A novel methodology for the development of an optimal agricultural crop field using Internet of Things

2020 ◽  
Author(s):  
Ramasamy Manikandan ◽  
Santhanam Prasanna ◽  
Muniyappan Ashwin ◽  
Lakshmanan Sathish Kumar ◽  
Sanjeevi Pandiyan
Keyword(s):  
Internet Of Things ◽  
Agricultural Crop ◽  
Crop Field

Internet of things‐based deeply proficient monitoring and protection system for crop field

2021 ◽  
Author(s):  
A. V. Prabu ◽  
G. Sateesh Kumar ◽  
Soundararajan Rajasoundaran ◽  
Prince Priya Malla ◽  
Sidheswar Routray ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Protection System ◽  
Crop Field

scholarly journals Internet of things survey on crop field smart irrigation automation using IOT

2018 ◽  
Vol 7 (2.8) ◽  
pp. 503
Author(s):  
T Pavan Kumar ◽  
Satyam Kumar Lala ◽  
Boppana Sravani ◽  
Andru Sandeep
Keyword(s):  
Soil Moisture ◽  
Internet Of Things ◽  
Light Intensity ◽  
Irrigation System ◽  
General Survey ◽  
Crop Fields ◽  
Soil Moisture Sensors ◽  
Crop Field ◽  
Common Goals ◽  
Entire Nation

This paper gives a general survey on Crop Field Smart Irrigation Mechanization utilizing web from claiming things. The paper covers details regarding the basics of Internet of Things and also the importance of Agriculture in a country like India. Internet of Things is fundamentally those intercontinental for everyone electronic units through Internet. By this interconnection the devices work in a synchronous way to achieve common goals. It is an evolving technology in the areas of trade, industry, medical and many applications. Many applications of IoT make use of sensors for detecting and activating gadgets helping in sharing of data. Agriculture is one such trade on which the entire nation is dependent. We in brief review the various techniques which will allow the farmers to grow more of their crops and reduce wastage of water by using sensors and automation of the irrigation system. The irrigation of crop fields depends on the data collected by the soil moisture sensors. The review can also be extended by understanding the way light intensity is controlled in greenhouses and also that the farmers can be able to monitor the field conditions from anywhere. This system is very useful in areas with scarcity of water. This sys is 92% more efficient than the conventional approach.

scholarly journals Smart System for Automated Irrigation Using Internet of Things Devices

2021 ◽  
pp. 1-10
Author(s):  
Rhuanito Soranz Ferrarezi ◽  
Tzu Wei Peng
Keyword(s):  
Internet Of Things ◽  
Precision Agriculture ◽  
Data Transfer ◽  
Low Cost ◽  
The Internet ◽  
Online Application ◽  
Crop Field ◽  
Set Up ◽  
The Right ◽  
Python Programming

Precision agriculture involves applying artificial intelligence, computers, sensors, and automation to improve crop field productivity while monitoring environmental conditions to conserve soil, water, and other natural resources focusing on agricultural sustainability. Despite many applications in agriculture, data monitoring and recording technologies have limited use due to the price. Low-cost open-source systems, like the ones available with the Internet of things (IoT) world, can potentially be developed as a universal-fit and cloud-connected technology for multiple applications. We designed and built a basic data collecting system using a commercial standalone embedded computer with Python programming language, serial data interface (SDI)-12/analog sensor adaptor, and digital sensors to monitor soil moisture and transmit the data remotely. SDI-12 is a standard communication protocol that transfers digital sensor measurements to a data recorder. We set up a pilot study that automatically collected and uploaded the data into the Internet to allow remote data transfer and access. The system performed reliably over 1 week with potting soil under field conditions without maintenance and successfully recorded data in real-time. The volumetric water content ranged from 0.03 to 0.23 m3·m−3, dielectric permittivity from 3.3 to 18.9 (unitless), EC from 0.0 to 0.3 dS·m−1, and soil temperature from 20.7 to 44.8 °C. All the data were successfully collected and uploaded to the cloud every 20 min, allowing users to remotely monitor the data using a free online application. However, heavy rainfall and high insolation could damage the system through excessive moisture or overheating, requiring a waterproof and heavy-duty protection case. The ThingSpeak channel allows customizing to suit a user’s specific requirements or adding more features for further development, such as automated irrigation, which can improve irrigation and fertilization efficiency by applying water and fertilizers at the right time based on sensor readings.

