Integrating innovative technologies for sustainable agricultural water management

Shuaib Ajetunmobi Abdulrasaq; Bilal Acar; Nadia Riaz

doi:10.21657/soilst.1996164

EN

Integrating innovative technologies for sustainable agricultural water management

Abstract

Agricultural water scarcity poses an escalating threat to global food production, driven by population growth, climate variability, and the inherent inefficiencies of conventional irrigation systems. This paper analyzes the transformational capacity of smart technologies like the Internet of Things (IoT), Artificial Intelligence (AI) and Machine Learning (ML), and Remote Sensing (RS) integrated with Geographic Information Systems (GIS) for sustainable agricultural water management. By synthesizing recent empirical studies, the paper analyzes the integrated effect of sensor-based monitoring, predictive analytics, automated irrigation control, and satellite and drone surveillance on water-use efficiency, irrigation optimization, and climate-resilient agriculture. Key findings indicate that IoT-based smart irrigation systems reduce water consumption by 20–55% and improve crop yields by 10-30% under optimized conditions, particularly when used with AI-driven decision-support platforms. RS and GIS technologies enable scalable, cost-effective estimation of evapotranspiration and crop water stress across field to regional scales. Despite these demonstrated benefits, substantial barriers to adoption persist, including high implementation costs, inadequate rural digital infrastructure, limited technical literacy among smallholder farmers, and insufficient policy frameworks. This review emphasized the need for supportive policies, cost-reduction strategies, and capacity-building initiatives to bridge the gap between technological innovation and field-level implementation. Overall, smart water management technologies offered a promising pathway toward sustainable agriculture, improved food security, and responsible water stewardship in an increasingly water-scarce world.

Keywords

References

Abbasi, R., Martinez, P., & Ahmad, R. (2022). The digitization of agricultural industry – a systematic literature review on agriculture 4.0. Smart Agricultural Technology, 2, 100042. https://doi.org/10.1016/j.atech.2022.100042
Abioye, E. A., Hensel, O., Esau, T. J., Elijah, O., Abidin, M. S. Z., Ayobami, A. S., Yerima, O., & Nasirahmadi, A. (2022). Precision Irrigation Management Using Machine Learning and Digital Farming Solutions. AgriEngineering, 4(1), 70–103. https://doi.org/10.3390/agriengineering4010006
Ahmed, Z., Gui, D., Murtaza, G., Yunfei, L., & Ali, S. (2023). An Overview of Smart Irrigation Management for Improving Water Productivity under Climate Change in Drylands. Agronomy, 13(8), 2113. https://doi.org/10.3390/agronomy13082113
Akanbi, M., Adedotun, K., Raji, A., & Banjoko, I. (2025). Optimizing Water Resource Management in Agriculture Using AI-Powered Solar Irrigation Systems. Journal of Science Innovation and Technology Research.
Al Mashhadany, Y., Alsanad, H., Abdulsalam, M., Algburi, S., & Taha, B. (2024). Irrigation intelligence—Enabling a cloud-based Internet of Things approach for enhanced water management in agriculture. Environmental Monitoring and Assessment, 196. https://doi.org/10.1007/s10661-024-12606-1
Alahmad, T., Neményi, M., & Nyéki, A. (2023). Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review. Agronomy, 13(10), 2603. https://doi.org/10.3390/agronomy13102603
Al-Bakri, J. T., D’Urso, G., Calera, A., Abdalhaq, E., Altarawneh, M., & Margane, A. (2022). Remote Sensing for Agricultural Water Management in Jordan. Remote Sensing, 15(1), 235. https://doi.org/10.3390/rs15010235
Alharbi, S., Felemban, A., Abdelrahim, A., & Al-Dakhil, M. (2024). Agricultural and Technology-Based Strategies to Improve Water-Use Efficiency in Arid and Semiarid Areas. Water, 16(13), 1842. https://doi.org/10.3390/w16131842

