scholarly journals A Low-Cost Platform for Environmental Smart Farming Monitoring System Based on IoT and UAVs

2021 ◽  
Vol 13 (11) ◽  
pp. 5908
Author(s):  
Faris A. Almalki ◽  
Ben Othman Soufiene ◽  
Saeed H. Alsamhi ◽  
Hedi Sakli
Keyword(s):  
Precision Agriculture ◽  
Low Cost ◽  
Environmental Parameters ◽  
Cost Effective ◽  
Crop Productivity ◽  
Environmental Data ◽  
Smart Farming ◽  
Smart Agriculture ◽  
Real Scenario ◽  
The Internet Of Things

When integrating the Internet of Things (IoT) with Unmanned Aerial Vehicles (UAVs) occurred, tens of applications including smart agriculture have emerged to offer innovative solutions to modernize the farming sector. This paper aims to present a low-cost platform for comprehensive environmental parameter monitoring using flying IoT. This platform is deployed and tested in a real scenario on a farm in Medenine, Tunisia, in the period of March 2020 to March 2021. The experimental work fulfills the requirements of automated and real-time monitoring of the environmental parameters using both under- and aboveground sensors. These IoT sensors are on a farm collecting vast amounts of environmental data, where it is sent to ground gateways every 1 h, after which the obtained data is collected and transmitted by a drone to the cloud for storage and analysis every 12 h. This low-cost platform can help farmers, governmental, or manufacturers to predict environmental data over the geographically large farm field, which leads to enhancement in crop productivity and farm management in a cost-effective, and timely manner. Obtained experimental results infer that automated and human-made sets of actions can be applied and/or suggested, due to the innovative integration between IoT sensors with the drone. These smart actions help in precision agriculture, which, in turn, intensely boost crop productivity, saving natural resources.

scholarly journals IoT Implementation and Management for Smart Farming

2019 ◽  
Vol 8 (10) ◽  
pp. 2483-2491
Keyword(s):  
Precision Agriculture ◽  
Rural Areas ◽  
Web Applications ◽  
Communication Technologies ◽  
Crop Productivity ◽  
Storage Solutions ◽  
Smart Farming ◽  
High Production ◽  
Architecture Frameworks ◽  
Smart Agriculture

Precision agriculture can enable the vision of smart agriculture, improves the crop productivity and increases profitability of yields. Utilization of water is also an important criterion for a good agriculture and high production. The new dimension of smart farming in agriculture is Internet of Things. The IoT is a best solution for smart agriculture due to the use of interoperable, pervasive, scalable and open technologies and gained momentum in the field of agriculture. The advanced growth in IoT technologies even made the dream come true with the connectivity reached to rural areas. The use of highly accurate IoT sensors can measure the environmental context of farms and helps in improving the accuracy of precision agriculture. This paper reviews the various applications of IoT motivated by a purpose to identify various areas with latest trends, architecture frameworks. Selected papers were clustered based on various domain and subdomains corresponding to the usage of sensors, actuators, communication technologies, energy controls, storage solutions, data analysis for decision making and visualization to the farmer through web applications.

scholarly journals A Survey on Smart Agricultural System Using LoRa Wireless Technology

2020 ◽  
Vol 6 (5) ◽  
pp. 13-18
Author(s):  
Parimal Solanki ◽  
Dr. Dipak M Patel ◽  
Dr. Darshak G Thakore
Keyword(s):  
Long Range ◽  
Precision Agriculture ◽  
Cost Effective ◽  
Great Distance ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Agricultural System ◽  
Wireless Protocols ◽  
Smart Farming ◽  
Smart Agriculture

Over the past few years, the designing in smart agriculture system is a very important concept. Using smart farming techniques we can build up the crop yield, and concurrently attain better output from the input. In precision agriculture, a wireless sensor network brings a cost-effective solution to watch and manipulate. We already have many wireless protocols like Wi-Fi, Cellular, BLE (Bluetooth low energy), etc. Although this automation, not optimal for cultivation sensor nodes, there is a demand to send information to a great distance without an internet connection. This leads to boost the LoRa (Long range) technology, which can do very long-range transmission with the lowest cost [14]. The paper provides a brief survey of certain requirements for Smart Agriculture such as wireless sensor networks.