scholarly journals UAV Based Agricultural Crop Canopy Mapping for Crop Field Monitoring

2019 ◽  
Vol 1 ◽  
pp. 1-1
Author(s):  
Prabath Priyankara ◽  
Takehiro Morimoto
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Satellite Imagery ◽  
Field Monitoring ◽  
Decision Makers ◽  
Agricultural Crop ◽  
Crop Canopy ◽  
Crop Fields ◽  
Crop Field ◽  
Multi Temporal

<p><strong>Abstract.</strong> Nowadays, mapping of agricultural crop canopy in different growing stages are vital data for crop field monitoring than field-based observations in large scale agricultural crop fields. By mapping agricultural crop canopy, it is very easy to analyse the status of an agricultural crop field by using different vegetation indices. Further, the data can be used to estimate the yield. These information are timely and reliable spatial information to the farmers and decision makers. Mapping of crop canopy in an agricultural crop field in different growing stages are very challenging using satellite imagery mainly due to the difficulty of recording with high cloud coverage. Also, the cost for satellite imagery are higher in proportion to the spatial resolution. It takes some time to order a satellite imagery and sometimes can’t cover some growing stages. This problem can be solved by using low cost RGB based UAV imageries which can be operated at low altitudes (below the clouds) which and when necessary. This study is therefore aimed at mapping of a maize crop canopy using RGB based UAV imageries. UAV flights at different growth stages were carried out with a high resolution RGB camera over a maize field in Ampara District, Sri Lanka. For accurate crop canopy mapping, very high-resolution multi-temporal ortho-mosaicked images were derived from UAV imageries using free and open source image processing platforms with spatial resolution in centimetre level. The resultant multi-temporal ortho-mosaicked images can be used to map and monitor the crop field’s precise and efficient manner. These information are very important for farmers and decision makers to properly manage the crop fields.</p>

Carbon dioxide, water vapor, and heat fluxes over agricultural crop field in an arid oasis of Northwest China, as determined by eddy covariance

2010 ◽  
Vol 64 (3) ◽  
pp. 619-629 ◽  
Author(s):  
Xi Bin Ji ◽  
Wen Zhi Zhao ◽  
Er Si Kang ◽  
Zhi Hui Zhang ◽  
Bo Wen Jin
Keyword(s):  
Carbon Dioxide ◽  
Water Vapor ◽  
Eddy Covariance ◽  
Northwest China ◽  
Heat Fluxes ◽  
Agricultural Crop ◽  
Crop Field

A Study on Smart Irrigation System Using IoT for Surveillance of Crop-Field

2018 ◽  
Vol 7 (4.5) ◽  
pp. 370 ◽  
Author(s):  
Ashwini B V
Keyword(s):  
Decision Making ◽  
Soil Moisture ◽  
Internet Of Things ◽  
Food Production ◽  
Irrigation System ◽  
Soil Condition ◽  
Wireless Transmission ◽  
Sensor Reading ◽  
Crop Field ◽  
Evolution Of Technology

In India, agriculture plays an important role for development in food production. In our country, agriculture depends on the monsoons which are not sufficient source of water. So the irrigation is used in agriculture field. Internet of Things (IoT) is a milestone in the evolution of technology. IOT plays an important role in many fields, one of that is Agriculture by which it can feed billions of people on Earth in future. The objective of this paper is aiming to overcome this challenge, the whole system is micro control based and can be operated from remote location through wireless transmission so there is no need to concern about irrigation timing as per crop or soil condition. Sensor is used to take sensor reading of soil like soil moisture, temperature, air moisture and decision making is controlled by user (farmer) by using microcontroller. The data received from sensors are sent to server database using wireless transmission. The irrigation will be automated when the moisture and temperature of the field is reduced. The farmer is notified with the information regarding field condition through mobile periodically. This system will be more useful in areas where there is scarcity of water and will be worth efficient with satisfying its requirements.  

