IoT-based smart irrigation management system using real-time data

An adequate water supply is essential for the growth and development of crops. When rainfall is insufficient, irrigation is necessary to meet crop water needs. It is a crucial and strategic aspect of economic and social development. To combat climate change, there is a need to adopt irrigation management techniques that increase and stabilize agricultural production while saving water, using intelligent agricultural water technologies. Internet of things (IoT) based technologies can achieve optimal use of water resources. This article introduces a smart realtime irrigation management system based on the internet of things. It provides optimal management of irrigation decisions using real-time weather and soil moisture data, as well as data from precipitation forecasts. The proposed algorithm is developed in real-time based on the IoT, enabling us to guide irrigation and control the amount of water in agricultural applications. The system uses real-time data analysis of climate, soil, and crop data to provide flexible planning of the irrigation system’s use. A case study from the Fez-Meknes region in Morocco is presented to demonstrate the proposed system’s effectivenes

IMPLEMENTATION OF SMART IRRIGATION SYSTEM ON CARROT PLANTATION USING INTERNET OF THINGS

Agriculture is one of the main sectors in Karo Regency, North Sumatra. One of the commodities produced by farmers in Karo Regency is carrot. The inability of farmers to control soil moisture may cause crop damage to a lack of productivity. This research aims to create a monitoring & control system that is integrated with the website to make it easier for farmers to prevent problems that occur. The method used in the research is the design, installation, monitoring, and deactivation. The results obtained from this research are that farmers can now monitor the field conditions in real-time using a web-based monitoring & control system

Development of Artificial Intelligence Algorithm for Smart Irrigation Using Internet of Things (IoT)

Artificial Intelligence (AI) is the most recent agricultural technology. In agriculture, water is used to irrigate the plants so that they can flourish. Due to the scarcity of water in most parts of the world, the watering process is one of the most significant and crucial procedures. To address this issue, a smart irrigation system based on the Internet of Things (IoT) was developed utilizing AI technology, an Arduino Uno microcontroller, and sensors. The objective of this study is to develop a modified ANFIS (Adaptive Neuro-Fuzzy Inference System) AI algorithm for improved automated irrigation system decision control and to reduce the computing complexity of ANFIS architectural layers. It also seeks to develop an integrated system for monitoring and managing irrigation to increase agricultural output using MANFIS and the Internet of Things. Lastly, is to determine the difference of algorithmic complexity between the conventional ANFIS and Modified ANFIS. As a result, architectural layers were reduced into 3 layers, INPUT, PROCESS and OUTPUT. It also waters the plant automatically and sends signals regarding smart irrigation system information such as the tank's water level, the plant's soil moisture content, and the trigging factor, or the quantity of water to be released which enables the farmers to monitor and manage its irrigation system using the IoT. The simulations were carried out using MATLAB software, a fuzzy logic controller is used to control the whole system by providing its input, rules and output. To determine the computational complexity of each method, the ANFIS and modified ANFIS were examined with 100 % success rate

An Automated Irrigation System for Smart Agriculture Using the Internet of Things

Water is a valuable but limited agriculture resource, and it is becoming harder to manage it efficiently. This paper discusses a system of an automated irrigation that integrates the cloud computing, tools, and IoT (Internet of Things) for optimization in order to reduce water usage in the agriculture. Low-cost sensors have been utilized by the automated irrigation system to monitor important factors like soil type, pH, soil moisture, and meteorological conditions. For information storage & analysis, the data is kept in the Thing speak cloud service. The field data is sent to the cloud by utilizing the networks of GSM cellular as well as a Wi-Fi modem. Subsequently, using an optimization model, the ideal irrigation rate is determined. This rate would then be automated by utilizing a solenoid valve & regulated by an ARM controller (WEMOS D1). The essential variables are available to farmers as a cloud-based service. When the recommended approach is used in a pilot-scale agricultural operation, our findings show a decrease a water use, a rise in the amount of data available, and better imagining

MOBILE INTEGRATED SMART IRRIGATION SYSTEM USING IoT

Today’s world, the scarcity and usage of water is increasing day by day, it is very much important to conserve water for the future generation. The water requirement is very much needful for irrigation system and at a same time, proper management of water is also very much important with the available sources. Therefore a smart system is essential to manage the same. These papers present a smart system developed for irrigation system using IoT (internet of things). The main purpose of this system is to periodically monitor the soil’s moisture, humidity and temperature levels which are very much required for the crops, based on requirements, the water supply is pumped to the field and at the same time the farmer will receive the real time information to farmer's smart phone

Development of IoT Based Smart Irrigation System with Programmable Logic Controller

Smart irrigation system is an automatic irrigation and monitoring system on agricultural land with a sensor, automation, and control technology based on the Internet of Things (IoT). This system can reduce the agricultural activities that were previously performed manually into an automatic system with a reduced human supervision. Smart Irrigation systems that are widely developed used Arduino as the controller. Arduino still lacks in response, low durability, and sensitivity to temperature change, hence requiring frequent maintenance to avoid weather disturbances, insects, and others. This paper presents a development of a smart irrigation system using a Programmable Logic Controller (PLC) as the controller and a soil moisture sensor as a humidity condition measurement tool. The advantage of using PLC as a controller is more stable and has sensor compatibility with higher accuracy. Hence the results are more consistent and accurate. The PLC system is expandable, allowing for the inclusion of more channels for sensors and other measurement instruments. The developed system can collect data on soil moisture conditions, trigger valves, and perform auto irrigation using sprinklers, reducing or even eliminating the need for human intervention. The IoT collects data from sensors and updates the data into a database system, allowing users to monitor the land conditions in real-time. The developed system was predicted to save manpower (20%) and water usage (42.47%) compared to the conventional method. Keywords: Smart Irrigation; IoT; PLC; Moisture Sensor; Sprinkle