scholarly journals An Agile AI and IoT-Augmented Smart Farming: A Cost-Effective Cognitive Weather Station

Agriculture ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 35
Author(s):  
Amine Faid ◽  
Mohamed Sadik ◽  
Essaid Sabir
Keyword(s):  
Internet Of Things ◽  
Human Life ◽  
Low Cost ◽  
Cost Effective ◽  
Base Station ◽  
Ease Of Use ◽  
Environmental Data ◽  
Radio Communication ◽  
Smart Farming ◽  
Set Up

Internet of Things (IoT) can be seen as the electricity of 21st century. It has been reshaping human life daily during the last decade, with various applications in several critical domains such as agriculture. Smart farming is a real-world application in which Internet of Things (IoT) technologies like agro-weather stations can have a direct impact on humans by enhancing crop quality, supporting sustainable agriculture, and eventually generating steady growth. Meanwhile, most agro-weather solutions are neither customized nor affordable for small farmers within developing countries. Furthermore, due to the outdoor challenges, it is often a challenge to develop and deploy low-cost yet robust systems. Robustness, which is determined by several factors, including energy consumption, portability, interoperability, and system’s ease of use. In this paper, we present an agile AI-Powered IoT-based low-cost platform for cognitive monitoring for smart farming. The hybrid Multi-Agent and the fully containerized system continuously surveys multiple agriculture parameters such as temperature, humidity, and pressure to provide end-users with real-time environmental data and AI-based forecasts. The surveyed data is ensured through several heterogeneous nodes deployed within the base station and in the open sensing area. The collected data is transmitted to the local server for pre-processing and the cloud server for backup. The system backbone communication is based on heterogeneous protocols such as MQTT, NRF24L01, and WiFi for radio communication. We also set up a user-friendly web-based graphical user interface (GUI) to support different user profiles. The overall platform design follows an agile approach to be easy to deploy, accessible to maintain, and continuously modernized.

A Self-Powered, Real-Time, NRF24L01 IoT Based-Cloud Enabled Service For Smart Agriculture Decision-Making System

2021 ◽  
Author(s):  
K. Lova Raju ◽  
V. Vijayaraghavan
Keyword(s):  
Precision Agriculture ◽  
Environmental Parameters ◽  
Field Evaluation ◽  
Low Noise ◽  
Heat Index ◽  
Low Noise Amplifiers ◽  
Agricultural Crop ◽  
Long Distance ◽  
Self Powered ◽  
Smart Agriculture

Abstract Internet of Things (IoT) based automation has provided sophisticated research and developments in the field of agriculture. In agriculture field production, using environmental and deployment sensors like DHT11, soil moisture, soil temperature, and so on, IoT has been utilised to monitor field conditions and automation in precision agriculture. The environmental parameters, field evaluation, deployment parameters, and shortage of water has become an unresolved task for agriculture monitoring. All of this leads to insufficient production of the agricultural crop. To eradicate the above-mentioned problems, we proposed a system in the using an architectural manner. This system uses an NRF24L01 module with in-built power and low noise amplifiers to enable a long-distance communication for transmission of the field information about the current crop situation to the farmers. This work is investigating an appropriate, reasonable, and applied IoT technology for precision agriculture by considering various applications of agriculture and experiments. The proposed system reduces power consumption, and improves operational efficiency. The proposed system reduces human efforts and also evaluates heat index measurement to monitor the environment. Based on the experiments, the current consumption and life expectancy of the AWMU are determined to be 0.02819 A and 3 days 20 hours 13 minutes and 47 seconds, respectively. Furthermore, the maximum transmission of AWMU is in an environmental location is 200 meters line of sight from the router.

scholarly journals DESIGN AND CONTROL OF SPIDER ROBOT MODEL

2019 ◽  
Vol 1 (1) ◽  
pp. 90-93
Author(s):  
Tan Thanh Nguyen ◽  
Duy Khanh Nguyen
Keyword(s):  
Operating System ◽  
High Stability ◽  
Low Cost ◽  
Environmental Parameters ◽  
Environmental Data ◽  
Control Methods ◽  
Multiple Control ◽  
Android Operating System ◽  
And Control ◽  
Mit App Inventor

