Abstract
Water management offers an effective solution to satisfy the world’s growing demand for water. Precision irrigation (PI), as an advanced concept in agriculture, has great promise to improve the efficiency of water use, as well as maintain or increase crop yield. PI involves different cutting-edge technologies such as the Internet of Thing (IoT), wireless sensor networks (WSN), and cloud computing. In this chapter, we present an overview of the PI concept and architecture including the most common wireless technologies used. Then, as a proof of concept, a real-time IoT-based smart irrigation system is designed. A number of wireless sensor nodes are deployed to monitor both soil moisture and temperature. Sensed data are transmitted to the gateway through the Queuing Telemetry Transport (MQTT) communication protocol. A Web interface and mobile application are provided to users to control the level of water in the soil in real time. Users can take immediate action to open or close the pump through the mobile application.
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References
Aggarwal, S. (2014). Flask framework cookbook. Birmingham: Packt Publishing Ltd.
Asghari, P., Rahmani, A. M., & Javadi, H. H. S. (2019). Internet of things applications: A systematic review. Computer Networks, 148, 241–261.
Barkunan, S., Bhanumathi, V., & Sethuram, J. (2019). Smart sensor for automatic drip irrigation system for paddy cultivation. Computers and Electrical Engineering, 73, 180–193.
Bayne, K., Damesin, S., & Evans, M. (2017). The internet of things—Wireless sensor networks and their application to forestry. New Zealand Journal of Forestry, 61(4), 37–41.
Bjarnason, J. (2017). Evaluation of Bluetooth low energy in agriculture environments. Bachelor Thesis, Malmö högskola University.
Chaudhry, S., & Garg, S. (2019). Smart irrigation techniques for water resource management. In Smart farming Technologies for Sustainable Agricultural Development (pp. 196–219). Hershey: IGI Global.
Chikankar, P. B., Mehetre, D., & Das, S. (2015). An automatic irrigation system using Zigbee in wireless sensor network. In 2015 International Conference on pervasive computing (ICPC), IEEE (pp. 1–5).
Dehury, C. K., & Sahoo, P. K. (2016). Design and implementation of a novel service management framework for IoT devices in cloud. Journal of Systems and Software, 119, 149–161.
Ds18b20 datasheet., https://datasheets.maximintegrated.com/en/ds/DS18B20.pdf, access (2019).
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.
Haque, M. S. T., Rouf, K. A., Khan, Z. A., Emran, A., & Zishan, M. S. R. (2019). Design and implementation of an IoT based automated agricultural monitoring and control system. In 2019 International Conference on robotics, electrical and signal processing techniques (ICREST) (pp. 13–16). Piscataway: IEEE.
Jawad, H. M., Nordin, R., Gharghan, S. K., Jawad, A. M., & Ismail, M. (2017). Energy-efficient wireless sensor networks for precision agriculture: A review. Sensors, 17(8), 1781.
Johnson, S. N., Hiltpold, I., & Turlings, T. C. (2013). Behaviour and physiology of root herbivores (Vol. 45). Oxford: Elsevier.
Kamienski, C., Soininen, J.-P., Taumberger, M., Fernandes, S., Toscano, A., Cinotti, T. S., Maia, R. F., & Neto, A. T. (2018). Swamp: An IoT-based smart water management platform for precision irrigation in agriculture. In 2018 Global Internet of Things Summit (GIoTS) (pp. 1–6). Piscataway: IEEE.
Kanoun, O., Keutel, T., Viehweger, C., Zhao, X., Bradai, S., Naifar, S., Trigona, C., Kallel, B., Chaour, I., Bouattour, G., et al. (2018). Next generation wireless energy aware sensors for internet of things: A review. In 2018 15th International Multi-Conference on systems, signals & devices (SSD) (pp. 1–6). Piscataway: IEEE.
Karayiannis C. (2019) The Lighttpd Web Server. In: Web-Based Projects that Rock the Class. Apress, Berkeley, CA.
Khelifa, B., Amel, D., Amel, B., Mohamed, C., & Tarek, B. (2015). Smart irrigation using internet of things. In 2015 Fourth International Conference on future generation communication technology (FGCT) (pp. 1–6). Piscataway: IEEE.
Khriji, S., Houssaini, D. E., Kammoun, I., & Kanoun, O. (2018a). Energy-efficient techniques in wireless sensor networks: Technology, components and system design. In Energy harvesting for wireless sensor networks (pp. 287–304). Berlin: DE GRUYTER. https://doi.org/10.1515/9783110445053-017.
Khriji, S., Cheour, R., Goetz, M., El Houssaini, D., Kammoun, I., & Kanoun, O. (2018b). Measuring energy consumption of a wireless sensor node during transmission: PanStamp. In 2018 IEEE 32nd International Conference on advanced information networking and applications (AINA) (pp. 274–280). Piscataway: IEEE.
Khriji, S., El Houssaini, D., Kammoun, I., Besbes, K., & Kanoun, O. (2019). Energy-efficient routing algorithm based on localization and clustering techniques for agricultural applications. IEEE Aerospace and Electronic Systems Magazine, 34(3), 56–66.
Larmo, A., Ratilainen, A., & Saarinen, J. (2019). Impact of CoAP and MQTT on NB-IoT system performance. Sensors, 19(1), 7.
