Abstract
The use of Internet of Things (IoT) for plant growth and environmental management is a promising new field of research. Here a network of seamlessly connected sensors is used to feed data aimed at providing healthier plant growth and a better environment. In this chapter, we present a system where eight types of sensors are used to measure the air and soil quality. Our design utilizes cloud storage for keeping the collected sensor data which then gets sorted online in order to create accurate forecasts on the environment and plants using an autoregressive integrated moving average algorithm. Additionally the system has been designed with web interface and data visualization, enabling people to obtain the real-time environmental information to take better decisions for plant growth and environmental management. Finally we highlight the accuracy of results of prediction data which is approximately 99.13%.
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References
Bach, F. R., & Jordan, M. I. (2004). Learning graphical models for stationary time series. IEEE Transactions on Signal Processing, 52(8), 2189–2199. https://doi.org/10.1109/TSP.2004.831032.
Bartholomew, D. J. (1971). Time series analysis forecasting and control. https://doi.org/10.1057/jors.1971.52.
Elsheikh, R., Rashid, A. B., Shariff, M., Amiri, F., Ahmad, N. B., Balasundram, S. K., & Soom, M. A. M. (2013). Agriculture land suitability evaluator (ALSE): A decision and planning support tool for tropical and subtropical crops. Computers and Electronics in Agriculture, 93(2015), 98–110.
Gotovtsev P. M., & Dyakov A. V. (2016). Biotechnology and internet of things for green smart city application. In Proceedings of the IEEE 3rd World Forum on Internet of Things (pp. 542–545).
Guest Writer. (2018). IoT applications in agriculture. Available at: https://www.iotforall.com/iot-applications-in-agriculture/. Accessed 3 Jan 2018.
Hyndman, R. J., & Khandakar, Y. (2008). Automatic time series forecasting: the forecast package for R. Journal of Statistical Software, 27(1), 1–22.
Ji, C., Lu, H., Ji, C., & Yan, J. (2015). An IoT and mobile cloud based architecture for smart planting. In 3rd International Conference on Machinery, Materials and Information Technology Applications, Atlantis Press.
Kamilaris, A., Andreas, K., & Boldú, F. X. P. (2017). A review on the practice of big data analysis in agriculture. Computers and Electronics in Agriculture, 143(2017), 23–37.
Kang, H., Lee, J., Hyochan, B., & Kang, S. (2012). A design of IoT based agricultural zone management system. Lecture Notes in Electrical Engineering (Vol. 180). Springer.
Karima, F., Karim, F., & Frihida, A. (2017, July). Monitoring system using web of things in precision agriculture. In The 12th International Conference on Future Networks and Communications (pp. 402–409). Leuven, Belgium: Elsevier.
Keerthi, V., & Kodandaramaiah, G. N. (2015). Cloud IoT based greenhouse monitoring system. International Journal of Engineering Research and Applications, 5, 35–41.
Mehrmolaei, S., & Keyvanpour, M. R. (2016). Time series forecasting using improved ARIMA. Artificial Intelligence and Robotics (Iranopen), Qazvin, 2016, 92–97. https://doi.org/10.1109/rios.2016.7529496.
Meonghun L., Jeonghwan H., & Hyun Y. (2013). Agricultural production systems based on IoT. In Proceedings of the IEEE 16th International Conference on Computational Science and Engineering (pp. 833–836).
Milman O (2015) Earth has lost a third of arable land in past 40 years, scientists say. Available at: https://www.theguardian.com/environment/2015/dec/02/arable-land-soil-food-security-shortage. Accessed 2 May 2018.
Mohanraj, I, Ashokumarb K, Naren J, (2016, September 6–8). Field monitoring and automation using IOT in agriculture domain. In 6th International Conference on Advances in Computing & Communications (pp. 931–941). Cochin, India: Elsevier.
Nadim, M., Rashed, M. R. H., Muhury, A., & Mominuzzaman, S. M. (2016). Estimation of optimum tilt angle for PV cell: a study in perspective of Bangladesh. In 9th International Conference on Electrical and Computer Engineering, IEEE.
Nau R. (2018). Statistical forecasting: Notes on regression and time series analysis. https://people.duke.edu/~rnau/411home.htm
Nukala, R., Panduru, K., & Shields, A. R. (2016, June 21–22). Internet of Things: A review from ‘Farm to Fork’. In International Conference on Future Internet of Things and Cloud, UK, IEEE.
Ojha, T., Misra, S., & Raghuwanshi, N. S. (2015). Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges. Computers and Electronics in Agriculture, 118, 66–84.