Robots imitating spider’s moving have many advantages such as flexible movement, high stability, diversity in movements performed, especially in terrain  crossing, in military reconnaissance, in surveying and collecting environmental data in dangerous areas,.... In this article  with the main objective is to exploit multiple control methods to support applications of a spider robot with low-cost, a spider robot with 6 legs and 18 joints was designed. The ESPWROOM-32 module (ESP32-D0WDQ6 chip) and MIT App Inventor were used as the main tools for conducting this research. As a result, the robot is controlled via Bluetooth and Wifi to move, making some actions by self-written software running on the Android operating system. In addition, the robot has the capacity of self-propelled to avoid simple obstacles and send some environmental parameters to the software, including obstacles distance, humidity and temperature.

scholarly journals Smart Agriculture and Smart Farming using IoT Technology

2021 ◽  
Vol 2089 (1) ◽  
pp. 012038
Author(s):  
V Dankan Gowda ◽  
M Sandeep Prabhu ◽  
M Ramesha ◽  
Jayashree M Kudari ◽  
Ansuman Samal
Keyword(s):  
Internet Of Things ◽  
Treatment Optimization ◽  
Agricultural Producers ◽  
Support Tools ◽  
Smart Farming ◽  
Protection Systems ◽  
Smart Agriculture ◽  
Remote Monitoring Systems ◽  
Future Technologies ◽  
The Internet Of Things

Abstract It has become easier to access agriculture data in recent years as a result of a decline in digital breaches between agricultural producers and IoT technologies. These future technologies can be used to boost productivity by cultivating food more sustainably while also preserving the environment, thanks to improved water use and input and treatment optimization. The Internet of Things (IoT) enables the production of agricultural process-supporting systems. Referred to as remote monitoring systems, decision support tools, automated irrigation systems, frost protection systems, and fertilisation systems, respectively. Farmers and researchers must be provided with a detailed understanding of IoT applications in agriculture as a result of the knowledge described above. This study is about using Internet of Things (IoT) technologies and techniques to enhance agriculture. This article is meant to serve as an introduction to IoT-based applications in agriculture by identifying need for such tools and explaining how they support agriculture.

IoT-Based Precision Agriculture System

2020 ◽  
pp. 1-7
Author(s):  
Sarita Tripathy ◽  
Shaswati Patra
Keyword(s):  
Internet Of Things ◽  
Precision Agriculture ◽  
Modern Method ◽  
The Internet ◽  
Huge Number ◽  
Traditional Farming ◽  
Smart Farming ◽  
Different Types ◽  
Farm Vehicles ◽  
The Internet Of Things

The huge number of items associated with web is known as the internet of things. It is associated with worldwide data consisting of various components and different types of gadgets, sensors, and software, and a large variety of other instruments. A large number of applications that are required in the field of agriculture should implement methods that should be realistic and reliable. Precision agriculture practices in farming are more efficient than traditional farming techniques. Precision farming simultaneously analyzes data along with generating it by the use of sensors. The application areas include tracking of farm vehicles, monitoring of the livestock, observation of field, and monitoring of storage. This type of system is already being accepted and adopted in many countries. The modern method of smart farming has started utilizing the IoT for better and faster yield of crops. This chapter gives a review of the various IoT techniques used in smart farming.

scholarly journals Low-Cost LoRaWAN Node for Agro-Intelligence IoT

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 987 ◽  
Author(s):  
Antonio Valente ◽  
Sérgio Silva ◽  
Diogo Duarte ◽  
Filipe Cabral Pinto ◽  
Salviano Soares
Keyword(s):  
Low Cost ◽  
Environmental Parameters ◽  
Effective Control ◽  
Area Network ◽  
Wide Area Network ◽  
Lightning Strikes ◽  
Intelligent Sensors ◽  
Increase Productivity ◽  
Smart Agriculture ◽  
Water Tension

