scholarly journals Ayurvedic Plant Identification using Image Processing and Artificial Intelligence

2021 ◽  
pp. 212-218
Author(s):  
Amey Sunil Deshmukh ◽  
Pushppavisha Mani Mudhaliar ◽  
Dr. Surabhi Thorat
Keyword(s):  
Sensor Networks ◽  
Wireless Networking ◽  
Home Automation ◽  
Plant Identification ◽  
Coverage Area ◽  
Bee Colony ◽  
Implementation Techniques ◽  
Military Applications ◽  
A New Technique ◽  
Architectural Survey

Wireless networks provide small sensing, machine and wireless networking nodes. Different designs and implementation techniques were built based on the device requirements for wireless network sensors (WSN). Sensor networks are used in various applications, such as environmental monitoring, home automation, military applications, etc. In this study introduce an architectural survey and deployment of nodes in the Wi-Fi Sensor network in this article. The environmental features that can be added to the sensor networks are given. The program relies on the node installed in the WSN and is deterministic or random. But the biggest issue in both cases is the coverage of the region involved. Researcher also describe WSN routing protocols. In this paper, a new technique to deployment problem is proposed based on the artificial bee colony (ABC) algorithm which is enhanced for the deployment of sensor networks to gain better performance by trying to increase the coverage area of the network and energy consumption. The good performance of the proposed EABC algorithm shows that it can be utilized in the deployment of WSN.

scholarly journals Enhanced Artificial Bee Colony method for node deployment and routing in Wireless Sensor Networks

2021 ◽  
pp. 28-37
Author(s):  
Basavaraj Madagouda ◽  
R. Sumathi
Keyword(s):  
Sensor Networks ◽  
Artificial Bee Colony ◽  
Wireless Networking ◽  
Home Automation ◽  
Coverage Area ◽  
Bee Colony ◽  
Implementation Techniques ◽  
Military Applications ◽  
A New Technique ◽  
Architectural Survey

Wireless networks provide small sensing, machine and wireless networking nodes. Different designs and implementation techniques were built based on the device requirements for wireless network sensors (WSN). Sensor networks are used in various applications, such as environmental monitoring, home automation, military applications, etc. In this study introduce an architectural survey and deployment of nodes in the Wi-Fi Sensor network in this article. The environmental features that can be added to the sensor networks are given. The program relies on the node installed in the WSN and is deterministic or random. But the biggest issue in both cases is the coverage of the region involved. Researcher also describe WSN routing protocols. In this paper, a new technique to deployment problem is proposed based on the artificial bee colony (ABC) algorithm which is enhanced for the deployment of sensor networks to gain better performance by trying to increase the coverage area of the network and energy consumption. The good performance of the proposed EABC algorithm shows that it can be utilized in the deployment of WSN.

Deterministic Deployment for Wireless Image Sensor Nodes

2014 ◽  
Vol 8 (1) ◽  
pp. 668-674
Author(s):  
Junguo Zhang ◽  
Yutong Lei ◽  
Fantao Lin ◽  
Chen Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Visual Information ◽  
Image Sensor ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Effective Coverage ◽  
Area Of Interest ◽  
Key Issues

Wireless sensor networks composed of camera enabled source nodes can provide visual information of an area of interest, potentially enriching monitoring applications. The node deployment is one of the key issues in the application of wireless sensor networks. In this paper, we take the effective coverage and connectivity as the evaluation indices to analyze the effect of the perceivable angle and the ratio of communication radius and sensing radius for the deterministic circular deployment. Experimental results demonstrate that the effective coverage area of the triangle deployment is the largest when using the same number of nodes. When the nodes are deployed in the same monitoring area in the premise of ensuring connectivity, rhombus deployment is optimal when √2 < rc / rs < √3 . The research results of this paper provide an important reference for the deployment of the image sensor networks with the given parameters.

scholarly journals Strengthening the PSO algorithm with a new technique inspired by the golf game and solving the complex engineering problem

2021 ◽  
Author(s):  
Serkan Dereli ◽  
Raşit Köker
Keyword(s):  
Pso Algorithm ◽  
Engineering Problem ◽  
Golf Ball ◽  
New Technique ◽  
Successful Implementation ◽  
Robot Arm ◽  
Bee Colony ◽  
Scientific World ◽  
Heuristic Technique ◽  
A New Technique

