A Smart and Intelligent Irrigation System With a Roadmap Ahead

In India, agriculture is an important domain of research for food production. Insufficient, uncertain, and irregular rain causes problems in agriculture, and also, most of the annual rainfall occurs within less than 4 months, for which multiple cropping is not possible. Irrigation is a major influencing factor in agriculture as it solves all these problems. Irrigation helps in stabilising the output and yield levels. The sources of artificial irrigation are wells or canals or some reservoirs, and one also need extra labour to irrigate the fields. Automated and intelligent irrigation can solve many of these problems and reduce the human efforts. Moreover, it also improves the quality of the irrigation by reducing the dependency on the humans. It sends data wirelessly to a central server, which collects the data, stores it, and allow it to be analysed. The results and the collected data can be displayed and data sent to the phone whenever required. In this article, a description of such an intelligent and automated irrigation system is presented.

[1]  Nilanjan Dey,et al.  Modified cuckoo search algorithm in microscopic image segmentation of hippocampus , 2017, Microscopy research and technique.

[2]  M. Zwarteveen Water: From basic need to commodity: A discussion on gender and water rights in the context of irrigation , 1997 .

[3]  I. Yule,et al.  A method for spatial prediction of daily soil water status for precise irrigation scheduling , 2009 .

[4]  Minzan Li,et al.  Development of a smart mobile farming service system , 2011, Math. Comput. Model..

[5]  Kalyani Mali,et al.  Fuzzy Electromagnetism Optimization (FEMO) and its application in biomedical image segmentation , 2020, Applied Soft Computing.

[6]  Kalyani Mali,et al.  An Efficient Image Cryptographic Algorithm based on Frequency Domain using Haar Wavelet Transform , 2015 .

[7]  Garry L. Grabow,et al.  Water Application Efficiency and Adequacy of ET-Based and Soil Moisture–Based Irrigation Controllers for Turfgrass Irrigation , 2013 .

[8]  M. Dursun,et al.  A wireless application of drip irrigation automation supported by soil moisture sensors , 2011 .

[9]  Shouvik Chakraborty,et al.  An Efficient Approach to Job Shop Scheduling Problem using Simulated Annealing , 2015 .

[10]  Michael D. Dukes,et al.  Validation of Landscape Irrigation Reduction with Soil Moisture Sensor Irrigation Controllers , 2012 .

[11]  L. Stroosnijder,et al.  Assessing drought risk and irrigation need in northern Ethiopia , 2011 .

[12]  Kassaye Hussien,et al.  A GIS-Based Multi-Criteria Land Suitability Analysis for Surface Irrigation along the Erer Watershed, Eastern Hararghe Zone, Ethiopia , 2019 .

[13]  Scott B. Jones,et al.  Precise irrigation scheduling for turfgrass using a subsurface electromagnetic soil moisture sensor , 2006 .

[14]  P. Aryastana,et al.  Irrigation Water Management by Using Remote Sensing and GIS Technology to Maintain the Sustainability of Tourism Potential in Bali , 2020 .

[15]  M. Mancini,et al.  Smart irrigation forecast using satellite LANDSAT data and meteo-hydrological modeling , 2019, Agricultural Water Management.

[16]  Jan W. Hopmans,et al.  Frequency, electrical conductivity and temperature analysis of a low-cost capacitance soil moisture sensor , 2008 .

[17]  Wim G.M. Bastiaanssen,et al.  Irrigation Performance Indicators Based on Remotely Sensed Data: a Review of Literature , 1999 .

[18]  Michael D. Dukes,et al.  Precision of soil moisture sensor irrigation controllers under field conditions , 2010 .