Precision Agriculture With Technologies for Smart Farming Towards Agriculture 5.0

2021 ◽  
pp. 247-276
Author(s):  
Dhirendra Siddharth ◽  
Dilip Kumar Saini ◽  
Ajay Kumar
Keyword(s):  
Precision Agriculture ◽  
Smart Farming

scholarly journals A Case Study about the Use of Precision Agriculture Technology Applied to a Zn Biofortification Workflow for Grapevine Vitis vinifera cv Moscatel

2021 ◽  
Vol 3 (1) ◽  
pp. 2
Author(s):  
Diana Daccak ◽  
Inês Carmo Luís ◽  
Ana Coelho Marques ◽  
Ana Rita F. Coelho ◽  
Cláudia Campos Pessoa ◽  
...  
Keyword(s):  
Vitis Vinifera ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Foliar Application ◽  
Fold Increase ◽  
Production Cycle ◽  
Smart Farming ◽  
Reduced Surface

As the human population is growing worldwide, the food demand is sharply increasing. Following this assumption, strategies to enhance the food production are being explored, namely, smart farming, for monitoring crops during the production cycle. In this study, a vineyard of Vitis vinifera cv. Moscatel located in Palmela (N 38°35′47.113′′ O 8°40′46.651) was submitted to a Zn biofortification workflow, through foliar application of zinc oxide (ZnO) or zinc sulfate (ZnSO4) (at a concentration of 60% and 90%—900 g·ha−1 and 1350 g·ha−1, respectively). The field morphology and vigor of the vineyard was performed through Unmanned Aerial Vehicles (UAVs) images (assessed with altimetric measurement sensors), synchronized by GPS. Drainage capacity and slopes showed one-third of the field with reduced surface drainage and a maximum variation of 0.80 m between the extremes (almost flat), respectively. The NDVI (Normalized Difference Vegetation Index) values reflected a greater vigor in treated grapes with treatment SZn90 showing a higher value. These data were interpolated with mineral content, monitored with atomic absorption analysis (showing a 1.3-fold increase for the biofortification index). It was concluded that the used technologies furnishes specific target information in real time about the crops production.

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 Sensor Applications in Agrifood Systems: Current Trends and Opportunities for Water Stewardship

Climate ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 44 ◽  
Author(s):  
Naoum Tsolakis ◽  
Eirini Aivazidou ◽  
Jagjit Singh Srai
Keyword(s):  
Precision Agriculture ◽  
Vital Role ◽  
Water Monitoring ◽  
Supply Networks ◽  
Factors Affecting ◽  
Sensor Applications ◽  
Smart Farming ◽  
Production Technologies ◽  
Food Commodities ◽  
Water Scarce

Growing global food demand and security concerns dictate the need for state-of-the-art food production technologies to increase farming efficiency. Concurrently, freshwater overexploitation in agriculture, especially in arid and water-scarce areas, emphasises the vital role of appropriate water-saving irrigations techniques to ensure natural resources sustainability in food supply networks. In line with the development of automated systems, the use of sensors for water monitoring, indicatively in the cases of smart farming or precision agriculture, could further promote the preservation of freshwater resources. To this end, this research first provides a review of sensor applications for improving sustainability in agrifood systems. We then focus on digital technologies applied for monitoring and assessing freshwater utilisation in the food commodities sector based on academic literature and real-world business evidence. A contextual map is developed for capturing the main technical, environmental and economic factors affecting the selection of sensors for water monitoring and stewardship during agricultural production. This first-effort framework, in terms of sensor-based freshwater monitoring, aims at supporting the agrifood system’s decision makers to identify the optimal sensor applications for improving sustainability and water efficiency in agricultural operations.

scholarly journals Enhancing Energy Saving in Smart Farming through Aggregation and Partition Aware IoT Routing Protocol

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2760 ◽  
Author(s):  
Karim Fathallah ◽  
Mohamed Abid ◽  
Nejib Ben Hadj-Alouane
Keyword(s):  
Low Power ◽  
Energy Saving ◽  
Routing Protocol ◽  
Precision Agriculture ◽  
Routing Algorithm ◽  
High Energy ◽  
Sensor Nodes ◽  
Personal Area Networks ◽  
Lossy Networks ◽  
Smart Farming

