INTERNET OF THINGS BASED SMART AGRICULTURE SYSTEM USING PREDICTIVE ANALYTICS

Due to the use of internet of things (IoT) devices, communication between different things is effective. The application of IoT in agriculture industryplays a key role to make functionalities easy. Using the concept of IoT and wireless sensor network (WSN), smart farming system has been developedin many areas of the world. Precision farming is one of the branches comes forward in this aspect. Many researchers have developed monitoring andautomation system for different functionalities of farming. Using WSN, data acquisition and transmission between IoT devices deployed in farms will be easy. In proposed technique, Kalman filter (KF) is used with prediction analysis to acquire quality data without any noise and to transmit this data for cluster-based WSNs. Due to the use of this approach, the quality of data used for analysis is improved as well as data transfer overhead is minimized in WSN application. Decision tree is used for decision making using prediction analytics for crop yield prediction, crop classification, soil classification, weather prediction, and crop disease prediction. IoT components, such as and cube (IOT Gateway) and Mobius (IOT Service platform), are integrated in proposed system to provide smart solution for crop growth monitoring to users.Â

HOMOGENEOUS MULTI-INTERFACE MOBILE NODE SUPPORT IN NS2

NS2 is a widely used, open source tool for network simulation. A Mobile Node (MN) in NS2 by default provides only a single Wi-Fi interface. It makes difficult for users to simulate the scenario where a mobile node is connected to multiple networks through different interfaces at the same time. Some projects have been done to implement multiple Wi-Fi interfaces but according to our view they have some limitations. This paper presents the implementation of mobile nodes in NS2 with multiple Wi-Fi interfaces and multiple WiMAX interfaces trying to overcome those limitations

Accuracy Optimization of Centrality Score Based Community Detection

Various concepts can be represented as a graph or the network. The network representation helps to characterize the varied relations between a set of objects by taking each object as a vertex and the interaction between them as an edge. Different systems can be modelled and analyzed in terms of graph theory. Community structure is a property that seems to be common to many networks. The division of the some objects into groups within which the connections or relations are dense, and the connections with other objects are sparser. Various research and data points proves that many real world networks has these communities or groups or the modules that are sub graphs with more edges connecting the vertices of the same group and comparatively fewer links joining the outside vertices. The groups or the communities exhibit the topological relations between the elements of the underlying system and the functional entities. The proposed approach is to exploit the global as well as local information about the network topologies. The authors propose a hybrid strategy to use the edge centrality property of the edges to find out the communities and use local moving heuristic to increase the modularity index of those communities. Such communities can be relevantly efficient and accurate to some applications. DOI: 10.17762/ijritcc2321-8169.15073

Automatic Classification of Medicinal Plants Using State-Of-The-Art Pre-Trained Neural Networks

Now a days every mankind is suffering due to infections. Ayurveda, the science of life helped to take preventive measures which boost our immunity.  It is plant-based science. Many medicinal plants found useful in daily life of common people for boosting immunity. Identifying the plant species having medicinal plant is challenging, it requires botanical expert. In the process of manual identification, botanical experts use various plant features as the identification keys, which are examined adaptively and progressively to identify plant species. The shortage of experts and trained taxonomist created global taxonomic impediment problem which is one of the major challenges.  Various researchers have worked in the field of automatic classification of plants since the last decade. The leaf is considered as primary input as it is available throughout the whole year. The research paper mainly focuses on the study of transfer learning approach for medicinal plant classification, which reuse already developed model at the starting point for model on a second task. Transfer learning approach is a black box approach used for image classification and many more applications by extracting features from an image. Some of the transfer learning models are MobileNet-V1, VGG-19, ResNet-50, VGG-16. Here it uses Mendeley dataset of Indian medicinal plant species which is freely available. Output layer classifies the species of leaves. The result provides evaluation and variations of above listed features extracted models. MobileNetV1 achieves maximum accuracy of 98%

Metal oxides and its blended derivative’s coating for anti-corrosion application

9-17Thin film deposition by using different nanomaterials has been an efficient and reliable way for enhancing the anti-corrosive property of the materials as well as strength improvement such as hardness, conductivity and wear resistance. Various materials have been taken as substrates like mild steel, magnesium, Aluminum, Copper, Tin, Carbon steel with thin film coatings of Zn–TiO2, Ce/Co, Zn-HA/TiO2, CrN/TiN, Ni- Co have been sampled. These specimens have been studied for numerous properties like surface roughness, wear resistance, adhesion strength, microhardness, hydrophobicity etc. It has been found that the components like muffler, differential, engine chassis, exhaust system, gears do undergo corrosion due to several factors like climate change, oxidation, moisture content etc. The aim of the review has been to highlight the advances in the coatings providing anticorrosive properties to various metallic substrates used specially for mechanical and automobile industries

POWER QUALITY IMPROVEMENT USING 5-LEVEL FLYING CAPACITOR MULTILEVEL CONVERTER BASED DYNAMIC VOLTAGE RESTORER FOR VARIOUS FAULTS

This paper present the use of five level flying capacitor multilevel converters based dynamic voltage restorer (DVR) on power distribution system to decrease the power-quality disturbances in distribution system, such as voltage imbalances, harmonic voltages, and voltage sags. This DVR based five multilevel topology is suitable for medium-voltage applications and operated by the control scheme based on the so called repetitive control. The organization of this paper has been divided into three parts; the first one eliminates the modulation high-frequency harmonics using filter increase the transient response

DIGITAL RIGHTS MANAGEMENTSOLUTIONS FOR ENTERPRIZES:AN OVERVIEW

In 21stcentury the digitalization of the processes and information has taken place very rapidly. Every organization in the competitive era has the confidential information and processes. The success of every organization is based on the security of such secret data and information.Confidential data, information, processes plays a vital role in development of the enterprise, in order to withstand in this market with a huge business competitors.Security of such information is really a challenge and many researchers have tried addressing this problem in last decade.Theft of such data may include the product development information, research data, business plans, financial details, list of the customers. It has been observedin the research that most of the times suchdata is stolen by insiders.Authors have tried to present the overview of various solutions proposed by researchers in past decade

Metal oxides and its blended derivative’s coating for anti-corrosion application

The prime objective of thin film formation on metallic substrate is to enhance the mechanical , structural ,tribological and electrical properties. Thin film deposition by using different nanomaterials is also an efficient and reliable way for enhancing the anti-corrosive property. As it is known that there are various factors which affect life and strength of mechanical parts. So thin film coatings can improve a material’s performance significantly in certain areas of corrosion control, and strength improvement for example hardness, conductivity, wear resistance etc. The various parts which are susceptible to corrosion and used in mechanical and automobile industries are firstly identified. It is found that the components like muffler, differential, engine chassis, exhaust system ,gears,etc.  which undergo corrosion due to  several  factors like climate change, oxidation, moisture content etc. To ameliorate anti corrosive property as well as other mechanical properties, it is necessary to obtain an optimum percentage of materials to be coated. The aim of the review is to highlight the advances in the coatings providing anticorrosive properties to various metallic substrates used specially for mechanical and automobile industries. Keywords-substrate, nanomaterials, muffler etc