Ali, A., Hussain, T., & Zahid, A. (2025). Smart Irrigation Technologies and Prospects for Enhancing Water Use Efficiency for Sustainable Agriculture. AgriEngineering, 7(4), 106. https://doi.org/10.3390/agriengineering7040106
Almheiri, M. S. M. A., Bashir, H., Ojiako, U., Haridy, S., & Shamsuzzaman, M. (2024). Examining the Challenges of Implementing Artificial Intelligence in the Water Supply Sector: A Case Study. Water, 16(23), 3539. https://doi.org/10.3390/w16233539 Amertet Finecomess, S., Gebresenbet, G., & Alwan, H. M. (2024). Utilizing an Internet of Things (IoT) Device, Intelligent Control Design, and Simulation for an Agricultural System. IoT, 5(1), 58–78. https://doi.org/10.3390/iot5010004
Amnuaylojaroen, T., Limsakul, A., & Chanvichit, P. (2024). Assessing the Impact of Climate Change on Agricultural Water Management in Mainland Southeast Asia. Advances in Meteorology, 2024. Scopus. https://doi.org/10.1155/2024/1653062
Anusha, M. K. (2024). Automated Irrigation System Using Temperature Sensor and Soil Humidity Sensor. International Journal for Research in Applied Science and Engineering Technology, 12(6), 1365–1370. https://doi.org/10.22214/ijraset.2024.63315
Arduino. (2023). Arduino UNO R3 datasheet (Document No. A000066). Arduino Documentation. https://docs.arduino.cc/resources/datasheets/A000066-datasheet.pdf
Arularasan, R., K.P, R. P., Vinitha, R., Praveena, T., Nithila, E. E., & Ravi, S. (2024). Smart Irrigation: Enhancing Agricultural Efficiency with IoT-Connected Drones and Machine Learning. 2024 IEEE North Karnataka Subsection Flagship International Conference (NKCon), 1–6. https://doi.org/10.1109/nkcon62728.2024.10775252
Aryan, A., Mohammed, A. A., Chabra, M., Rasheed, S. S., Adnan, M., & Raoof, M. A. (2024). Precision Agriculture: Enhancing Crop Yield and Water Efficiency with Smart Irrigation Systems. 2024 4th International Conference on Innovative Sustainable Computational Technologies (CISCT), 1–6. https://doi.org/10.1109/cisct62494.2024.11134212
Ashour, M. A., Abdel Nasser, M. S., & Abu-Zaid, T. S. (2024). Evaluation of the effects of improving tertiary earthen canals on water savings, conveyance efficiency, and agricultural productivity. Ain Shams Engineering Journal, 15(8), 102850. https://doi.org/10.1016/j.asej.2024.102850
Athelly, A., Guzmán, S. M., Yu, Z., & Watson, J. A. (2025). Bridging the gap between water-saving technologies and adoption in vegetable farming: Insights from Florida, USA. Frontiers in Agronomy, Volume 7-2025. https://doi.org/10.3389/fagro.2025.1622260
Baek, S., Lee, J. J., Shin, J., Kim, J. H., Hong, S., & Kim, S. (2022). Resistive Water Level Sensors Based on AgNWs/PEDOT:PSS-g-PEGME Hybrid Film for Agricultural Monitoring Systems. ACS Omega, 7(18), 15459–15466. https://doi.org/10.1021/acsomega.2c00017
Balasooriya, T. N., Mantri, P., & Suriyampola, P. (2020). IoT-Based Smart Watering System Towards Improving the Efficiency of Agricultural Irrigation. 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), 1–7. https://doi.org/10.1109/gcaiot51063.2020.9345902
Balassem, Z. A., Mahdi A. A., & Nadimpalli, V. G. R. (2025). Investigating Internet of Things and Artificial Intelligence-Based Approaches to Smart Irrigation System Optimisation for Agricultural Water Resource Management. SHS Web of Conferences 216:1059. https://doi.org/10.1051/shsconf/202521601059
Balendonck, J., Tuzel, I. H., Tunali, U., Oztekin, G. B., & Tuzel, Y. (2021). Performance evaluation of the AquaTag, a prototype near-field RF-based soil moisture sensor. 2021 13th International Conference on Electromagnetic Wave Interaction with Water and Moist Substances (ISEMA), 1–6. https://doi.org/10.1109/isema49699.2021.9508292
Bamurigire, P., Vodacek, A., Valkó, A., & Ngoga, S. R. (2020). Simulation of internet of things water management for efficient rice irrigation in Rwanda. Agriculture (Switzerland), 10(10), 1–12. Scopus. https://doi.org/10.3390/agriculture10100431
Bautista-Capetillo, C., Pineda-Martínez, H., Flores-Chaires, L. A., & Pineda-Martínez, L. F. (2025). Agriculture Resilient at Three Irrigation Modules of Zacatecas, Mexico: Water Scarcity and Climate Variability. Agronomy, 15(4), 800. https://doi.org/10.3390/agronomy15040800
Bazrafkan, A., Kim, J., Proulx, R., & Lin, Z. (2025). Automated Detection of Center-Pivot Irrigation Systems from Remote Sensing Imagery Using Deep Learning. Remote Sensing, 17(13), 2276. https://doi.org/10.3390/rs17132276
Benyamina, B., & Hanane, G. (2025). Multispectral Indices for Crop Water Stress Assessment and Precision Irrigation in Arid Agriculture: A Case Study from Béchar, Algeria. International Journal of Computational and Experimental Science and Engineering, 11(3). https://doi.org/10.22399/ijcesen.3414
Bhaba, K.K, Joyt, D., Asaruddin S., Samiran D. & Pritam Singh B. (2025). Smart Farming Revolution: AI, IoT, and Robotics in Precision Agriculture and Soil Conservation. International Journal of Scientific Research in Science, Engineering and Technology, 12(2), 688–706. https://doi.org/10.32628/ijsrset25122193
Bhargav Reddy, M., & Vijayreddy, D. (2025). The Recent Applications of Remote sensing in Agriculture-A Review. Journal of Agriculture Biotechnology & Applied Sciences, 1(2), 28–35. https://doi.org/10.63143/jabaas.2120233
Bhattacharyya, A., Sarkar, S., Karmakar, I., Saha, S., & Dutta, J. (2025). Revolutionizing Smart Farming with AI, IoT, and Earth Observation for Precision Agriculture. 2025 International Conference on Computing, Intelligence, and Application (CIACON), 1–6. https://doi.org/10.1109/ciacon65473.2025.11189708
Bhavsar, D., Limbasia, B., Mori, Y., Imtiyazali Aglodiya, M., & Shah, M. (2023). A comprehensive and systematic study in smart drip and sprinkler irrigation systems. Smart Agricultural Technology, 5, 100303. https://doi.org/10.1016/j.atech.2023.100303
Bispo, R. C., Hernandez, F. B. T., Gonçalves, I. Z., Neale, C. M. U., & Teixeira, A. H. C. (2022). Remote sensing-based evapotranspiration modeling for sugarcane in Brazil using a hybrid approach. Agricultural Water Management, 271, 107763. https://doi.org/10.1016/j.agwat.2022.107763
Borankulova, G., Altybayev, G., Tungatarova, A., Yeraliyeva, B., Dulatbayeva, S., Murzakhmetov, A., & Bekbolatov, S. (2025). Development of Real-Time Water-Level Monitoring System for Agriculture. Sensors, 25(17), 5564. https://doi.org/10.3390/s25175564
Bwambale, E., Abagale, F. K., & Anornu, G. K. (2022). Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review. Agricultural Water Management, 260, 107324. https://doi.org/10.1016/j.agwat.2021.107324
Calera, A. (2015). Remote Sensing for Crop Water Management. Agrociencia, 19(3), 77. https://doi.org/10.31285/agro.19.289
Chakraborty, M., Malkani, A., & Biswas, K. (2019). Hand-held soil moisture meter using polymer coated sensor. IEEE Instrumentation & Measurement Magazine, 22(5), 24–29. https://doi.org/10.1109/imm.2019.8868273
