IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Fault Diagonosis Approach for WSN using Normal Bias TechniqueIDES Editor
In wireless sensor and actor networks (WSAN), the
sensor nodes have a limitation on lifetime as they are equipped
with non-chargeable batteries. The failure probability of the
sensor node is influenced by factors like electrical dynamism,
hardware disasters, communication inaccuracy and undesired
environment situations, etc. Thus, fault tolerant is a very
important and critical factor in such networks. Fault tolerance
also ensures that a system is available for use without any
interruption in the presence of faults. In this paper an
improved fault tolerance scheme is proposed to find the
probability of correctly identifying a faulty node for three
different types of faults based on normal bias. The nodes fault
status is declared based on its confidence score that depends
on the threshold valve. The aim is to find the Correct
Recognition Rate (CRR) and the False Fear Rate (FFR) with
respect to the different error probability (pe) introduced. The
techniques, neighboring nodes, fault calculations, range and
CRR for existing algorithm and proposed algorithm is also
presented.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Fault Diagonosis Approach for WSN using Normal Bias TechniqueIDES Editor
In wireless sensor and actor networks (WSAN), the
sensor nodes have a limitation on lifetime as they are equipped
with non-chargeable batteries. The failure probability of the
sensor node is influenced by factors like electrical dynamism,
hardware disasters, communication inaccuracy and undesired
environment situations, etc. Thus, fault tolerant is a very
important and critical factor in such networks. Fault tolerance
also ensures that a system is available for use without any
interruption in the presence of faults. In this paper an
improved fault tolerance scheme is proposed to find the
probability of correctly identifying a faulty node for three
different types of faults based on normal bias. The nodes fault
status is declared based on its confidence score that depends
on the threshold valve. The aim is to find the Correct
Recognition Rate (CRR) and the False Fear Rate (FFR) with
respect to the different error probability (pe) introduced. The
techniques, neighboring nodes, fault calculations, range and
CRR for existing algorithm and proposed algorithm is also
presented.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
DESIGN ISSUES ON SOFTWARE ASPECTS AND SIMULATION TOOLS FOR WIRELESS SENSOR NE...IJNSA Journal
In this paper, various existing simulation environments for general purpose and specific purpose WSNs are discussed. The features of number of different sensor network simulators and operating systems are compared. We have presented an overview of the most commonly used operating systems that can be used in different approaches to address the common problems of WSNs. For different simulation environments there are different layer, components and protocols implemented so that it is difficult to compare them. When same protocol is simulated using two different simulators still each protocol implementation differs, since their functionality is exactly not the same. Selection of simulator is purely based on the application, since each simulator has a varied range of performance depending on application.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Prototyping a Wireless Sensor Node using FPGA for Mines Safety ApplicationIDES Editor
The sensor nodes in a wireless sensor network are
normally microcontroller based which are having limited
computational capability related to various applications. This
paper describes the selection, specification and realization of
a wireless sensor node using the field programmable gate
array (FPGA) based architecture for an early detection of
hazards (e.g fire and gas-leak ) in mines area. The FPGAs in
it’s place are more efficient for complex computations in
compare to microcontrollers, which is tested by implementing
the adaptive algorithm for removing the noise in sensor
received data in our work. Another advantage of using FPGA
is also due to it’s reconfigurable feature without changing
the hardware itself. The node is implemented using cyclone
II FPGA device present in Altera dE2 board .In this work the
network comprises of 4 nodes out of which 2 are test nodes,
one routing node and one base station node. An energy
efficient MAC protocol is tested for transmitting the data from
test node to base station node.
EEG Based BCI Applications with Deep LearningRiddhi Jain
Summarised a Survey Paper describing EEG Based BCI Applications and Sensing Technologies and their Computational Intelligence Approach published on Jan 28, 2020
Performance of energy balanced territorial predator scent marking algorithm b...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
NETWORK PERFORMANCE ENHANCEMENT WITH OPTIMIZATION SENSOR PLACEMENT IN WIRELES...ijwmn
From one side, sensor manufacturing technology and from other side wireless communication technology
improvement has an effect on the growth and deployment of Wireless Network Sensor (WSN). The
appropriate performance of WSN has abundant necessity which has dependent on the different parameters
such as optimize sensor placement and structure of network sensor. The optimized placement in WSN not
only would optimize number of sensors, but also help to reach to the more precise information. Therefore
different solutions are proposed to reduce cost and increase life time of sensor networks that most of them
are concentrated in the field of routing and information transmission. In this paper, places which they need
new sensors placement or sensor movements are determined and then with applying these changes,
performance of WSN will calculate. To achieve the optimum placement, the network should evaluate
precisely and effective criteria on the performance should extract. Therefore the criteria should be ranked
and after weighting with using AHP algorithms, with use of Geographical Information System (GIS), these
weighted criteria will combined and in the locations which WSN doesn’t have enough performance, new
sensor placement will create. New proposed method, improve 21.11% performance of WSN with sensor
placement in the low performance locations. Also the number of added sensor is 26.09% which is lowest
number of added sensors in comparison with other methods.