Internet of things (IoT) for precision agriculture or Smart Farming (SF) is an emerging area of application. It consists essentially of deploying wireless sensor networks (WSNs), composed of IP-enabled sensor nodes, in a partitioned farmland area. When the surface, diversity, and complexity of the farm increases, the number of sensing nodes increases, generating heavy exchange of data and messages, and thus leading to network congestion, radio interference, and high energy consumption. In this work, we propose a novel routing algorithm extending the well known IPv6 Routing Protocol for Low power and Lossy Networks (RPL), the standard routing protocol used for IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). It is referred to as the Partition Aware-RPL (PA-RPL) and improves the performance of the standard RPL. In contrast to RPL, the proposed technique builds a routing topology enabling efficient in-network data aggregation, hence dramatically reducing data traffic through the network. Performance analysis of a typical/realistic precision agriculture case, considering the potato pest prevention from the well-known late blight disease, shows that PA-RPL improves energy saving up to 40 % compared to standard RPL.

scholarly journals Challenges of UAVs Adoption for Agricultural Pesticide Spraying: A Social Cognitive Perspective

2020 ◽  
Author(s):  
Ting-Chu Hsieh ◽  
Ming-Chien Hung ◽  
Mai-Lun Chiu ◽  
Pay-Jiing Wu
Keyword(s):  
Precision Agriculture ◽  
Social Cognitive ◽  
Implementation Process ◽  
Technical Problems ◽  
Smart Farming ◽  
Scope Of Application ◽  
Software And Hardware ◽  
Production Output ◽  
Labor Requirements ◽  
Technological Frame

Unmanned aerial vehicles (UAVs) are one of the most promising innovative technologies invented in recent years to promote precision agriculture and smart farming. UAVs can not only reduce labor requirements but also increase production output, reduce the use of pesticides, and protect the environment. However, previous studies on agricultural UAVs have mostly focused on technical problems such as software and hardware design. Few studies have examined users’ behaviors in the implementation process. On the basis of Orlikowski and Gash’s technological frames, this study explored the participants’ cognition and expectation of farmers, pesticide, sprayers, and agriculture officials, who are three key groups of stakeholders involved in the application of UAVs to pesticide spraying, regarding agricultural UAVs and examined how the conflicts between their cognition and expectation influenced the choice of using pesticide spraying UAVs. The conclusions of this study contributed to supplement the content and broaden the scope of application of technological frame theory and provided a crucial reference for the promotion of agricultural UAVs in practice.

scholarly journals Integrated Smart Farming Based on Internet of Things (Iot) System for Figs Cultivation

2019 ◽  
Vol 9 (2) ◽  
pp. 1429-1436
Keyword(s):  
Internet Of Things ◽  
Precision Agriculture ◽  
Market Price ◽  
Farming System ◽  
Raspberry Pi ◽  
Entire System ◽  
Technology Deployment ◽  
Sensing Technology ◽  
Smart Farming ◽  
Value Changes

Fig plants are gaining popularity among farmers across Malaysia, mainly influenced by the high demands for fresh fig fruits and a fairly higher market price for the fruit. Current practices in farm fields are still based on observation and scheduling approach without any quantitative approaches which provide a precise way of determining the crucial elements such as irrigation and fertilization needs. This paper explains the design and development of smart farming system with sensing technology deployment for precision agriculture and the Internet of Things (IoT) approach to get farmers connected to their farm. Raspberry Pi 3 Model B acts as a brain of the entire system, delivering its functionality in performing monitoring and controlling tasks. Database is implemented by using ThingSpeak IoT cloud platform while for mobile application, this project is using Swift 4 programming language within Xcode IDE in implementing the iOS user interface features. The evaluation and validation result shows the microcontrollers and all embedded sensors associated to them are successfully executing their tasks in performing the surrounding humidity, irrigation and fertilization control duties. The developed system also capable in tracing the surrounding temperature and humidity, soil humidity and pH, and fertilizer EC value changes. Assistance in mobile device application implementation and ThingSpeak cloud database deployment in this project also get the farmers connected to their farm. Although this project has been completed successfully, however there are several areas which can be further improved in order to make the entire system more efficient and useful to the user.

scholarly journals A Review on Various Techniques to Transform Traditional Farming to Precision Agriculture