AbstractThis study has been inspired by golf ball movements during the game to improve particle swarm optimization. Because, all movements from the first to the last move of the golf ball are the moves made by the player to win the game. Winning this game is also a result of successful implementation of the desired moves. Therefore, the movements of the golf ball are also an optimization, and this has a meaning in the scientific world. In this sense, the movements of the particles in the PSO algorithm have been associated with the movements of the golf ball in the game. Thus, the velocities of the particles have converted to parabolically descending structure as they approach the target. Based on this feature, this meta-heuristic technique is called RDV (random descending velocity) IW PSO. In this way, the result obtained is improved thousands of times with very small movements. For the application of the proposed new technique, the inverse kinematics calculation of the 7-joint robot arm has been performed and the obtained results have been compared with the traditional PSO, some IW techniques, artificial bee colony, firefly algorithm and quantum PSO.

An Outline of Threats and Sensor Cloud Infrastructure in Wireless Sensor Network

2015 ◽  
pp. 412-432
Author(s):  
Bhavana Butani ◽  
Piyush Kumar Shukla ◽  
Sanjay Silakari
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Cloud Infrastructure ◽  
Node Capture Attack ◽  
Node Capture ◽  
Sensor Cloud ◽  
A New Technique ◽  
Commercial Applications

Wireless sensor networks are utilized in vital situations like military and commercial applications, traffic surveillance, habitat monitoring, and many other applications. WSNs have to face various issues and challenges in terms of memory, communication, energy, computation, and storage, which require efficient management of huge amount of sensor data. Therefore, storage is an important issue in the WSN. Emergence of Sensor-Cloud infrastructure overcomes several shortcomings of WSN such as storage capacity and offers high processing capabilities for huge sensor data. Security is also the major challenge that is faced by the sensor network. This chapter includes a brief overview of the importance of cloud computing in sensor networks and the goal of DDoS and Node Capture Attack in WSN. This chapter includes descriptions of different modeling techniques of Node Capture attack and various detection and key pre-distribution schemes to invent a new technique to improve network resilience against node capture attacks.

Deep Reinforcement Learning Methods for Energy-Efficient Underwater Wireless Networking

2021 ◽  
pp. 212-223
Author(s):  
Ahmed Ali Saihood ◽  
Laith Alzubaidi
Keyword(s):  
Wireless Sensor Networks ◽  
Reinforcement Learning ◽  
Sensor Networks ◽  
Natural Disasters ◽  
Energy Efficient ◽  
Wireless Networking ◽  
Wireless Sensor ◽  
Learning Methods ◽  
Underwater Environment ◽  
Learning Techniques

The wireless sensor networks have been developed and extended to more expanded environments, and the underwater environment needs to develop more applications in different fields, such as sea animals monitoring, predict the natural disasters, and data exchanging between underwater and ground environments. The underwater environment has almost the same infrastructure and functions with ground environment with some limitations, such as processing, communications, and battery limits. In terms of battery limits, many techniques have been proposed; in this chapter, the authors will focus in deep reinforcement learning techniques.

A Big Data Test-bed for Analyzing Data Generated by an Air Pollution Sensor Network

2016 ◽  
Vol 13 (4) ◽  
pp. 19-35 ◽  
Author(s):  
Lídice García Ríos ◽  
José Alberto Incera Diéguez
Keyword(s):  
Air Pollution ◽  
Big Data ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Sensor Network ◽  
Proof Of Concept ◽  
Test Bed ◽  
Pollution Levels ◽  
Wide Range ◽  
Military Applications

Sensor networks have perceived an extraordinary growth in the last few years. From niche industrial and military applications, they are currently deployed in a wide range of settings as sensors are becoming smaller, cheaper and easier to use. Sensor networks are a key player in the so-called Internet of Things, generating exponentially increasing amounts of data. Nonetheless, there are very few documented works that tackle the challenges related with the collection, manipulation and exploitation of the data generated by these networks. This paper presents a proposal for integrating Big Data tools (in rest and in motion) for gathering, storage and analysis of data generated by a sensor network that monitors air pollution levels in a city. The authors provide a proof of concept that combines Hadoop and Storm for data processing, storage and analysis, and Arduino-based kits for constructing their sensor prototypes.

scholarly journals A Route Map for Wireless Sensor Networks over Large Coverage Area

2018 ◽  
Author(s):  
Rishabh Jain ◽  
Partha Saha Adhikary ◽  
Guillermo Ramirez-Prado ◽  
Bashar Barmada ◽  
Iman Ardekani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Wireless Sensor ◽  
Coverage Area
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