Abstract

Abstract An intelligent climate and watering agriculture system is presented that is controlled with Android application for smart water consumption considering small and medium ruler agricultural fields. Data privacy and security as a big challenge in current Internet of Things (IoT) applications, as with the increase in number of connecting devices, these devices are now more vulnerable to security threats. An intelligent fuzzy logic and blockchain technology is implemented for timely analysis and securing the network. The proposed design consists of various sensors that collect real-time data from environment and field such as temperature, soil moisture, light intensity, and humidity. The sensed field information is stored in IoT cloud platform, and after the analysis of entries, watering is scheduled by implementing the intelligent fuzzy logic and blockchain. The intelligent fuzzy logic based on different set of rules for making smart decisions to meet the watering requirements of plant and blockchain technology provides necessary security to the IoT-enabled system. The implementation of blockchain technology allows access only to the trusted devices and manages the network. From the experimentation, it is observed that the proposed system is highly scalable and secure. Multiple users at the same time can monitor and interact with the system remotely by using the proposed intelligent agricultural system. The decisions are taken by applying intelligent fuzzy logic based on input variables, and an alert is transmitted about watering requirements of a field to the user. The proposed system is capable of notifying users for turning water motor on and off. The experimental outcomes of the proposed system also reveal that it is an efficient and highly secure application, which is capable of handling the process of watering the plants.

Highlights

  • Due to the modernization of farming, the climate monitoring in agriculture is essential for the growth of agricultural yields

  • The collected data from a real-time environment are deposited in cloud database, but this data can only be retrieved through the web application. Their scheme is capable of providing the learning of water conservation to the users through computerization and building a bridge between the computer system and the proposed centric system based on soil moisture sensor measurement

  • The modern technologies should be utilized for increasing the efficiency and productivity of the agricultural products. This project is aimed to design an intelligent agricultural system, which is capable for monitoring the climate and other important parameters such as temperature, humidity, soil moisture, and light intensity for enhancing the health of plant and increasing the productivity

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Summary

Introduction

Due to the modernization of farming, the climate monitoring in agriculture is essential for the growth of agricultural yields. There is a requirement for an automatic and intelligent agricultural system that can be adopted for providing essential amount of water to the plants and climate monitoring during the maximum farming time. The irrigation of plants needs proper control on soil moisture level and monitoring of weather and watering quantity for its growth Many such technologies have been designed for providing better water utility during irrigation [3–6]. The prime focus of the proposed design is to present an automatic intelligent agricultural system that is capable of monitoring climate and providing an efficient utilization of water resources to feed plants during the maximum farming time [7]. The adopted blockchain technology enables the design by providing access only to the trusted devices and thereby controlling and managing the proposed intelligent climate and watering agriculture system (ICWAS).

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Architecture design of intelligent agriculture system
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Implementation of intelligent agriculture system
Process of intelligent agriculture system at server end
Analysis of intelligent agriculture system through mobile application
Experimental analysis and discussion
Humidity
Findings
Conclusion
Full Text
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