2021 ◽  
Vol 12 (2) ◽  
pp. 131-135
Author(s):  
Rana Gill
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Precision Agriculture ◽  
Wireless Sensors ◽  
Agricultural Sector ◽  
Wireless Sensor ◽  
Time Data ◽  
Traditional Farming ◽  
Agriculture Sector ◽  
Smart Farming

The agricultural sector is of great importance to fulfill food resources need of the country. Precision Agriculture (PA) with Internet of Things and Wireless Sensor Network is a transformation from traditional farming to smart farming. Wireless sensor networks and Internet of Things are considered as drivers to develop system which can change agriculture sector from manual to automatic. Advancement in the technology have pushed the growth of precision agriculture to very large extent despite of several challenges faced in this area. System for precision agriculture relies on hardware components mainly wireless sensors which act as a source for gathering of real time data. Depending upon the real time date retrieved by sensors automation in agriculture is done by adopting decision-based system. With Precision agriculture productivity is optimized by maintaining sustaniability as crop receives what is acutual requirement on the basis of new techniques and software platforms. This review article includes Inernet of Things (IoT), Wireless Sensors, Wireless communication and challenges faced in this area.

scholarly journals Agriculture in the Fourth Industrial Revolution

2019 ◽  
Vol 23 (2) ◽  
pp. 115-122
Author(s):  
T Ane ◽  
S Yasmin
Keyword(s):  
Artificial Intelligence ◽  
Precision Agriculture ◽  
Industrial Revolution ◽  
Insect Pests ◽  
Fourth Industrial Revolution ◽  
Level Data ◽  
Smart Farming ◽  
Real Time Information ◽  
Time Information ◽  
Crop Health

Agriculture and industry are tied up and both are complementary to each other. The fourth industrial revolution is an advanced digital technology, it focuses an opportunity that could change the environment in the way human think and work. The farms and factories must implement smart technology to move very fast and it should be an innovative applications to embrace the fourth industrial revolution robustly for Bangladesh. The fourth industrial revolution concept combines artificial intelligence and big data that have achieved significant attention and popularity in precision farming like in monitoring, diagnosing insect pests, measuring soil moisture, diagnosing harvest time and monitoring crop health status and reducing complicated monitoring by human. Industry that extend precision agriculture using artificial intelligence with robotic technology in fourth industrial revolution and its application is embedding into smart observation that retrieve real-time information from field level data with minor human interference. The fourth industrial revolution builds a smart farming technology which brings advanced and sustainable changes for both production and agroprocessing. The fourth industrial revolution extends farms production and also increase their value. This paper reviewed the past effects of industrial revolution, discussed expanded benefit into smart farming and predicted impacts of fourth industrial revolution in Bangladesh agriculture. Ann. Bangladesh Agric. (2019) 23(2) : 115-122

scholarly journals Precision Agriculture for Crop and Livestock Farming—Brief Review

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2345
Author(s):  
António Monteiro ◽  
Sérgio Santos ◽  
Pedro Gonçalves
Keyword(s):  
Animal Behavior ◽  
Precision Agriculture ◽  
Physical Environment ◽  
Negative Impact ◽  
Automatic Monitoring ◽  
Livestock Farming ◽  
Modern Agriculture ◽  
Smart Farming ◽  
Data Driven Approach ◽  
Animal Growth

In the last few decades, agriculture has played an important role in the worldwide economy. The need to produce more food for a rapidly growing population is creating pressure on crop and animal production and a negative impact to the environment. On the other hand, smart farming technologies are becoming increasingly common in modern agriculture to assist in optimizing agricultural and livestock production and minimizing the wastes and costs. Precision agriculture (PA) is a technology-enabled, data-driven approach to farming management that observes, measures, and analyzes the needs of individual fields and crops. Precision livestock farming (PLF), relying on the automatic monitoring of individual animals, is used for animal growth, milk production, and the detection of diseases as well as to monitor animal behavior and their physical environment, among others. This study aims to briefly review recent scientific and technological trends in PA and their application in crop and livestock farming, serving as a simple research guide for the researcher and farmer in the application of technology to agriculture. The development and operation of PA applications involve several steps and techniques that need to be investigated further to make the developed systems accurate and implementable in commercial environments.

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