Chand, J., Acharya, R., Pandey, R., Paudel, M., & Bimali, S. (2025). Automation in drip irrigation system: A comprehensive review with mathematical modeling and optimization algorithms. International Journal of Sustainable Agricultural Research, 12(1), 67–80.
Chaudhry, S., & Garg, S. (2019). Smart Irrigation Techniques for Water Resource Management. Advances in Environmental Engineering and Green Technologies, 196–219. https://doi.org/10.4018/978-1-5225-5909-2.ch009
Chen, Y., Devon S., Hieu T. T., Yan S. S. Y., Soomin S., & Woo S. K. (2025). Precision Irrigation with AI-Driven Optimization of Plant Electrophysiology. Smart Agricultural Technology 12:101169. https://doi.org/10.1016/j.atech.2025.101169
Choudhary, S. M. (2025). Integration of Remote Sensing Technology for Smart Agriculture System. International Journal for Research in Applied Science and Engineering Technology, 13(7), 204–209. https://doi.org/10.22214/ijraset.2025.72970
Chouhan, S., Smita K., Rajneesh K., & Pravin L. C. (2023). Climate Resilient Water Management for Sustainable Agriculture. International Journal of Environment and Climate Change 13(7):411–26. https://doi.org/10.9734/ijecc/2023/v13i71894
Corbari, C., Al Bitar, A., Skokovic, D., Sobrino, J. & mancini, M. (2022). Irrigation management though the assimilation of multiple remote sensing data into an energy-water-crop model. https://doi.org/10.5194/egusphere-egu22-10127
Dahlmann, H., Andersen, L. S., Schaphoff, S., Stenzel, F., Braun, J., Müller, C., & Gerten, D. (2025). Shifting water scarcities: Irrigation alleviates agricultural green water deficits while increasing blue water scarcity. https://doi.org/10.5194/egusphere-2025-3817
Das, A., Gupta, Y., Wedhane, N. V., & Islam, Md. R. (2021). Smart Water Management in Irrigation System Using IoT. Lecture Notes in Electrical Engineering, 341–352. https://doi.org/10.1007/978-981-33-6393-9_35
Deng, C., & Zhu, Z. (2020). Continuous subpixel monitoring of urban impervious surface using Landsat time series. Remote Sensing of Environment, 238, 110929. https://doi.org/10.1016/j.rse.2018.10.011 Devi, V. B., Privadharshini, K., Haritha, M., & others. (2025). Smart Irrigation System by Detecting Plant Squeals Using IoT. 2025 International Conference on Computing and Communication Technologies (ICCCT), 1–8.
Diallo, M. C. A., Santos, R. C., Gomes, E. P., Machado, C. A. C., Dias, C. R. A., Santos, E. C. dos, Padilha, G. A. C., Belarmino, M. D., Galiaso, M., Riffel, A. S., Silva, E. A. S. da, & Lovatto, J. (2024). Challenges of smart irrigation implementation in water optimization and agricultural sustainability. CONTRIBUCIONES A LAS CIENCIAS SOCIALES, 17(13). https://doi.org/10.55905/revconv.17n.13-270
Dibbern, T., Romani, L. A. S., & Massruhá, S. M. F. S. (2024). Main drivers and barriers to the adoption of Digital Agriculture technologies. Smart Agricultural Technology, 8, 100459. https://doi.org/10.1016/j.atech.2024.100459
Dziuba, O., Custódio, C., Silva, C. O., Granja-Martins, F. M., Lança, R., & Fernandez, H. M. (2025). GIS-Based Site Selection for Agricultural Water Reservoirs: A Case Study of São Brás de Alportel, Portugal. Sustainability, 17(22). https://doi.org/10.3390/su172210276
Elshaikh, A., E. Elsheikh, & J. Mabrouki. (2024). Applications of Artificial Intelligence in Precision Irrigation. Journal of Environmental and Earth Sciences 6(2):176–86. https://doi.org/10.30564/jees.v6i2.6679
El-Shirbeny, M. A., Ali, Abdelraouf. M., Savin, I., Poddubskiy, A., & Dokukin, P. (2020). Agricultural Water Monitoring for Water Management Under Pivot Irrigation System Using Spatial Techniques. Earth Systems and Environment, 5(2), 341–351. https://doi.org/10.1007/s41748-020-00164-8
Emon, M. J. H., Hussain, S. M., Islam, A., & Ahmed, S. S. (2025). Integration of IoT, Machine Learning, and Sensors for Intelligent Environmental Monitoring and Agricultural Development. Journal of Computer Networks and Communications.
Erekalo, K. T., Pedersen, S. M., Christensen, T., Denver, S., Gemtou, M., Fountas, S., & Isakhanyan, G. (2024). Review on the contribution of farming practices and technologies towards climate-smart agricultural outcomes in a European context. Smart Agricultural Technology, 7, 100413. https://doi.org/10.1016/j.atech.2024.100413
Espressif Systems. (2024). ESP32 series datasheet (Version 5.2). https://www.espressif.com/sites/default/files/documentation/esp32_datasheet_en.pd
Fernández, J. E., Alcon, F., Diaz-Espejo, A., Hernandez-Santana, V., & Cuevas, M. (2020). Water use indicators and economic analysis for on-farm irrigation decision: A case study of a super high-density olive tree orchard. Agricultural Water Management, 237, 106074.
Fu, P., Meacham-Hensold, K., Guan, K., Wu, J., & Bernacchi, C. J. (2020). Estimating photosynthetic traits from reflectance spectra: A synthesis of spectral indices, numerical inversion, and partial least square regression. Plant, Cell and Environment, 43(5), 1241–1258. Scopus. https://doi.org/10.1111/pce.13718
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. https://doi.org/10.3390/s20041042
Gautam, D., & Pagay, V. (2020). A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops. Agronomy, 10(1), 140. https://doi.org/10.3390/agronomy10010140
Gebresenbet, G., Bosona, T., Patterson, D., Persson, H., Fischer, B., Mandaluniz, N., Chirici, G., Zacepins, A., Komasilovs, V., Pitulac, T., & Nasirahmadi, A. (2023). A concept for application of integrated digital technologies to enhance future smart agricultural systems. Smart Agricultural Technology, 5, 100255. https://doi.org/10.1016/j.atech.2023.100255
Gonçalves, I. Z., Ruhoff, A., Laipelt, L., Bispo, R. C., Hernandez, F. B. T., Neale, C. M. U., Teixeira, A. H. C., & Marin, F. R. (2022). Remote sensing-based evapotranspiration modeling using geeSEBAL for sugarcane irrigation management in Brazil. Agricultural Water Management, 274, 107965. https://doi.org/10.1016/j.agwat.2022.107965
Gopathoti, K. K., Gopatoti, A., Swathi, N., & Pendyala, S. S. (2024). Enhancing Crop Water Management: A Logistic Regression Approach Integrated with IoT for Smart Irrigation. International Journal of Scientific Methods in Computational Science and Engineering, 1(1), 1–8. https://doi.org/10.58599/ijsmcse.2024.1104
Grant, S., Harden, A., Coggins, K., Parker, D., Tabei, F., & Askarian, B. (2024). A Comprehensive Comparison of IoT Soil Moisture Sensors for Agricultural Applications. 2024 IEEE 17th Dallas Circuits and Systems Conference (DCAS), 1–6. https://doi.org/10.1109/dcas61159.2024.10539876 Gul, D., & Banday, R. U. Z. (2024). Transforming crop management through advanced AI and machine learning: Insights into innovative strategies for sustainable agriculture. AI, Computer Science and Robotics Technology.