Lawson, T., & Vialet-Chabrand, S. (2019). Speedy stomata, photosynthesis and plant water use efficiency. New Phytologist, 221(1), 93–98.
Liang, M.-H., He, Y.-F., Chen, L.-J., & Du, S.-F. (2018). Greenhouse environment dynamic monitoring system based on WIFI. IFAC-PapersOnLine, 51(17), 736–740.
Mbava, N., Mutema, M., Zengeni, R., Shimelis, H., & Chaplot, V. (2020). Factors affecting crop water use efficiency: A worldwide meta-analysis. Agricultural Water Management, 228, 105878.
Mehmood, R., Alam, F., Albogami, N. N., Katib, I., Albeshri, A., & Altowaijri, S. M. (2017). Utilearn: A personalised ubiquitous teaching and learning system for smart societies. IEEE Access, 5, 2615–2635.
Monica, M., Yeshika, B., Abhishek, G., Sanjay, H., & Dasiga, S. (2017). IoT based control and automation of smart irrigation system: An automated irrigation system using sensors, GSM, Bluetooth and cloud technology. In 2017 International Conference on recent innovations in signal processing and embedded systems (RISE) (pp. 601–607). Piscataway: IEEE.
Ni, J.-J., Cheng, Y.-F., Bordoloi, S., Bora, H., Wang, Q.-H., Ng, C.-W.-W., & Garg, A. (2019). Investigating plant root effects on soil electrical conductivity: An integrated field monitoring and statistical modelling approach. Earth Surface Processes and Landforms, 44(3), 825–839.
Pham, M. L., Nguyen, T. T., & Tran, M. D. (2019). A benchmarking tool for elastic MQTT brokers in IoT applications. International Journal of Information and Communication Sciences, 4(4), 70–78.
Reddy, A. S. (n.d.). Reaping the benefits of the internet of things. Cognizant Reports, May.
Sales, N., Remédios, O., & Arsenio, A. (2015). Wireless sensor and actuator system for smart irrigation on the cloud. In 2015 IEEE 2nd World Forum on internet of things (WF-IoT) (pp. 693–698). Piscataway, NJ: IEEE.
Santos, F., Abney, R., Barnes, M., Bogie, N., Ghezzehei, T. A., Jin, L., Moreland, K., Sulman, B. N., & Berhe, A. A. (2019). The role of the physical properties of soil in determining biogeochemical responses to soil warming. In Ecosystem consequences of soil warming (pp. 209–244). Elsevier.
Schlosser, C. A., Strzepek, K., Gao, X., Fant, C., Blanc, É., Paltsev, S., Jacoby, H., Reilly, J., & Gueneau, A. (2014). The future of global water stress: An integrated assessment. Earth’s Future, 2(8), 341–361.
Siping, H., Feng, W., Shejie, L. (2019). Design and optimization of Nginx sever based on LNMP. DEStech Transactions on Computer Science and Engineering (iccis).
Sparkfun soil moisture sensor., https://www.sparkfun.com/products/13637, access (2019).
Stergiou, C., Psannis, K. E., Kim, B.-G., & Gupta, B. (2018). Secure integration of IoT and cloud computing. Future Generation Computer Systems, 78, 964–975.
Taskın, D., Taskin, C., et al. (2018). Developing a Bluetooth low energy sensor node for greenhouse in precision agriculture as internet of things application. Advances in Science and Technology Research Journal, 12, 88–96.
Thakare, S., & Bhagat, P. (2018). Arduino-based smart irrigation using sensors and esp8266 WIFI module. In 2018 Second International Conference on intelligent computing and control systems (ICICCS) (pp. 1–5). Piscataway: IEEE.
Unninayar, S., & Olsen, L. (2008). Monitoring, observations, and remote sensing–global dimensions. In Encyclopedia of Ecology, Jørgensen, SE, Fath BD (eds.). Oxford: Academic Press (pp. 2425 – 2446). [Online]. Available: http://www.sciencedirect.com/science/article/pii/B9780080454054007497
Vaishali, S., Suraj, S., Vignesh, G., Dhivya, S., & Udhayakumar, S. (2017). Mobile integrated smart irrigation management and monitoring system using IoT. In 2017 International Conference on Communication and Signal Processing (ICCSP) (pp. 2164–2167). Piscataway: IEEE.
Yin, L., Wang, F., Han, S., Li, Y., Sun, H., Lu, Q., Yang, C., & Wang, Q. (2016). Application of drive circuit based on l298n in direct current motor speed control system. In Advanced laser manufacturing technology (Vol. 10153, p. 101530N). International Society for Optics and Photonics.
Zhou, Y., Yang, X., Guo, X., Zhou, M., & Wang, L. (2007). A design of greenhouse monitoring & control system based on Zigbee wireless sensor network. In 2007 International Conference on wireless communications, networking and Mobile computing (pp. 2563–2567). Piscataway: IEEE.
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Khriji, S., El Houssaini, D., Kammoun, I., Kanoun, O. (2021). Precision Irrigation: An IoT-Enabled Wireless Sensor Network for Smart Irrigation Systems. In: Hamrita, T. (eds) Women in Precision Agriculture. Women in Engineering and Science. Springer, Cham. https://doi.org/10.1007/978-3-030-49244-1_6
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