scholarly journals Recognition and Early Stage Detection of Phytophthora in a Crop Farm Using IoT

2021 ◽  
Author(s):  
Pooja Vajpayee ◽  
Kuldeep Kr. Yogi

Detection of agricultural plant pests is seen as one of the farmers’ problems. Automated Pest Detection Machine enables early detection of crop insects with advanced computer vision and image recognition. Innovative research in the field of agriculture has demonstrated a new direction by Internet of Things (IoT). IoT needs to be widely experienced at the early stage, so that it is widely used in different farming applications. It allows farmers increase their crop yield with reduced time and greater precision. For the past decade, climate change and precipitation have been unpredictable. Due to this, many Indian farmers are adopting smart methods for environment known as intelligent farming. Smart farming is an automated and IOT-based information technology (Internet of Things). In all wireless environments IOT is developing quickly and widely. The Internet of Things helps to monitor agricultural crops and thus quickly and effectively increase farmers’ income. This paper presents a literature review on IoT devices for recognizing and detecting insects in crop fields. Different types of framework/models are present which are explaining the procedure of insect detection.

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 61-63 ◽  
Author(s):  
Akihiro Fujii

The Internet of Things (IoT) is a term that describes a system of computing devices, digital machines, objects, animals or people that are interrelated. Each of the interrelated 'things' are given a unique identifier and the ability to transfer data over a network that does not require human-to-human or human-to-computer interaction. Examples of IoT in practice include a human with a heart monitor implant, an animal with a biochip transponder (an electronic device inserted under the skin that gives the animal a unique identification number) and a car that has built-in sensors which can alert the driver about any problems, such as when the type pressure is low. The concept of a network of devices was established as early as 1982, although the term 'Internet of Things' was almost certainly first coined by Kevin Ashton in 1999. Since then, IoT devices have become ubiquitous, certainly in some parts of the world. Although there have been significant developments in the technology associated with IoT, the concept is far from being fully realised. Indeed, the potential for the reach of IoT extends to areas which some would find surprising. Researchers at the Faculty of Science and Engineering, Hosei University in Japan, are exploring using IoT in the agricultural sector, with some specific work on the production of melons. For the advancement of IoT in agriculture, difficult and important issues are implementation of subtle activities into computers procedure. The researchers challenges are going on.


T-Comm ◽  
2020 ◽  
Vol 14 (12) ◽  
pp. 45-50
Author(s):  
Mikhail E. Sukhoparov ◽  
◽  
Ilya S. Lebedev ◽  

The development of IoT concept makes it necessary to search and improve models and methods for analyzing the state of remote autonomous devices. Due to the fact that some devices are located outside the controlled area, it becomes necessary to develop universal models and methods for identifying the state of low-power devices from a computational point of view, using complex approaches to analyzing data coming from various information channels. The article discusses an approach to identifying IoT devices state, based on parallel functioning classifiers that process time series received from elements in various states and modes of operation. The aim of the work is to develop an approach for identifying the state of IoT devices based on time series recorded during the execution of various processes. The proposed solution is based on methods of parallel classification and statistical analysis, requires an initial labeled sample. The use of several classifiers that give an answer "independently" from each other makes it possible to average the error by "collective" voting. The developed approach is tested on a sequence of classifying algorithms, to the input of which the time series obtained experimentally under various operating conditions were fed. Results are presented for a naive Bayesian classifier, decision trees, discriminant analysis, and the k nearest neighbors method. The use of a sequence of classification algorithms operating in parallel allows scaling by adding new classifiers without losing processing speed. The method makes it possible to identify the state of the Internet of Things device with relatively small requirements for computing resources, ease of implementation, and scalability by adding new classifying algorithms.


2018 ◽  
Author(s):  
Henry Tranter

Security is always at the forefront of developing technologies. One can seldom go a week without hearing of a new data breach or hacking attempt from various groups around the world, often taking advantage of a simple flaw in a system’s architecture. The Internet of Things (IoT) is one of these developing technologies which may be at risk of such attacks. IoT devices are becoming more and more prevalent in everyday life. From keeping track of an individual’s health, to suggesting meals from items available in an individual’s fridge, these technologies are taking a much larger role in the personal lives of their users. With this in mind, how is security being considered in the development of these technologies? Are these devices that monitor individual’s personal lives just additional vectors for potential data theft? Throughout this survey, various approaches to the development of security systems concerning IoT devices in the home will be discussed, compared, and contrasted in the hope of providing an ideal solution to the problems this technology may produce.