Gurung, S., Thakur, S., Smithers, B., & Acevedo, M. (2020). Wireless soil moisture sensor networks for agriculture. 2020 Waste-Management Education Research (WERC), 1–9. https://doi.org/10.1109/werc49736.2020.9146500
Güven, A. E., Yücel, M., & Utündağ, B. B. (2025). Daily evapotranspiration estimation across Türkiye with limited sensor data using machine learning. In Proceedings of Agro-Geoinformatics 2025 Conference.
Hachisuca, A. M. M., de Souza, E. G., Oliveira, W. K. M., Bazzi, C. L., Donato, D. G., Mendes, I. de S., Abdala, M. C., & Mercante, E. (2023). AgDataBox-IoT - application development for agrometeorological stations in smart. MethodsX, 11, 102419. https://doi.org/10.1016/j.mex.2023.102419
Hadipour, M., Derakhshandeh, J. F., & Shiran, M. A. (2020). An experimental setup of multi-intelligent control system (MICS) of water management using the Internet of Things (IoT). ISA Transactions, 96, 309–326.
Hafian, A., Benbrahim, M., & Kabbaj, M. N. (2023). IoT-based smart irrigation management system using real-time data. International Journal of Electrical and Computer Engineering (IJECE), 13(6), 7078. https://doi.org/10.11591/ijece.v13i6.pp7078-7088
Haripriya, R., Sangeetha, P., Sindhuja, K., & Monica, S. (2024). Advanced Approach of Predictive Algorithm Using IoT Based Soil Moisture Monitoring System for Effective Irrigation. International Journal of Progressive Sciences and Technologies, 45(2), 668. https://doi.org/10.52155/ijpsat.v45.2.7126
Hassan, E. S., Alharbi, A. A., Oshaba, A. S., & El-Emary, A. (2024). Enhancing Smart Irrigation Efficiency: A New WSN-Based Localization Method for Water Conservation. Water, 16(5), 672. https://doi.org/10.3390/w16050672
Hassan, N., Hasib Cheragee, S., Ahammed, S., & Md. Touhidul Islam, A. Z. (2021). Sensor based Smart Irrigation System with Monitoring and Controlling using Internet of Things. The International Journal of Ambient Systems and Applications, 9(2), 17–26. https://doi.org/10.5121/ijasa.2021.9203
Hatton, N., Sharda, A., Schapaugh, W., & van der Merwe, D. (2020). Remote thermal infrared imaging for rapid screening of sudden death syndrome in soybean. Computers and Electronics in Agriculture, 178, 105738. https://doi.org/10.1016/j.compag.2020.105738
Hussein, M. A., Riga, F. T., Derseh, M. B., Assefa, T. T., Worqlul, A. W., Haileslassie, A., Adie, A., Jones, C. S., & Tilahun, S. A. (2024). Application of Irrigation Management and Water-Lifting Technologies to Enhance Fodder Productivity in Smallholder Farming Communities: A Case Study in Robit Bata, Ethiopia. Agronomy.
Inayah, I., Agustirandi, B., Budiman, M., Djamal, M., & Faizal, A. (2025). Experimental design: Implementation of IoT-based drip irrigation to enhance the productivity of Cilembu sweet potato (Ipomoea batatas) cultivation. Results in Engineering, 25, 103600.
Industry Research. (2026). Soil moisture monitoring system market report. https://www.industryresearch.biz/market-reports/soil-moisture-monitoring-system-market-109644
Irfan, F., Zaka, R., Rehman, S., Sattar, B., Haider, S.A., & Hayat, M.A. (2025). An IoT-driven smart agriculture framework for precision farming, resource optimization, and crop health monitoring. Academia International Journal for Social Sciences 4(3), 3329–3342. https://doi.org/10.63056/acad.004.03.0615
Ishore, B., Bhargav, A. M., Patel, S. K., Kumar, V., Sinha, J., & Kumar, S. (2025). Advancing Smart Agriculture: How IoT and 5G Technologies Enhance Precision Farming and Sustainability. International Journal of Communication Systems, 39(1). https://doi.org/10.1002/dac.70310
Jaiswal, N., Kumar, T. V., & Shukla, C. (2025). Smart drip irrigation systems using IoT: a review of architectures, machine learning models, and emerging trends. Discover Agriculture, 3(1), 253.
Kamienski, C., Soininen, J.-P., Taumberger, M., Dantas, R., Toscano, A., Salmon Cinotti, T., Filev Maia, R., & Torre Neto, A. (2019). Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture. Sensors, 19(2), 276. https://doi.org/10.3390/s19020276
Kang, S., Hao, X., Du, T., Tong, L., Su, X., Lu, H., Li, X., Huo, Z., Li, S., & Ding, R. (2017). Improving agricultural water productivity to ensure food security in China under changing environment: From research to practice. Agricultural Water Management, 179, 5–17. https://doi.org/10.1016/j.agwat.2016.05.007
Khupse, S. M., & Ramteke, P. L. (2025). IoT-Enabled Smart Irrigation System for Efficient Water and Nutrient Management. EPJ Web of Conferences, 341, 1034. https://doi.org/10.1051/epjconf/202534101034
Köksal, D. D., Ahi, Y., & Todorovic, M. (2025). Assessing Agricultural Reuse Potential of Treated Wastewater: A Hybrid Machine Learning Approach. Agronomy, 15(3), 703. https://doi.org/10.3390/agronomy15030703
Komal, K., Joon, R., Juneja, R., saluja, H., Nisha, N., & Nikhil, N. (2025). Smart Irrigation System Using IoT for Precision Agriculture and Water Conservation. International Journal of Scientific Research In Engineering And Management, 09, 1–9. https://doi.org/10.55041/IJSREM50738
Krishna, S., Natarajan, R., Premkumar, A., Irudayasamy, A., Mahadev, N., & Thangarasu, N. (2025). Weather-Aware Smart Irrigation System Using Temporal Fusion Transformer for Precision Agriculture. 2025 International Conference on Computing Technologies &Amp; Data Communication (ICCTDC), 1–6. https://doi.org/10.1109/icctdc64446.2025.11158052
Kuli, B., Debnath, J., Sheikh, A., Das, S., & Balai, P.S. (2025). Smart Farming Revolution: AI, IoT, and Robotics in Precision Agriculture and Soil Conservation. International Journal of Scientific Research in Science, Engineering and Technology, 12(2), 688–706. https://doi.org/10.32628/ijsrset25122193
Kumar, K., & Yadav, R. K. (2024). Maximizing Agricultural Water Efficiency: Integrating Iot and Supervised Learning for Smart Irrigation Optimization. International Journal of Research - GRANTHAALAYAH, 12(6).https://doi.org/10.29121/granthaalayah.v12.i6.2024.5663
Kumar, T. P., Supriya, G., Papnoi, P., Patri, S. R., & Katkoori, S. (2022). Low Power IoT Soil Moisture Sensor Node for Smart Irrigation. 2022 IEEE International Symposium on Smart Electronic Systems (iSES), 107–111.
Kumar, V., Singh, C. D., Rao, K. R., Kumar, M., Rajwade, Y. A., Babu, B., & Singh, K. (2023). Evaluation of IoT based smart drip irrigation and ETc based system for sweet corn. Smart Agricultural Technology, 5, 100248.
Kushwaha, Y. K., Joshi, A., Panigrahi, R. K., & Pandey, A. (2024). Development of a smart irrigation monitoring system employing the wireless sensor network for agricultural water management. Journal of Hydroinformatics, 26(12), 3224–3243. https://doi.org/10.2166/hydro.2024.241
Leher. (n.d.). Uses and benefits of drones in agriculture. https://www.leher.ag/blogs/uses-and-benefits-of-drones-in-agriculture
