scholarly journals An Implementation of IoT and Data Analytics in Smart Agricultural System – A Systematic Literature Review

2021 ◽  
pp. 41-70
Author(s):  
K. Vikranth ◽  
Krishna Prasad K.
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Data Analytics ◽  
Agricultural Land ◽  
Seed Quality ◽  
Farming System ◽  
The Internet ◽  
Smart Farming ◽  
Smart Agriculture ◽  
The Internet Of Things

India is a country that depends on agriculture, where about half the population relies heavily on agriculture for their livelihood. However, most of the practices undertaken in the agricultural process are not for profit and yield favorable. It should upgrade with current technologies to boost seed quality, check soil infertility, check the water level, environmental changes, and market price prediction, and achieve in agriculture sensitivity of faults and background understanding. The advancement in technology and developments is seen as a significant aspect in their financial development and agricultural production growth. The Internet of Things (IoT), Wireless Sensor Networks (WSN), and data analytics accomplish these upgrades. These technologies help in providing solutions to agricultural issues such as resource optimization, agricultural land monitoring, and decision-making support, awareness of the crop, land, weather, and market conditions for farmers. Smart agriculture is based on data from sensors, data from cloud platform storage and data from databases, all three concepts need to be implemented. The data are collected from different sensors and stored in a cloud-based back end support, which is then analyzed using proper analytics techniques, and then the relevant information is transferred to a user interface, which naturally supported the decision to conclude. The IoT applications mainly use sensors to monitor the situation, which collects a large size of data every time, so in the case of the Internet of Things (IoT) application, sensors contribute more. Data analytics requires data storage, data aggregation, data processing and data extraction. To retrieve data and information from database, we must use data mining techniques. It acts a significant position in the selection-making process on several agricultural issues. The eventual objective of data mining is to acquire information form data transform it for some advanced use into a unique human-comprehensible format. Big data's role in Agriculture affords prospect to increase the farmers' economic gain by undergoing a digital revolution in this aspect that we examine with precision. This paper includes reviewing a summary of some of the conference papers, journals, and books that have been going in favor of smart agriculture. The type of data required for smart farming system are analyzed and the architecture and schematic diagram of a proposed intelligent farming system are included. It also involves implementing different components of the smart farming system and integrating IoT and data analytics in the smart farming system. Based on the review, research gap, research agendas to carry out further research are identified.

scholarly journals A Study on the Necessity and Construction Plan of the Internet of Things Platform for Smart Agriculture

2014 ◽  
Vol 17 (11) ◽  
pp. 1313-1324 ◽  
Author(s):  
Joonyoung Lee ◽  
ShinHo Kim ◽  
SaeBom Lee ◽  
HyeonJin Choi ◽  
JaiJin Jung
Keyword(s):  
Internet Of Things ◽  
The Internet ◽  
Smart Agriculture ◽  
The Internet Of Things

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.

scholarly journals An Application of the Internet of Things on Sustainable Aquaculture System

2021 ◽  
Vol 16 (2) ◽  
pp. 061-065
Author(s):  
SANTHOSH K
Keyword(s):  
Internet Of Things ◽  
Fish Farming ◽  
Farming System ◽  
Food Sources ◽  
The Internet ◽  
Additional Energy ◽  
Living Space ◽  
Course Of Action ◽  
Calcium Iron ◽  
The Internet Of Things

Hydroponics is one of the human significant food sources. This paper proposed the model of the system, Feasible Fish-Farming System (SFFS), which can make the water cultivating framework more practical, employing applying the Internet of things (IoT) to lessen the need for energy for controlling the climate. Little freshwater fish species (SFFs) (length <25 cm) are exceptionally plentiful in nutrient A, calcium, iron and so on and consequently can add to social wellbeing through a supplement to country networks. Under the pressing factor of broad current rural practices and aimless collecting, loads of SFFs are step by step declining, and their environments and favourable places are likewise being crumbled at a quicker rate. A superior protectionist approach could be the carp-SFFS combination which will decrease aimless mass catch fishing of SFFs and will guarantee the preservation of normal SFFs stocks in their territories giving financial advantage to partners. Various investigations have effectively showed an example of overcoming adversity of SFF polyculture through carp—SFFs joining. This creation cum preservation practice prompts manageability—a superior term in the fishery is 'social fishery'. The part that needs consideration is the taking care of nature of SFFs to comprehend inside and between species (with carps) food apportioning and living space inclination as better culture cum conservational approach. Exploration in hydroponics is a contribution to increment settled creation. In the last decade, different researchers have supported attempts that came about in advancing current creation advances that have altered homestead creation. Fish developing is having the chance to be a champion among the most remunerating ambitious activities on account of the low advancement, insignificant exertion course of action-adventure and the 3 to half-year gathering cycles. IoT advancements have altered homestead creation in the country. In this paper, we propose an idea to distinguish far off observing the fish cultivating framework by utilizing the different sensors to diminish the dangers. In this paper, we utilize different sensors like pH worth, temperature and level sensors. By utilizing these sensors, all the work is mechanized, and it will likewise be not challenging to screen the fish cultivating distantly from other areas. The SFFS coordinates the sun-based homestead and fish-ranch to lessen the additional energy input. Furthermore, the lighting of LEDs is utilized to help the photosynthesis in the evening. This way is more energy-proficient than the customary siphoning. Besides, this model shows the subjective accessibility of SFFS.

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.

Big Data Analytics in Bioinformatics

Biotechnology ◽  
2019 ◽  
pp. 1967-1984
Author(s):  
Dharmendra Trikamlal Patel
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Annual Growth ◽  
Predictive Analysis ◽  
The Internet ◽  
Data Generation ◽  
Intelligent Devices ◽  
The Internet Of Things

Voluminous data are being generated by various means. The Internet of Things (IoT) has emerged recently to group all manmade artificial things around us. Due to intelligent devices, the annual growth of data generation has increased rapidly, and it is expected that by 2020, it will reach more than 40 trillion GB. Data generated through devices are in unstructured form. Traditional techniques of descriptive and predictive analysis are not enough for that. Big Data Analytics have emerged to perform descriptive and predictive analysis on such voluminous data. This chapter first deals with the introduction to Big Data Analytics. Big Data Analytics is very essential in Bioinformatics field as the size of human genome sometimes reaches 200 GB. The chapter next deals with different types of big data in Bioinformatics. The chapter describes several problems and challenges based on big data in Bioinformatics. Finally, the chapter deals with techniques of Big Data Analytics in the Bioinformatics field.

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