeexplore.ieee.org/document/9144060
Panda, P., Kumar, C., Vivek, B., Balachandra, M., & Dargar, S. (2022). Implementation of a Wild Animal Intrusion Detection Model Based on Internet of Things. 2022 Second International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022, 1256–1261. https://doi.org/10.1109/ICAIS53314.2022.9742948 DOI: https://doi.org/10.1109/ICAIS53314.2022.9742948
Pathak, A., Uddin, M., Jainal Abedin, M., Andersson, K., Mustafa, R., & Hossain, M. (2019). IoT based Smart System to Support Agricultural Parameters: A Case Study. Procedia Computer Science, 155, 648–653. https://doi.org/10.1016/J.PROCS.2019.08.092. DOI: https://doi.org/10.1016/j.procs.2019.08.092
Perales, Á., López-de-Teruel, P., Ruiz, A., García-Mateos, G., Bernabé García, G., & García, F. (2022). FARMIT: continuous assessment of crop quality using machine learning and deep learning techniques for IoT-based smart farming. Cluster Computing, 25(1), 2163–2178. http://dx.doi.org/10.1007/s10586-021-03489-9. DOI: https://doi.org/10.1007/s10586-021-03489-9
Ponce, J., Erazo Moreta, O., & Vicuña Pino, A. (2021). Técnicas estadísticas aplicadas a la caracterización de cacao con enfoque agromática. Revista San Gregorio, 1(46). https://doi.org/10.36097/rsan.v1i46.1527.
Quezada-Sarmiento, P. A., (2017). Implementación de una solución web y móvil para la gestión vehicular basada en Arquitectura de Aspectos y metodologías ágiles: Un enfoque educativo de la teoría a la práctica. Risti. Revista Ibérica de Sistemas e Tecnologías de Informação, (25), 1–14. https://doi.org/10.17013/risti.25.98-111. DOI: https://doi.org/10.17013/risti.25.98-111
Rajkumar, M., Abinaya, S., & Kumar, V. (2017). Intelligent irrigation system - An IOT based approach. 2017 International Conference on Innovations in Green Energy and Healthcare Technologies (IGEHT). https://doi.org/10.1109/IGEHT.2017.8094057. DOI: https://doi.org/10.1109/IGEHT.2017.8094057
Roy, S., Sowmya, B., Seema, S., Rajeshwari, S., & Vinutha, M. (2019). Utility System for Elevating Pre and Post Production of Crops. 2019 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER). https://doi.org/10.1109/DISCOVER47552.2019.9008103 DOI: https://doi.org/10.1109/DISCOVER47552.2019.9008103
Sachan, R., Kaur, S., & Shukla, A. (2021). Smart Irrigation and Security System for Agricultural Crops and Trees. 2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO). https://doi.org/10.1109/ICRITO51393.2021.9596246. DOI: https://doi.org/10.1109/ICRITO51393.2021.9596246
Sharma, A., Kumar, H., Mittal, K., Kauhsal, S., Kaushal, M., Gupta, D., & Narula, A. (2021). IoT and deep learning-inspired multi-model framework for monitoring Active Fire Locations in Agricultural Activities. Computers & Electrical Engineering, 93. https://doi.org/10.1016/J.COMPELECENG.2021.107216. DOI: https://doi.org/10.1016/j.compeleceng.2021.107216
Singh, P., & Sharma, A. (2022). An intelligent WSN-UAV-based IoT framework for precision agriculture application. Computers and Electrical Engineering, 100. https://doi.org/10.1016/J.COMPELECENG.2022.107912. DOI: https://doi.org/10.1016/j.compeleceng.2022.107912
Sinha, B., & Dhanalakshmi, R. (2022). Recent advancements and challenges of Internet of Things in smart agriculture: A survey. Future Generation Computer Systems, 126, 169–184. https://doi.org/10.1016/j.future.2021.08.006 DOI: https://doi.org/10.1016/j.future.2021.08.006