Lei, F., Crow, W. T., Kustas, W. P., Dong, J., Yang, Y., Knipper, K. R., Anderson, M. C., Gao, F., Notarnicola, C., Greifeneder, F., McKee, L. M., Alfieri, J. G., Hain, C., & Dokoozlian, N. (2020). Data assimilation of high-resolution thermal and radar remote sensing retrievals for soil moisture monitoring in a drip-irrigated vineyard. Remote Sensing of Environment, 239, 111622. https://doi.org/10.1016/j.rse.2019.111622
Lena, B. P., Bondesan, L., Pinheiro, E. A. R., Ortiz, B. V., Morata, G. T., & Kumar, H. (2022). Determination of irrigation scheduling thresholds based on HYDRUS-1D simulations of field capacity for multilayered agronomic soils in Alabama, USA. Agricultural Water Management, 259, 107234. https://doi.org/10.1016/j.agwat.2021.107234
Liu, J., Xu, Y., Li, H., & Guo, J. (2021). Soil moisture retrieval in farmland areas with sentinel multi-source data based on regression convolutional neural networks. Sensors, 21(3), 1–21. Scopus. https://doi.org/10.3390/s21030877
Machireddy, S. R. (2025). Geospatial Technology Approach for Soil Moisture Estimation in Kurnool District, Andhra Pradesh, Using NDVI and LST. Sensing and Imaging, 26(1), 62. https://doi.org/10.1007/s11220-025-00598-2
Madhavi, N., Shruthi, G., Srishanth, M., Laxmi, T.V.P., Siddhartha, G., & Manish, L. (2025). Smart farming – precision agriculture using ML. International Research Journal on Advanced Engineering and Management 3(4), 1035–1041. https://doi.org/10.47392/irjaem.2025.0169
Mafuta, M., Zennaro, M., Bagula, A., Ault, G., Gombachika, H., & Chadza, T. (2013). Successful deployment of a wireless sensor network for precision agriculture in Malawi. International Journal of Distributed Sensor Networks, 9(5), 150703.
Maraveas, C. (2023). Incorporating Artificial Intelligence Technology in Smart Greenhouses: Current State of the Art. Applied Sciences (Switzerland), 13(1). Scopus. https://doi.org/10.3390/app13010014
Mishra, V. K., Awasthi, M. K., Kumar, L., & Sharma, S. K. (2025). Integrating Remote Sensing and GIS for Irrigated Area Mapping in the Betwa River Basin, India. Journal of Scientific Research and Reports, 31(10), 709–721. https://doi.org/10.9734/jsrr/2025/v31i103615
Mohiuddin, M., Islam, Md. S., & Shanjida, S. (2024). Internet of Things (IoT)-Based Smart Agriculture Irrigation and Monitoring System Using Ubidots Server. ECSA-11, 99. https://doi.org/10.3390/ecsa-11-20528
Morchid, A., Alblushi, I. G. M., Khalid, H. M., Qjidaa, H., & El Alami, R. (2025). Integrating IoT and fuzzy logic for intelligent irrigation in sustainable agriculture for improving water scarcity: Benefits and challenges. Sustainable Computing: Informatics and Systems, 48, 101191. https://doi.org/10.1016/j.suscom.2025.101191
Morchid, A., El Alami, R., Raezah, A. A., & Sabbar, Y. (2024). Applications of internet of things (IoT) and sensors technology to increase food security and agricultural Sustainability: Benefits and challenges. Ain Shams Engineering Journal, 15(3). Scopus. https://doi.org/10.1016/j.asej.2023.102509
Msamadya, S., Joo, J. C., Lee, J. M., Choi, J. S., Lee, S., Lee, D. J., Go, H. W., Jang, S. Y., & Lee, D. H. (2022). Role of Water Policies in the Adoption of Smart Water Metering and the Future Market. Water, 14(5), 826. https://doi.org/10.3390/w14050826
Nagabhooshanam, N., Sharma, K., Kaur, M., Singh, R., & Murthy, N. B. C. S. N. (2025). Enhancing agricultural water management through sensor-based irrigation systems. Toxicological & Environmental Chemistry, 107(10), 1996–2009. https://doi.org/10.1080/02772248.2025.2580608
Naganjali, K., N. Charitha, Sk. Aslam, A. Saikishore, D. Sravanthi, K. Siddappa, K. Gopala Krishna Murthy, J. Hemantha Kumar, P. Neelima, and T. Pavani. 2024. “Revamping Water Use in Agriculture: Techniques and Emerging Innovations.” Journal of Scientific Research and Reports 30(7):1055–66. https://doi.org/10.9734/jsrr/2024/v30i72215
Nagappan, M., Swetha J., and Aarthika K. (2025). Advanced Prediction of Crop Water Requirements Using Machine Learning Models. International Journal of Innovative Science and Research Technology 2518–23. https://doi.org/10.38124/ijisrt/25feb1206
Nikam, Prof. D. A., Bujare, Mr. H. M., Gavali, Mr. S. P., Patil, Mr. A. M., Konuri, Mr. P. T., & Desai, Miss. S. B. (2024). Smart Agriculture Automation System using ML. International Journal for Research in Applied Science and Engineering Technology, 12(4), 755–758. https://doi.org/10.22214/ijraset.2024.59848
Oğuztürk, G. E. (2025). AI-driven irrigation systems for sustainable water management: A systematic review and meta-analytical insights. Smart Agricultural Technology, 11, 100982.
Ondrasek, Gabrijel. (2013). Water Scarcity and Water Stress in Agriculture. Physiological Mechanisms and Adaptation Strategies in Plants Under Changing Environment 75–96. https://doi.org/10.1007/978-1-4614-8591-9_4
Özel, B., Demir, Y., Başkan, O., & Alp, E. (2020). Evaluation of effectiveness of the water management strategies with the focus on agricultural water use: A case study on Upper-Sakarya River Basin in Turkey. https://doi.org/10.5194/egusphere-egu2020-16055 Padma, T., & Sinha, D. (2023). Crop yield prediction using improved random forest. ITM Web of Conferences, 56, 02007.
Pang, Y., Marinello, F., Tang, P., Li, H., & Liang, Q. (2023). Bibliometric Analysis of Trends in Smart Irrigation for Smart Agriculture. Sustainability, 15(23), 16420. https://doi.org/10.3390/su152316420
Patel, D. H., Shah, K. P., Gupta, R., Jadav, N. K., Tanwar, S., Neagu, B. C., Attila, S., Alqahtani, F., & Tolba, A. (2023). Blockchain-Based Crop Recommendation System for Precision Farming in IoT Environment. Agronomy, 13(10), 2642. https://doi.org/10.3390/agronomy13102642
Patil, B., & Asra, S. (2025). Smart IoT-Driven Precision Irrigation: Enhancing Water Efficiency with Machine Learning and Real-Time Environmental Monitoring. 2025 International Conference on Computing Technologies &Amp; Data Communication (ICCTDC), 1–8. https://doi.org/10.1109/icctdc64446.2025.11158868
Patle, G. T., & Sherpa, T. (2022). IoT Based Automated Irrigation Management Technique for Climate Smart Agriculture. Water Science and Technology Library, 305–324. https://doi.org/10.1007/978-3-031-13467-8_20
Payili, P. (2025). AI in agriculture: Smart greenhouses and indoor farming systems. International Journal of Science and Research Archive, 14(1), 315–322. https://doi.org/10.30574/ijsra.2025.14.1.0054 Pennsylvania State University Extension. (2026, February 13). Using drones in agriculture and natural resource management. https://extension.psu.edu/using-drones-in-agriculture-and-natural-resource-management
Pereira, G. P., Chaari, M. Z., & Daroge, F. (2023). IoT-Enabled Smart Drip Irrigation System Using ESP32. IoT, 4(3), 221–243. https://doi.org/10.3390/iot4030012