Intelligent agriculture in general, but especially when agricultural fields are very heterogeneous, requires a large number of sensors in order to obtain an effective control and thus increase productivity. This need becomes more evident in vineyards on the farms of the demarcated Douro region due to the specificities of the territory and the vineyards themselves. Thus, it is necessary to have low cost sensors which are, essentially, easy to install and maintain. In the present work, a node with these characteristics was developed, which, in addition, is low consumption and communicates wirelessly through a Long Rang Wide Area Network (LoRaWAN) network. To obtain an easy installation, a library of clusters was created for the LoRaWAN network and dedicated to sensors used in agriculture, especially those using an asynchronous serial protocol for intelligent sensors. Three nodes were developed and tested with sensors used in agriculture to measure several environmental parameters (soil and air temperature; wind speed, gust and direction; soil water content, water tension and electrical conductivity; solar radiation; precipitation; atmospheric and vapor pressure; relative humidity; and lightning strikes count). The three nodes send data to a server through an existing gateway on the farm. The data are decoded and sent to an Internet-of-Things analytics platform where it is aggregated, viewed and analyzed. Samples of the data collected are presented. The developed nodes are of small dimensions ( 85 × 65 × 35 m m ), thus making them easy to handle and install. Energy consumption depends on the distance to the gateway, and the number and type of sensors connected to each node. In the implemented cases, the maximum consumption was ≈ 400 μ A . The development of a cluster based library makes the node plug-and-play. The developed nodes will be a great step forward for the use of wireless sensors in smart agriculture in Douro vineyards.

scholarly journals A Survey on Intelligent Agricultural Information Handling Methodologies

2019 ◽  
Vol 11 (12) ◽  
pp. 3278 ◽  
Author(s):  
Yorghos Voutos ◽  
Phivos Mylonas ◽  
John Katheniotis ◽  
Anastasia Sofou
Keyword(s):  
Information Technologies ◽  
Production Systems ◽  
Low Cost ◽  
Small Scale ◽  
Research Knowledge ◽  
Current State ◽  
Smart Farming ◽  
Efficient Data ◽  
Art Research ◽  
The Internet Of Things

The term intelligent agriculture, or smart farming, typically involves the incorporation of computer science and information technologies into the traditional notion of farming. The latter utilizes plain machinery and equipment used for many decades and the only significant improvement made over the years has been the introduction of automation in the process. Still, at the beginning of the new century, there are ways and room for further vast improvements. More specifically, the low cost of rather advanced sensors and small-scale devices, now even connected to the Internet of Things (IoT), allowed them to be introduced in the process and used within agricultural production systems. New and emerging technologies and methodologies, like the utilization of cheap network storage, are expected to advance this development. In this sense, the main goals of this paper may be summarized as follows: (a) To identify, group, and acknowledge the current state-of-the-art research knowledge about intelligent agriculture approaches, (b) to categorize them according to meaningful data sources categories, and (c) to describe current efficient data processing and utilization aspects from the perspective of the main trends in the field.

scholarly journals A Smart, Sensible Agriculture System Using the Exponential Moving Average Model

Symmetry ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 457 ◽  
Author(s):  
Tai-hoon Kim ◽  
Virendra Singh Solanki ◽  
Hardik J. Baraiya ◽  
Anirban Mitra ◽  
Hirav Shah ◽  
...  
Keyword(s):  
Climatic Factors ◽  
Moving Average ◽  
Environmental Parameters ◽  
Cost Effective ◽  
Sensing Element ◽  
Agricultural Modernization ◽  
Modern Agriculture ◽  
Moving Average Model ◽  
Smart Agriculture ◽  
Using Data

Smart agriculture systems with combinations of advanced technologies are used in an attempt to increase the competence of certain farming activities and the standard of living for farm employees by reducing significant labor and tedious tasks. Internet-of-things-based sensors are capable of providing such information about smart agriculture and then acting upon predictions using data analysis. The proposed methodology works alongside a cloud-based server and a mobile-based device (ideally an Android/iOS device) to assist the user in regulating the standing of the plant as monitored by a mix of software packages and hardware devices. Our system detects changes in the moisture, temperature, and light intensity conditions in and around the plant and performs a learning-based call to supply necessary irrigation and illumination to plants. It permits the user to update, manage, and monitor using wireless sensing element networks. The sensors measure the aforementioned parameters and store the data within the cloud, which users can access at any time from anywhere. Farmers will have access to the most up-to-date knowledge so that they can act accordingly and make modifications as needed. This smart planting has become a core tool associated with cost-effective technology in agricultural modernization technologies. The proposed smart modern agriculture tool can be used to monitor climatic factors such as temperature, moisture, and virtually all environmental parameters relevant to the growth of plants.

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