Sushanth, G., & Sujatha, S. (2018). IOT Based Smart Agriculture System. 2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). https://doi.org/10.1109/WISPNET.2018.8538702 DOI: https://doi.org/10.1109/WiSPNET.2018.8538702
Tephila, M., Sri, R., Abinaya, R., Lakshmi, J., & Divya, V. (2022). Automated Smart Irrigation System using IoT with Sensor Parameter. 2022 International Conference on Electronics and Renewable Systems (ICEARS), 543–549. https://doi.org/10.1109/ICEARS53579.2022.9751993 DOI: https://doi.org/10.1109/ICEARS53579.2022.9751993
Thirrunavukkarasu, R., Meeradevi, T., Ganesh Prabhu, S., Arunachalam, J., Manoj Kumar, P., & Prasath, R. (2021). Smart Irrigation and Crop Protection Using Arduino. 2021 7th International Conference on Advanced Computing and Communication Systems, ICACCS 2021, 639–643. https://doi.org/10.1109/ICACCS51430.2021.9441867. DOI: https://doi.org/10.1109/ICACCS51430.2021.9441867
Tiglao, N., Alipio, M., Balanay, J., Saldivar, E., & Tiston, J. (2020). Agrinex: A low-cost wireless mesh-based smart irrigation system. Measurement, 161. https://doi.org/10.1016/J.MEASUREMENT.2020.107874. DOI: https://doi.org/10.1016/j.measurement.2020.107874
Tovar, J., Solórzano, J. D. los S., Badillo, A., & Rodríguez Cainaba, G. (2019). Internet de las cosas aplicado a la agricultura: estado actual. Lámpsakos, (22), 86–105. https://doi.org/10.21501/21454086.3253 DOI: https://doi.org/10.21501/21454086.3253
Turner, M. (2010). Digital Libraries and Search Engines for Software Engineering Research: An Overview. January 2010, 1–11. http://ebse.webspace.durham.ac.uk/wp-content/uploads/sites/49/2022/08/SearchEngineIndex_v5.pdf.
Tzounis, A., Katsoulas, N., Bartzanas, T., & Kittas, C. (2017). Internet of Things in agriculture, recent advances and future challenges. Biosystems Engineering, 164, 31–48. https://doi.org/10.1016/j.biosystemseng.2017.09.007. DOI: https://doi.org/10.1016/j.biosystemseng.2017.09.007
Vásquez-Bermúdez, M., Hidalgo, J., Crespo-León, K., & Cadena-Iturralde, J. (2019). Citizen Science in Agriculture Through ICTs. A Systematic Review. In: Valencia-García, R., Alcaraz-Mármol, G., Cioppo-Morstadt, J., Vera-Lucio, N., Bucaram-Leverone, M. (Eds.). ICT for Agriculture and Environment. CITAMA2019 2019. Advances in Intelligent Systems and Computing, 901, (pp. 111–121). Springer. https://doi.org/10.1007/978-3-030-10728-4_12 DOI: https://doi.org/10.1007/978-3-030-10728-4_12
Venkatesh, J., Ramasamy, K., Aruna, M., Praveen, K., Sasikala, N., & Nasani, K. (2022). EAgri: Smart Agriculture Monitoring Scheme using Machine Learning Strategies. 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES). https://doi.org/10.1109/ICSES55317.2022.9914216 DOI: https://doi.org/10.1109/ICSES55317.2022.9914216
Verdouw, C., Wolfert, S., & Tekinerdogan, B. (2016). Internet of things in agriculture. CABI Reviews, 11(35)., 1-12. https://doi.org/10.1079/PAVSNNR201611035. DOI: https://doi.org/10.1079/PAVSNNR201611035
Wu, J. (2022). Crop Growth Monitoring System Based on Agricultural Internet of Things Technology. Journal of Electrical and Computer Engineering, 2022, 1–10. https://doi.org/10.1155/2022/8466037 DOI: https://doi.org/10.1155/2022/8466037
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