Pereira, L. S., Cordery, I., & Iacovides, I. (2012). Improved indicators of water use performance and productivity for sustainable water conservation and saving. Agricultural Water Management, 108, 39–51.
Piedelobo, L., Ortega-Terol, D., Del Pozo, S., Hernández-López, D., Ballesteros, R., Moreno, M. A., Molina, J.-L., & González-Aguilera, D. (2018). HidroMap: A New Tool for Irrigation Monitoring and Management Using Free Satellite Imagery. ISPRS International Journal of Geo-Information, 7(6), 220. https://doi.org/10.3390/ijgi7060220
Pôças, I., Calera, A., Campos, I., & Cunha, M. (2020). Remote sensing for estimating and mapping single and basal crop coefficientes: A review on spectral vegetation indices approaches. Agricultural Water Management, 233, 106081. https://doi.org/10.1016/j.agwat.2020.106081
Polwaththa, K., Amarasinghe, S., Amarasinghe, A., & Amarasinghe, A. (2024). Exploring artificial intelligence and machine learning in precision agriculture: A pathway to improved efficiency and economic outcomes in crop production. American Journal of Agricultural Science, Engineering, and Technology, 8(3), 50–59.
Prajapati, K. R. (2025). A Smart IOT-Driven Irrigation Solution for Efficient Water Use and Improved Crop Productivity in India. International Journal of Scientific Research in Engineering and Management, 9(4), 1–9. https://doi.org/10.55041/ijsrem46491
Praveen, P. (2025). AI in agriculture: Smart greenhouses and indoor farming systems. International Journal of Science and Research Archive, 14(1), 315–322. https://doi.org/10.30574/ijsra.2025.14.1.0054
Praveen, R., Mittal, M., Parida, P., Kumar, Y., Singla, A., & Thandra, N. (2025). Leveraging IoT and AI in Precision Agriculture for Efficient Water Management. 2025 International Conference on Computational, Communication and Information Technology (ICCCIT), 803–808. https://doi.org/10.1109/icccit62592.2025.10927765
Rabie, A. B., Elhag, M., & Subyani, A. (2025). Remote Sensing, GIS, and Machine Learning in Water Resources Management for Arid Agricultural Regions: A Review. Water, 17(21), 3125. https://doi.org/10.3390/w17213125
Rahman, F. (2025). AI in Agriculture: Advanced Smart Irrigation for Enhanced Crop Yields. SHS Web of Conferences, 216, 1065. https://doi.org/10.1051/shsconf/202521601065
Rahu, M., Shaikh, M., Karim, S., Ahmed, S., Hussain, D., & Shah, S. (2024). Water Quality Monitoring and Assessment for Efficient Water Resource Management through Internet of Things and Machine Learning Approaches for Agricultural Irrigation. Water Resources Management, 38, 4987–5028. https://doi.org/10.1007/s11269-024-03899-5
Ramadhan, A. J., Arun Kumar, B., Bala, I., Mijwil, M. M., Abotaleb, M., Alkattan, H., & Albadran, Z. (2024). IoT-Integrated Multi-Sensor Plant Monitoring and Automated Tank-Based Smart Home Gardening System. BIO Web of Conferences, 97, 154. https://doi.org/10.1051/bioconf/20249700154
Raspberry Pi Ltd. (2025). Raspberry Pi 4 Model B product brief. https://datasheets.raspberrypi.com/rpi4/raspberry-pi-4-product-brief.pdf
Rencai, L., He, C., Dening, Z., Zheng, W., Jiabing, C., Ran, Z., Lili, Z., & Yuling, J. (2023). Estimating Topsoil Water Content Using Crop Water Stress Index and Remote Sensing Technologies. Journal of Irrigation & Drainage, 42(4).
Saad, A., Benyamina, A. E. H., & Gamatie, A. (2020). Water Management in Agriculture: A Survey on Current Challenges and Technological Solutions. IEEE Access, 8, 38082–38097. https://doi.org/10.1109/access.2020.2974977
Saravanan, S., Jennifer, J. J., Abijith, D., & Singh, L. (2020). A GIS-based spatially distributed crop water demand modelling for Pullambadi canal command area in lower Cauvery basin, Tamil Nadu, India. Arabian Journal of Geosciences, 13(19). https://doi.org/10.1007/s12517-020-06014-1
Serret, M. D., Al-Dakheel, A. J., Yousfi, S., Fernáandez-Gallego, J. A., Elouafi, I. A., & Araus, J. L. (2020). Vegetation indices derived from digital images and stable carbon and nitrogen isotope signatures as indicators of date palm performance under salinity. Agricultural Water Management, 230, 105949. https://doi.org/10.1016/j.agwat.2019.105949
Sharma, V., Kaur, G., S., S., Chhabra, V., & Kashyap, R. (2025). Smart irrigation systems in agriculture: An overview. Computers and Electronics in Agriculture, 239, 111008. https://doi.org/10.1016/j.compag.2025.111008
Shirzadifar, A., Maharlooei, M., Bajwa, S. G., Oduor, P. G., & Nowatzki, J. F. (2020). Mapping crop stand count and planting uniformity using high resolution imagery in a maize crop. Biosystems Engineering, 200, 377–390. https://doi.org/10.1016/j.biosystemseng.2020.10.013
Sidik, A. R., Tawakal, A., Sumirat, G. S., & Narputro, P. (2025). Smart Irrigation Based on Soil Moisture Sensors with Photovoltaic Energy for Efficient Agricultural Water Management: A Systematic Literature Review. ETLTC 2025, 17. https://doi.org/10.3390/engproc2025107017
Singha, A., Gope, H. L., Islam, A. K. M., Billah, M. M., Hasan, M. M., & Barman, S. (2024). Integrating IoT-Based Smart Irrigation Systems to Optimize Crop Yield and Water Management for Sustainable Agriculture. Proceedings of the 3rd International Conference on Computing Advancements, 123–130. https://doi.org/10.1145/3723178.3723195
Somashekar, S., Moinuddin, Belagalla, N., Srinatha, T. N., Abhishek, G., Kumar, V., & Tiwari, A. (2024). Revolutionizing Agriculture: Innovative Techniques, Applications, and Future Prospects in Precision Farming. Journal of Scientific Research and Reports. 30(8). 405-19. https://10.9734/jsrr/2024/v30i82263
Somefun, O. T., Masasi, B., & Adelabu, A. O. (2024). Irrigation and Water Management of Tomatoes–A Review. Journal of Sustainable Agriculture and Environment, 3(4). https://doi.org/10.1002/sae2.70020 Souza, G., de Faria, B. T., Gomes Alves, R., Lima, F., Aquino, P. T., & Soininen, J.-P. (2020). Calibration equation and field test of a capacitive soil moisture sensor. 2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 180–184. https://doi.org/10.1109/metroagrifor50201.2020.9277634 Srinivasan, K., & Yadav, V. K. (2023). An empirical investigation of barriers to the adoption of smart technologies integrated urban agriculture systems. Journal of Decision Systems, 33(4), 878–912. https://doi.org/10.1080/12460125.2023.2189652
Swett, Cassandra L. 2020. “Managing Crop Diseases Under Water Scarcity.” Annual Review of Phytopathology 58(1):387–406. https://doi.org/10.1146/annurev-phyto-030320-041421
Syrový, T., Vik, R., Pretl, S., Syrová, L., Čengery, J., Hamáček, A., Kubáč, L., & Menšík, L. (2020). Fully Printed Disposable IoT Soil Moisture Sensors for Precision Agriculture. Chemosensors, 8(4), 125. https://doi.org/10.3390/chemosensors8040125