Smart Farm Monitoring Using Internet of Things and LoRa Technology Based on Wireless Sensor Networks

2020 ◽  
Vol 17 (9) ◽  
pp. 4136-4140
Author(s):  
G. P. Revathi ◽  
S. Supreetha
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Internet Of Things ◽  
New Technologies ◽  
Rapid Evolution ◽  
Wireless Sensor ◽  
User Friendliness ◽  
Transmission Distance ◽  
Crop Field ◽  
Smart Farming

In the recent years there has been rapid evolution in Smart farming and IOT. Farmers are interested in applying new technologies to their farm field to increase their crop yield, but only few farmers are able to apply this to their crop field due to many reasons like excessive cost, lack of user friendliness. Most wireless communication innovations have high utilization of power and cover small transmission distance and therefore do not satisfy the prerequisites required for applications on IoT’s for establishing networks. Consequently, LoRa technology has been proposed. LoRa™ is a low power wide area wireless network (LPWAN) protocol mainly used for applications based on Internet of Things (IoTs) technology. LPWAN ia a viable empowering innovation for largescale wireless sensor networks (WSNs). This paper proposes Monitoring of crop field and Automatic irrigation using LoRa technology.

scholarly journals A Mesh Sensor Network based on Bluetooh: Comparing Topologies to Crop Monitoring

2019 ◽  
Author(s):  
Luan Alves ◽  
Elida Antunes ◽  
Ricardo Ferreira ◽  
José Augusto Nacif
Keyword(s):  
Sensor Network ◽  
Mesh Network ◽  
Wireless Sensor ◽  
World Population ◽  
Agricultural Crop ◽  
Fluorescence Sensors ◽  
Crop Monitoring ◽  
Crop Field ◽  
The World ◽  
The Internet Of Things

The growth of the world population increases the demand for food and other products from agriculture. Therefore, it is increasingly needed to enhance and optimize the productivity of farms. Through using a Wireless Sensor Network (WSN) and the application of the internet of things (IoT) technologies, we can better monitor the condition of farm crops. In this work, we designed a Bluetooth Low Energy mesh network joined fluorescence sensors for agricultural crop monitoring, and also we evaluated the suitability of this solution in a crop field scenario.

scholarly journals Leaching Estimation for Paddy Crop using IoT and Machine Learning

2021 ◽  
Vol 9 (VI) ◽  
pp. 4419-4423
Author(s):  
Ch. Madhavi Sudha
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Root Zone ◽  
Salinity Level ◽  
Machine Learning Model ◽  
Crop Field ◽  
Field Temperature ◽  
Crop Growth Stage ◽  
Paddy Crop ◽  
Agricultural Organization

Soil salinity is a major issue in farming faced by many farmers across the globe. So it is very much important to identify the salinity level of the soil. Internet of Things (IoT) assisted solution is proposed to determine Electric Conductivity, temperature, and Moisture level at the root zone of the crop field. Internet of Things (IoT) and Machine Learning (ML), based leaching water requirements estimation for saline soils is made using the onsite monitoring of the salinity level and crop field temperature and crop growth stage. Food and Agricultural Organization (FAO) proposed method of leaching requirement is implemented for efficient leaching water estimation. These parameters are used to train and test the Machine learning model to predict the leaching requirement. The performance of machine learning is measured in terms of accuracy.

RFID Protocol Design, Optimization, and Security for the Internet of Things

2017 ◽  
Author(s):  
Alex X. Liu ◽  
Muhammad Shahzad ◽  
Xiulong Liu ◽  
Keqiu Li
Keyword(s):  
Internet Of Things ◽  
Design Optimization ◽  
Protocol Design ◽  
The Internet ◽  
The Internet Of Things ◽  
Rfid Protocol
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