Paraforos, D. S., Vassiliadis, V., Kortenbruck, D., Stamkopoulos, K., Ziogas, V., Sapounas, A. X., & Griepentrog, H. W. (2016, August). A farm management information system using future internet technologies. In 5th IFAC Conference on Sensing, Control and Automation Technologies for Agriculture (pp. 324–329). USA: Elsevier.
Online 1, available: http://re.jrc.ec.europa.eu/pvgis/apps4/pvest.php?lang=en&map=Africa. Accessed 1 May 2018.
Online 2, available: http://www.pveducation.org/pvcdrom/properties-of-sunlight/calculation-of-solar-insolation. Accessed 1 May 2018.
Online 3, available: http://photovoltaic-software.com/PV-solar-energy-calculation.php. Accessed 1 May 2018.
Online 4, available: http://precisionagricultu.re/soil-temperature-and-its-importance/. Accessed 1 May 2018.
Online 5, available: http://www.jonathangreen.com/importance-soil-ph.html. Accessed 1 May 2018.
Online 6, available: soilquality.org.au/factsheets/soil-acidity (article 2016) (www.gardeningsingapore; article reprinted with permission from Agri-Food & Veterinary Authority).
Pitts L. (2016). https://observant.zendesk.com/hc/en-us/articles/208067926-Monitoring-Soil-Moisture-for-Optimal-Crop-Growth
Popović, T., Latinović, N., Pešić, A., Zečević, Z., Krstajić, B., & Djukanović, S. (2017). Architecting an IoT-enabled platform for precision agriculture and ecological monitoring: A case study. Computers and Electronics in Agriculture, 140, 255–265.
Rad, C.-R., Hancu, O., Takacs, L., & Olteanu, G. C. (2015, June 4–6). Smart monitoring of potato crop: A cyber-physical system architecture model in the field of precision agriculture. In International Conference “Agriculture for Life, Life for Agriculture” (pp. 73–79). Bucharest, Romania: Elsevier.
Sfetsos, T. (2000). A comparison of various forecasting techniques applied to mean hourly wind speed time series. Renewable Energy, 21(1), 23–35.
Shenoy, J., & Pingle, Y. (2016). IoT in agriculture. In Proceedings of the International Conference on Computing for Sustainable Global Development (pp. 1456–1458).
Talavera, J. M., Tobón, L. E., Gómez, J. A., Culman, M. A., Aranda, J. M., Parra, D. T., Quiroz, L. A., Hoyos, A., & Garreta, L. E. (2017). Review of IoT applications in agro-industrial and environmental fields. Computers and Electronics in Agriculture, 142, 283–297.
Tang Z, Almeida C, Fishwick PA (1991) Time series forecasting using neural networks vs. Box- Jenkins methodology, 57(5), pp. 303–310.
Thaker, T. (2016). ESP8266 based implementation of wireless sensor network with Linux based web-server. Symposium on Colossal Data Analysis and Networking (CDAN), Indore, 1–5. https://doi.org/10.1109/CDAN.2016.7570919.
Tilley, N. https://www.gardeningknowhow.com/garden-how-to/soil-fertilizers/determining-soil-temperature.htm. Accessed 4 May 2018.
Tran, N., & Reed, D. A. (2004). Automatic ARIMA time series modeling for adaptive I/O prefetching. IEEE Transactions on Parallel and Distributed Systems, 15(4), 362–377. https://doi.org/10.1109/tpds.2004.1271185.
Uddin, M. A., Mansour, A., Jeune, D. L., & Aggoune, H. M. (2017). Agriculture Internet of Things: AG-IOT. In 27th International Telecommunication Networks and Applications Conference, IEEE.
Vasisht, D., Kapetanovic, Z., Won, J., Jin, X., Chandra, R., Kapoor, A., Sinha, S. N., Sudarshan, M. & Stratman, S. (2017). FarmBeats: An IoT platform for data-driven agriculture. In 14th USENIX Symposium on Networked Systems Design and Implementation, USENIX Association.
Verdouw, C., Wolfert, S., & Tekinerdogan, B. (2016). Internet of Things in agriculture. CAB Reviews, 11, 1–12. https://doi.org/10.1079/PAVSNNR201611035.
Wang, Y., Song, J., Liu, X., Jiang, S., & Liu, Y. (2013). Plantation Monitoring System Based on Internet of Things. In IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, 366–369.
Zhou L, Song L, Xie C, Zhang J (2013) Applications of internet of things in the facility agriculture. IFIT advances in information and communication technology, 392, Springer.
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Kamruzzaman, S.M., Pavel, M.I., Hoque, M.A., Sabuj, S.R. (2019). Promoting Greenness with IoT-Based Plant Growth System. In: Anandakumar, H., Arulmurugan, R., Onn, C. (eds) Computational Intelligence and Sustainable Systems. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-02674-5_16
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