Talpur, Z., Zaidi, A. Z., Ahmed, S., Mengistu, T. D., Choi, S.-J., & Chung, I.-M. (2023). Estimation of Crop Water Productivity Using GIS and Remote Sensing Techniques. Sustainability, 15(14), 11154. https://doi.org/10.3390/su151411154
Tang, Y., Zhang, F., Engel, B. A., Liu, X., Yue, Q., & Guo, P. (2020). Grid-scale agricultural land and water management: A remote-sensing-based multiobjective approach. Journal of Cleaner Production, 265, 121792. https://doi.org/10.1016/j.jclepro.2020.121792
Tang, Z., Lu, J., Xiang, Y., Shi, H., Sun, T., Zhang, W., Wang, H., Zhang, X., Li, Z., & Zhang, F. (2024). Farmland mulching and optimized irrigation increase water productivity and seed yield by regulating functional parameters of soybean (Glycine max L.) leaves. Agricultural Water Management, 298. Scopus. https://doi.org/10.1016/j.agwat.2024.108875
Tarate, S. B., Patel, N. R., Danodia, A., Pokhariyal, S., & Parida, B. R. (2024). Geospatial Technology for Sustainable Agricultural Water Management in India—A Systematic Review. Geomatics, 4(2), 91–123. https://doi.org/10.3390/geomatics4020006
Thomas, R. J., O’Hare, G., & Coyle, D. (2023). Understanding technology acceptance in smart agriculture: A systematic review of empirical research in crop production. Technological Forecasting and Social Change, 189, 122374. https://doi.org/10.1016/j.techfore.2023.122374 Togneri, R., Prati, R., Nagano, H., & Kamienski, C. (2023). Data-driven water need estimation for IoT-based smart irrigation: A survey. Expert Systems with Applications, 225, 120194. https://doi.org/10.1016/j.eswa.2023.120194
Tong, X., Zhao, L., Heber, A. J., & Ni, J.-Q. (2020). Mechanistic modelling of ammonia emission from laying hen manure at laboratory scale. Biosystems Engineering, 192, 24–41. https://doi.org/10.1016/j.biosystemseng.2020.01.004
Toureiro, C., Serralheiro, R., Shahidian, S., & Sousa, A. (2017). Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition. Agricultural Water Management, 184, 211–220. https://doi.org/10.1016/j.agwat.2016.02.010
Tunca, E. (2024). Evaluating the performance of the TSEB model for sorghum evapotranspiration estimation using time series UAV imagery. Irrigation Science, 42(5), 977-994.
Tunca, E., Köksal, E. S., & Taner, S. Ç. (2022). Comparison of daily ET estimation using the METRIC model and Google Earth Engine. Uluslararası Tarım ve Yaban Hayatı Bilimleri Dergisi, 8(2), 256–267.
Ukani, N. A., Khera, S., & Chakole, S. S. (2025). IoT Integrated Graphene Derivative-Based Capacitive Sensors with Machine Learning Classification for Precision Soil Moisture Monitoring Process. EPJ Web of Conferences, 328, 1074. https://doi.org/10.1051/epjconf/202532801074
Ungureanu, N., Vlăduț, V., & Voicu, G. (2020). Water Scarcity and Wastewater Reuse in Crop Irrigation. Sustainability, 12(21), 9055. https://doi.org/10.3390/su12219055
Valiantzas, J. D. (2018). “Temperature-and Humidity-Based Simplified Penman’s ET0 Formulae. Comparisons with Temperature-Based Hargreaves-Samani and Other Methodologies.” Agricultural Water Management 208:326–34. https://doi.org/10.1016/j.agwat.2018.06.028
Venkateswaran, D., & Cho, Y. (2024). Efficient solar power generation forecasting for greenhouses: A hybrid deep learning approach. Alexandria Engineering Journal, 91, 222–236. https://doi.org/10.1016/j.aej.2024.02.004
Vogel, E., J. Lerat, R. Pipunic, A. J. Frost, C. Donnelly, M. Griffiths, D. Hudson, & S. Loh. (2021). Seasonal Ensemble Forecasts for Soil Moisture, Evapotranspiration and Runoff across Australia. Journal of Hydrology 601:126620. https://doi.org/10.1016/j.jhydrol.2021.126620
Wanyama, J., Bwambale, E., Kiraga, S., Katimbo, A., Nakawuka, P., Kabenge, I., & Oluk, I. (2024). A systematic review of fourth industrial revolution technologies in smart irrigation: Constraints, opportunities, and future prospects for sub-Saharan Africa. Smart Agricultural Technology, 7, 100412. https://doi.org/10.1016/j.atech.2024.100412
Wenting, H., Liyuan, Z., Yaxiao, N., & Xiang, S. (2020). Review on UAV Remote Sensing Application in Precision Irrigation. Nongye Jixie Xuebao/Transactions of the Chinese Society of Agricultural.
West, G., & Kovacs, K. (2017). Addressing Groundwater Declines with Precision Agriculture: An Economic Comparison of Monitoring Methods for Variable-Rate Irrigation. Water, 9(1), 28. https://doi.org/10.3390/w9010028
Wojtaszek, M. V., & Abdurahmanov, I. (2021). Crop Water Condition Mapping by Optical Remote Sensing. International Journal of Geoinformatics, 11–17. https://doi.org/10.52939/ijg.v17i1.1699
Xu, Z., Xiuzhi C., Susie R W., Mimi G., Yueyue D., Jinyan W., Yunkai L., and Jianguo L. (2019). Spatial-Temporal Assessment of Water Footprint, Water Scarcity and Crop Water Productivity in a Major Crop Production Region. Journal of Cleaner Production 224:375–83. https://doi.org/10.1016/j.jclepro.2019.03.108
Yıldırım, D., Cemek, B., & Küçüktopçu, E. (2019). Bulanık Yapay Sinir Ağları ve Çok Katmanlı Yapay Sinir Ağları ile Günlük Buharlaşma Tahmini. Toprak Su Dergisi Özel Sayı (24–31) https://doi.org/10.21657/topraksu.654778
Yildirim, D., Küçüktopcu, E., Cemek, B., & Simsek, H. (2023). Comparison of machine learning techniques and spatial distribution of daily reference evapotranspiration in Türkiye. Applied Water Science, 13(4), 107.
Younas, M., Nadeem Akhtar, M., Batool, S., Owais, M., Sahar, S., & Anum, W. (2025). The Integration of Artificial Intelligence in Agriculture: Emerging Trends, Benefits and Challenges. Journal of Asian Development Studies, 14(1), 1316–1333. https://doi.org/10.62345/jads.2025.14.1.105
Yousaf, W., Awan, W. K., Kamran, M., Ahmad, S. R., Bodla, H. U., Riaz, M., Umar, M., & Chohan, K. (2021). A paradigm of GIS and remote sensing for crop water deficit assessment in near real time to improve irrigation distribution plan. Agricultural Water Management, 243, 106443. https://doi.org/10.1016/j.agwat.2020.106443
Zhang, J. (2025). The Principles, Applications, and Development Trends of GIS and Remote Sensing Technology in Precision Agriculture. Theoretical and Natural Science, 117(1), 140–145. https://doi.org/10.54254/2753-8818/2025.ld25384
Zheng, B., Tian, S., Rao, C., Wang, Q., Liang, C., & Tan, B. (2023). Wireless Smart Greenhouse Management System Based on Multi-sensor of IoT. 2023 IEEE 3rd International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB), 95–99. https://doi.org/10.1109/iceib57887.2023.10170112
Zidan, F., & Febriyanti, D. E. (2024). Optimizing agricultural yields with artificial intelligence-based climate adaptation strategies. IAIC Transactions on Sustainable Digital Innovation (ITSDI), 5(2), 136–147.
Zondo, W. N. S., Ndoro, J. T., & Mlambo, V. (2024). The Adoption and Impact of Climate-Smart Water Management Technologies in Smallholder Farming Systems of Sub-Saharan Africa: A Systematic Literature Review. Water, 16(19), 2787. https://doi.org/10.3390/w16192787