IOT Based Smart Farming Application

Smart agriculture is one of the Internet of Things' most important uses. Water, fertilizer, and crop yield waste are all reduced via smart agriculture. The manual detection of specifications like temperature, moisture, and humidity in the existing agricultural system drives up labor costs, and continuous monitoring is not possible. The irrigation procedure is carried out automatically in this study utilizing various sensors, which reduces manual work. It is suggested to utilize a sensor-based monitoring system for crop fields. It would entail gathering information on the soil moisture, humidity, and temperature. Automation of irrigation is possible by keeping an eye on all these variables. Unquestionably, smart farming is a key facilitator in providing more food with less resources for a growing global population. While this is essential to feeding the world's expanding population responsibly, smart farming also offers producers and communities throughout the world additional advantages. Farmers may raise yields and improve environmental management by using these strategies. By monitoring the field, IoT-based smart agriculture enhances the overall farming system. The Internet of Things in agriculture helps farmers save time and lessen the usage of resources like water thanks to sensors and connections. electricity, internet-connected temperature monitoring

A Smart Decision System for Digital Farming

[EN] New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management.This paper has been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR and by the "Ministerio de Ciencia, Innovacion y Universidades" through the "Ayudas para la adquisicion de equipamiento cientifico-tecnico, Subprograma estatal de infraestructuras de investigacion y equipamiento cientifico-tecnico (plan Estatal i+d+i 2017-2020)" (project EQC2018-004988-P).Cambra-Baseca, C.; Sendra, S.; Lloret, J.; Tomás Gironés, J. (2019). A Smart Decision System for Digital Farming. Agronomy. 9(5):1-19. https://doi.org/10.3390/agronomy9050216S11995Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787-2805. doi:10.1016/j.comnet.2010.05.010Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171-209. doi:10.1007/s11036-013-0489-0De Mauro, A., Greco, M., & Grimaldi, M. (2016). A formal definition of Big Data based on its essential features. Library Review, 65(3), 122-135. doi:10.1108/lr-06-2015-0061Haghverdi, A., Leib, B. G., Washington-Allen, R. A., Ayers, P. D., & Buschermohle, M. J. (2015). Perspectives on delineating management zones for variable rate irrigation. Computers and Electronics in Agriculture, 117, 154-167. doi:10.1016/j.compag.2015.06.019Vazquez, J. I., Ruiz-de-Garibay, J., Eguiluz, X., Doamo, I., Renteria, S., & Ayerbe, A. (2010). Communication architectures and experiences for web-connected physical Smart objects. 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). doi:10.1109/percomw.2010.5470521Misra, S., Barthwal, R., & Obaidat, M. S. (2012). Community detection in an integrated Internet of Things and social network architecture. 2012 IEEE Global Communications Conference (GLOBECOM). doi:10.1109/glocom.2012.6503350Atzori, L., Iera, A., & Morabito, G. (2014). From «smart objects» to «social objects»: The next evolutionary step of the internet of things. IEEE Communications Magazine, 52(1), 97-105. doi:10.1109/mcom.2014.6710070Agrivi App http://www.agrivi.com/en/reApollo Project http://apollo-h2020.eu/Cambra, C., Sendra, S., Lloret, J., & Lacuesta, R. (2018). Smart System for Bicarbonate Control in Irrigation for Hydroponic Precision Farming. Sensors, 18(5), 1333. doi:10.3390/s18051333Ortiz, A. M., Hussein, D., Park, S., Han, S. N., & Crespi, N. (2014). The Cluster Between Internet of Things and Social Networks: Review and Research Challenges. IEEE Internet of Things Journal, 1(3), 206-215. doi:10.1109/jiot.2014.2318835Ji, Z., Ganchev, I., O’Droma, M., Zhao, L., & Zhang, X. (2014). A Cloud-Based Car Parking Middleware for IoT-Based Smart Cities: Design and Implementation. Sensors, 14(12), 22372-22393. doi:10.3390/s141222372Ning, H., & Wang, Z. (2011). Future Internet of Things Architecture: Like Mankind Neural System or Social Organization Framework? IEEE Communications Letters, 15(4), 461-463. doi:10.1109/lcomm.2011.022411.11012

MONITOR CROP-FIELD BASED SMART IRRIGATION SYSTEM USING IOT

Internet of Things (IoT) is really a shared system of objects or things that can interact with each other offered the Internet link. IoT plays an role this is certainly important farming business which can give 9.6 billion individuals from the Earth by 2050. Smart Agriculture helps to lower wastage, efficient usage of fertilizer and thus boost the crop yield. Something is developed to monitor crop-field using detectors (earth dampness, heat, humidity, Float amount sensor) and automate the irrigation system in this work. The information from sensors are provided for Web host database utilizing transmission this is certainly wireless. The info tend to be encoded in JSON format in server database. On the basis of the water level within the land while raining the motor will ON/OFF be switched automatically

IoT based smart irrigation control and monitoring system

The "Internet of things" (IoT) has been rapidly developed and applied to the various sector including automotive, manufacture, industrial, and many more. IoT also refers to connecting to another device through a network without any interactions from the human. In this project, the idea is to design and develop an irrigation system that can be control and monitor by using a mobile phone. The purpose of this work is to help agriculture sector in maintaining the moisture of their plantation automatically. The design system should be able to monitor and controller the watering system automatically by detecting the level of moisture in the soil. At the end of the project, smart irrigation system, with an IoT functionality, is successfully designed and tested. Earlier testing provides some promising result, with system can be either automatically controlled or manually control, remotely using smartphone