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

Veerachamy, Ramachandran; Ramalakshmi, R.; Srinivasan, Seshadhri

doi:10.1109/icarcv.2018.8581221

Cited by 43 publications

(14 citation statements)

References 11 publications

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“…The collected data are used for analysis, and, depending on the obtained values, the system can automatically control the actuators (e.g., water pumps) as needed. Various autonomous irrigation systems [81][82][83][84][85] have been designed and implemented in the last decade, in order to optimise the irrigation process.…”

Section: Irrigation Systemsmentioning

confidence: 99%

Characterising the Agriculture 4.0 Landscape—Emerging Trends, Challenges and Opportunities

et al. 2021

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Investment in technological research is imperative to stimulate the development of sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and sensor networks, robotics, artificial intelligence, big data, cloud computing, etc. foster the transition towards the Agriculture 4.0 era. This fourth revolution is currently seen as a possible solution for improving agricultural growth, ensuring the future needs of the global population in a fair, resilient and sustainable way. In this context, this article aims at characterising the current Agriculture 4.0 landscape. Emerging trends were compiled using a semi-automated process by analysing relevant scientific publications published in the past ten years. Subsequently, a literature review focusing these trends was conducted, with a particular emphasis on their applications in real environments. From the results of the study, some challenges are discussed, as well as opportunities for future research. Finally, a high-level cloud-based IoT architecture is presented, serving as foundation for designing future smart agricultural systems. It is expected that this work will positively impact the research around Agriculture 4.0 systems, providing a clear characterisation of the concept along with guidelines to assist the actors in a successful transition towards the digitalisation of the sector.

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Section: Irrigation Systemsmentioning

confidence: 99%

Characterising the Agriculture 4.0 Landscape—Emerging Trends, Challenges and Opportunities

et al. 2021

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“…The WSN-based smart agriculture system was implemented by utilizing the Zigbee network and communicating the crops' status to farmers and a cloud server [17,18]. A Wi-Fi, GSM, and WEMOS D1 controller-based agriculture monitoring system has been implemented for monitoring the parameters of crops, such as pH, soil moisture, soil type, and weather conditions, and communicate these to a cloud server [19]. A low-cost information-based system was implemented for agriculture using 2G GSM and orang-pi [20].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

LoRa-LBO: An Experimental Analysis of LoRa Link Budget Optimization in Custom Build IoT Test Bed for Agriculture 4.0

et al. 2021

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The Internet of Things (IoT) is transforming all applications into real-time monitoring systems. Due to the advancement in sensor technology and communication protocols, the implementation of the IoT is occurring rapidly. In agriculture, the IoT is encouraging implementation of real-time monitoring of crop fields from any remote location. However, there are several agricultural challenges regarding low power use and long-range transmission for effective implementation of the IoT. These challenges are overcome by integrating a long-range (LoRa) communication modem with customized, low-power hardware for transmitting agricultural field data to a cloud server. In this study, we implemented a custom-based sensor node, gateway, and handheld device for real-time transmission of agricultural data to a cloud server. Moreover, we calibrated certain LoRa field parameters, such as link budget, spreading factor, and receiver sensitivity, to extract the correlation of these parameters on a custom-built LoRa testbed in MATLAB. An energy harvesting mechanism is also presented in this article for analyzing the lifetime of the sensor node. Furthermore, this article addresses the significance and distinct kinds of localization algorithms. Based on the MATLAB simulation, we conclude that hybrid range-based localization algorithms are more reliable and scalable for deployment in the agricultural field. Finally, a real-time experiment was conducted to analyze the performance of custom sensor nodes, gateway, and handheld devices.

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“…Mobile application based automatic accident prevention and detection system was designed [15] [16], the detection possibility of small accidents and support of the application from different mobile processors were major concerns to be addressed. A suitable cloud service is required to store the real-time data and Thingspeak an easily deployable open source service available with inbuilt lab view and MATLAB functions [18] is a right choice for swift deployment. Other than the existing research the traditional accident alert or avoidance, system includes the following.…”

Section: Existing Systemsmentioning

confidence: 99%

Accident Prevention and Traffic Pattern Analysis System for Hilly Regions

2019

IJITEE

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In hilly regions, there will be a number of curves and hairpin bends. The roadway is one of the often-used modes of transport in these regions. Accident rate and death rate in hilly regions are increasing day by day. The roads in this region will definitely have bends and steep curves; hence, it is difficult to see the vehicles coming from the opposite side. The proposed system aims in reducing the risk of driving vehicle in the terrain region with hairpin bends and steep curves. The deployed controller with ultrasonic sensor senses the vehicle coming towards the bend and intimates it to the other side of the bend or curve; it gives three stages of LED alerts to the driver driving the vehicle from the opposite side of the hairpin bend or curve. It also senses the speed of the vehicle, if the vehicle speed is high, it will alert the drivers through the buzzer. These alerts will indirectly convey the drivers to slow down the speed of the vehicle. The foremost focus of the proposed system is to prevent accidents for the drivers and passengers in order to decrease the death rates in hilly regions. This system also provides a way for analyzing the number of uphill and downhill vehicles in the hill stations by storing the data in the cloud. The analyzed data is be viewed over the internet through a web application. The web application serves as a traffic pattern analyzer for people who wish to travel by that road.

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

Cited by 43 publications

References 11 publications

Characterising the Agriculture 4.0 Landscape—Emerging Trends, Challenges and Opportunities

Characterising the Agriculture 4.0 Landscape—Emerging Trends, Challenges and Opportunities

LoRa-LBO: An Experimental Analysis of LoRa Link Budget Optimization in Custom Build IoT Test Bed for Agriculture 4.0

Accident Prevention and Traffic Pattern Analysis System for Hilly Regions

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