Details

Primary Language

English

Subjects

Agricultural Engineering (Other)

Journal Section

Review

Authors

Shuaib Ajetunmobi Abdulrasaq ^*
Türkiye

Bilal Acar
0000-0003-2866-2543
Türkiye

Nadia Riaz
0000-0003-2224-1756
Türkiye

Publication Date

July 17, 2026

Submission Date

January 21, 2026

Acceptance Date

May 4, 2026

Published in Issue

Year 2026 Volume: 15 Number: 1

DOI

https://doi.org/10.21657/soilst.1996164

IZ

https://izlik.org/JA36UR54LL

Cite

RIS / Bibtex

APA

Abdulrasaq, S. A., Acar, B., & Riaz, N. (2026). Integrating innovative technologies for sustainable agricultural water management. Soil Studies, 15(1), 39-61. https://doi.org/10.21657/soilst.1996164

AMA

1.Abdulrasaq SA, Acar B, Riaz N. Integrating innovative technologies for sustainable agricultural water management. SoilSt. 2026;15(1):39-61. doi:10.21657/soilst.1996164

Chicago

Abdulrasaq, Shuaib Ajetunmobi, Bilal Acar, and Nadia Riaz. 2026. “Integrating Innovative Technologies for Sustainable Agricultural Water Management”. Soil Studies 15 (1): 39-61. https://doi.org/10.21657/soilst.1996164.

EndNote

Abdulrasaq SA, Acar B, Riaz N (July 1, 2026) Integrating innovative technologies for sustainable agricultural water management. Soil Studies 15 1 39–61.

IEEE

[1]S. A. Abdulrasaq, B. Acar, and N. Riaz, “Integrating innovative technologies for sustainable agricultural water management”, SoilSt, vol. 15, no. 1, pp. 39–61, July 2026, doi: 10.21657/soilst.1996164.

ISNAD

Abdulrasaq, Shuaib Ajetunmobi - Acar, Bilal - Riaz, Nadia. “Integrating Innovative Technologies for Sustainable Agricultural Water Management”. Soil Studies 15/1 (July 1, 2026): 39-61. https://doi.org/10.21657/soilst.1996164.

JAMA

1.Abdulrasaq SA, Acar B, Riaz N. Integrating innovative technologies for sustainable agricultural water management. SoilSt. 2026;15:39–61.

MLA

Abdulrasaq, Shuaib Ajetunmobi, et al. “Integrating Innovative Technologies for Sustainable Agricultural Water Management”. Soil Studies, vol. 15, no. 1, July 2026, pp. 39-61, doi:10.21657/soilst.1996164.

Vancouver

1.Shuaib Ajetunmobi Abdulrasaq, Bilal Acar, Nadia Riaz. Integrating innovative technologies for sustainable agricultural water management. SoilSt. 2026 Jul. 1;15(1):39-61. doi:10.21657/soilst.1996164