Author(s):  
Clinton Fernandes ◽  
Vijay Sivaraman

This article examines the implications of selected aspects of the Telecommunications (Interception and Access) Amendment (Data Retention) Act 2015, which was passed by the Australian Parliament in March 2015. It shows how the new law has strengthened protections for privacy. However, focusing on the investigatory implications, it shows how the law provides a tactical advantage to investigators who pursue whistleblowers and investigative journalists. The article exposes an apparent discrepancy in the way ‘journalist’ is defined across different pieces of legislation. It argues that although legislators’ interest has been overwhelmingly focused on communications data, the explosion of data generated by the so-called Internet-of-Things (IoT) is as important or more. It shows how the sensors in selected IoT devices lead to a loss of user control and will enable non-stop, involuntary and ubiquitous monitoring of individuals. It suggests that the law will need to be amended further once legislators and investigators’ knowledge of the potential of IoT increases. 


Author(s):  
Tanweer Alam

In next-generation computing, the role of cloud, internet and smart devices will be capacious. Nowadays we all are familiar with the word smart. This word is used a number of times in our daily life. The Internet of Things (IoT) will produce remarkable different kinds of information from different resources. It can store big data in the cloud. The fog computing acts as an interface between cloud and IoT. The extension of fog in this framework works on physical things under IoT. The IoT devices are called fog nodes, they can have accessed anywhere within the range of the network. The blockchain is a novel approach to record the transactions in a sequence securely. Developing a new blockchains based middleware framework in the architecture of the Internet of Things is one of the critical issues of wireless networking where resolving such an issue would result in constant growth in the use and popularity of IoT. The proposed research creates a framework for providing the middleware framework in the internet of smart devices network for the internet of things using blockchains technology. Our main contribution links a new study that integrates blockchains to the Internet of things and provides communication security to the internet of smart devices.


2018 ◽  
Author(s):  
Henry Tranter

Security is always at the forefront of developing technologies. One can seldom go a week without hearing of a new data breach or hacking attempt from various groups around the world, often taking advantage of a simple flaw in a system’s architecture. The Internet of Things (IoT) is one of these developing technologies which may be at risk of such attacks. IoT devices are becoming more and more prevalent in everyday life. From keeping track of an individual’s health, to suggesting meals from items available in an individual’s fridge, these technologies are taking a much larger role in the personal lives of their users. With this in mind, how is security being considered in the development of these technologies? Are these devices that monitor individual’s personal lives just additional vectors for potential data theft? Throughout this survey, various approaches to the development of security systems concerning IoT devices in the home will be discussed, compared, and contrasted in the hope of providing an ideal solution to the problems this technology may produce.


2021 ◽  
Vol 2089 (1) ◽  
pp. 012038
Author(s):  
V Dankan Gowda ◽  
M Sandeep Prabhu ◽  
M Ramesha ◽  
Jayashree M Kudari ◽  
Ansuman Samal

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.


Author(s):  
Sarita Tripathy ◽  
Shaswati Patra

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.


Author(s):  
Kundankumar Rameshwar Saraf ◽  
Malathi P. Jesudason

This chapter explores the encryption techniques used for the internet of things (IoT). The security algorithm used for IoT should follow many constraints of an embedded system. Hence, lightweight cryptography is an optimum security solution for IoT devices. This chapter mainly describes the need for security in IoT, the concept of lightweight cryptography, and various cryptographic algorithms along with their shortcomings given IoT. This chapter also describes the principle of operation of all the above algorithms along with their security analysis. Moreover, based on the algorithm size (i.e., the required number of gate equivalent, block size, key size, throughput, and execution speed of the algorithm), the chapter reports the comparative analysis of their performance. The chapter discusses the merits and demerits of these algorithms along with their use in the IoT system.


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