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Agricultural data analysis is an important challenge for the data mining community present not only in India but also in the world. This is due to the fact that majority of the cultivation lands in the globe suffer highly from shortage of irrigation water. In such a scenario, drip irrigation techniques have been developed by researchers to reduce the water consumption in dry areas. However, due to the lack of guidelines and systematic techniques to utilize the water and electricity in an optimistic manner, the agricultural sector faces water problem in many places. Therefore, the overheads of farmers using the conventional drip irrigation have become high, and they have to manually visit and monitor the lands frequently. Agricultural data can be collected more efficiently by the use of sensors for data collection and also for effective analysis. A smart irrigation system can be built with smart sensor networks for collecting field values and can be analyzed using rules for effectively watering the plants. Hence, a new sensor network-assisted irrigation system and rule-based analysis model have been developed in this research work to enhance the efficiency of water usage.

Water management for irrigation purposes is especially decisive in places prone to droughts because soil moisture sensors are economically unattainable for farmers. The sustainable usage of water should not be restricted by the elevated price of the system. In this paper, we present a low-cost sensor for the monitoring of soil moisture, which can be part of a smart irrigation system. The sensor is composed of two coils, one is powered with alternate current and the other one is used to measure the induced voltage. It is based on conductivity and uses the method of mutual inductance. We study five prototypes, which have different numbers of turns in each coil. We compare them in order to determine the best model. The best sensor is the one that consists of one coil with 40 turns (which is powered) and one with 100 turns (which is induced). The best frequency is 260 kHz, the coil is induced with 10 peak to peak voltage and the induced voltage, which is measured with an oscilloscope, changes with the soil moisture. At this frequency, the sensor presents the biggest difference in volts. The differences are 1.2 V between 0 and 6% of water volume in the soil; 0.8 between 6 and 8% water volume in the soil; and 1.6 V between 8 and 17% of water volume in soil. Considering these differences, we can safely formulate an equation to extract the soil moisture values with high accuracy.

From past decades, India is an agriculture-based country where the majority of the population is heavily dependent on farming. However, energy management and resource conservation continues to be the major issues in agricultural domain. The main motivations of this research is to conserve water which is a fast depleting source, and also automates the process of watering in order to reduce human workload in remote areas. In this paper, a smart irrigation alert system is developed using NodeMCU boards, a soil moisture sensor and a servo motor. The sensor measures the volumetric content of water in the soil and data is uploaded to the cloud. The main challenge addressed in this research is to seamlessly connect multiple Node MCUs to a sink (or, gateway) node such that the data can be uploaded to the cloud. Two topologies are considered. The first one is the star topology which is efficient for a kitchen garden where each of the plants is in close proximity of the sink. The second one is the multi-hop topology which is necessary in a big agriculture field. The soil moisture is sensed using multiple FC-28 sensors and uploaded to the cloud. When the moisture content drops below the threshold value, an alert notification is sent to the subscriber by e-mail and automatic watering follows by actuating the servo motor. The user can monitor and control the status of watering anywhere through the Internet. The integration of sensors, cloud and the servo motor through multiple Node MCUs is the main novelty of this work.

Living in a threat of global warming, the effort to make the world a little bit greener is what we all want. Automation of nursery system can make people more encouraged to contribute in making a greener earth. With the advancement of the technologies unmanned or less man controlled nursery system has become very popular. This paper presents an embedded secured smart nursery system that provides automated watering and drainage system, automated light control and supply system for photo-periodic plants and automated light system sensing the light intensity of garden. The design of this system was implemented in an academic environment using soil moisture sensor, LDR sensor and mobile application. The proposed system is easier to set up, cost-effective, fully automatic and has easy maintenance.

Watering to plants or on whole field of crop is most important and pain taking task on daily basis. Quantity of water required by plant is one of the effective parameter for greenhouse effect on plants. To make this challenging work to informal, some analytical and historical data is required so that irrigation cycle of crop may become easy task for farmers. This project is made with the use of Node MCU board; consist of ESP8266 Microcontroller with in-built Wi-Fi module. Soil Moisture sensor is set in the field, which keeps track of moisture level in field soil. That collected data are sent over cloud to make people’s nurturing activity pleased and tranquil. Data from the cloud is collected and irrigation related graph report for future use for farmer is made to take decision about which crop is to be sown. “Smart Irrigation Analysis” is an IoT application which provides remote analysis of irrigation on the field to the end user which is better than traditional irrigation of crop on field. Smart irrigation application has an automated recurring watering schedule; sensing and analysis of water used for crop and also senses moisture level giving real time data.

In this article, we show a prototype of an irrigation system for oil palm plantations in Colombia. We make use of a predictive control model to improve the irrigation schedule. This model takes weather predictions from the Internet and uses them in the control model as a new variable to take into account when it comes to deciding whether the crops should be irrigated or not. A soil moisture sensor is used to both validate if the decision was correct and maintain the crop within the desired range of soil moisture. With this work, we want to give farmers the opportunity to embrace the Internet of Things (IoT) as a technology that can make their job easier and with better productivity in their plantations. © 2017, Springer International Publishing AG. Department of Science, Information Technology and Innovation, Queensland Government Departamento Administrativo de Ciencia, Tecnología e Innovación, COLCIENCIAS: Colciencias Ministry of Information and Communications Technology, Iran FP44842-502-2015 Acknowledgment. The authors would like to acknowledge the cooperation of all partners within the Centro de Excelencia y Apropiación en Internet de las Cosas (CEA-IoT) project. The authors would also like to thank all the institutions that supported this work: the Colombian Ministry for the Information and Communications Technology (Ministerio de Tecnologías de la Información y las Comunicaciones - MinTIC) and the Colombian Administrative Department of Science, Technology and Innovation (Departamento Administrativo de Ciencia, Tecnología e Innovación - Colciencias) through the Fondo Nacional de Financiamiento para la Ciencia, la Tecnología y la Innovación Francisco Joséde Caldas (Project ID: FP44842-502-2015).

This chapter introduces an application of small satellite for environmental monitoring using real-time data that focuses on measured soil moisture and temperature using in situ sensor network. Soil Moisture Active Passive Mission (SMAP) uses microwave radar and radiometer to sense surface soil moisture condition but gives coarser result than the in situ data. To overcome the limitation of accuracy in SMAP mission, the proposed architecture will provide sensor data via a Ground Monitoring Wireless Sensor Network (GM-WSN) where data is collected by small satellite(s) operating in Lower Earth Orbit (LEO). The satellite will store the data until it passes over a ground station whereby it is communicated back to earth. The motivation for developing satellite accessible in situ measurements is to retrieve information from remote areas like Lake Tana in Ethiopia, where human accessibility is difficult. Hence, those important and unattended places would be covered by the proposed system. Another key attribute of this architecture is that it addresses four (climate, carbon, weather, and water) out of six NASA’s earth science strategic focus areas. The GM-WSN will consist of a sensor network that will measure soil moisture and temperature. The base station function is to fuse the data from the sensors, provide a time stamp, and format the data to be transmitted to satellite. It will also act as transceiver for ground to space communication using the amateur VHF/UHF radio band that has a maximum data rate of 9.6 kbps and will provide health maintenance and power management of network.