Wireless Sensor Network Simulators: A Survey and ComparisonsCSCJournals
Simulation tools for wireless sensor networks are increasingly being used to study sensor webs and to test new applications and protocols in this evolving research field. There is always an overriding concern when using simulation that the results may not reflect accurate behavior. It is therefore essential to know the strengths and weaknesses of these simulators. This paper provides a comprehensive survey and comparisons of various popular sensor network simulators with a view to help researchers choose the best simulator available for a particular application environment. It also provides a detailed comparison describing the pros and cons of each simulator.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Novel Three-Dimensional Adaptive Localization (T-Dial) Algorithm for Wirele...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
DESIGN ISSUES ON SOFTWARE ASPECTS AND SIMULATION TOOLS FOR WIRELESS SENSOR NE...IJNSA Journal
In this paper, various existing simulation environments for general purpose and specific purpose WSNs are discussed. The features of number of different sensor network simulators and operating systems are compared. We have presented an overview of the most commonly used operating systems that can be used in different approaches to address the common problems of WSNs. For different simulation environments there are different layer, components and protocols implemented so that it is difficult to compare them. When same protocol is simulated using two different simulators still each protocol implementation differs, since their functionality is exactly not the same. Selection of simulator is purely based on the application, since each simulator has a varied range of performance depending on application.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Prototyping a Wireless Sensor Node using FPGA for Mines Safety ApplicationIDES Editor
The sensor nodes in a wireless sensor network are
normally microcontroller based which are having limited
computational capability related to various applications. This
paper describes the selection, specification and realization of
a wireless sensor node using the field programmable gate
array (FPGA) based architecture for an early detection of
hazards (e.g fire and gas-leak ) in mines area. The FPGAs in
it’s place are more efficient for complex computations in
compare to microcontrollers, which is tested by implementing
the adaptive algorithm for removing the noise in sensor
received data in our work. Another advantage of using FPGA
is also due to it’s reconfigurable feature without changing
the hardware itself. The node is implemented using cyclone
II FPGA device present in Altera dE2 board .In this work the
network comprises of 4 nodes out of which 2 are test nodes,
one routing node and one base station node. An energy
efficient MAC protocol is tested for transmitting the data from
test node to base station node.
EEG Based BCI Applications with Deep LearningRiddhi Jain
Summarised a Survey Paper describing EEG Based BCI Applications and Sensing Technologies and their Computational Intelligence Approach published on Jan 28, 2020
Performance of energy balanced territorial predator scent marking algorithm b...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
NETWORK PERFORMANCE ENHANCEMENT WITH OPTIMIZATION SENSOR PLACEMENT IN WIRELES...ijwmn
From one side, sensor manufacturing technology and from other side wireless communication technology
improvement has an effect on the growth and deployment of Wireless Network Sensor (WSN). The
appropriate performance of WSN has abundant necessity which has dependent on the different parameters
such as optimize sensor placement and structure of network sensor. The optimized placement in WSN not
only would optimize number of sensors, but also help to reach to the more precise information. Therefore
different solutions are proposed to reduce cost and increase life time of sensor networks that most of them
are concentrated in the field of routing and information transmission. In this paper, places which they need
new sensors placement or sensor movements are determined and then with applying these changes,
performance of WSN will calculate. To achieve the optimum placement, the network should evaluate
precisely and effective criteria on the performance should extract. Therefore the criteria should be ranked
and after weighting with using AHP algorithms, with use of Geographical Information System (GIS), these
weighted criteria will combined and in the locations which WSN doesn’t have enough performance, new
sensor placement will create. New proposed method, improve 21.11% performance of WSN with sensor
placement in the low performance locations. Also the number of added sensor is 26.09% which is lowest
number of added sensors in comparison with other methods.
Wireless Sensor Network Simulators: A Survey and ComparisonsCSCJournals
Simulation tools for wireless sensor networks are increasingly being used to study sensor webs and to test new applications and protocols in this evolving research field. There is always an overriding concern when using simulation that the results may not reflect accurate behavior. It is therefore essential to know the strengths and weaknesses of these simulators. This paper provides a comprehensive survey and comparisons of various popular sensor network simulators with a view to help researchers choose the best simulator available for a particular application environment. It also provides a detailed comparison describing the pros and cons of each simulator.
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Novel Three-Dimensional Adaptive Localization (T-Dial) Algorithm for Wirele...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
As Wireless Sensor Networks are penetrating into the industrial domain, many research opportunities are emerging. One such essential and challenging application is that of node localization. A feed-forward neural network based methodology is adopted in this paper. The Received Signal Strength Indicator (RSSI) values of the anchor node beacons are used. The number of anchor nodes and their configurations has an impact on the accuracy of the localization system, which is also addressed in this paper. Five different training algorithms are evaluated to find the training algorithm that gives the best result. The multi-layer Perceptron (MLP) neural network model was trained using Matlab. In order to evaluate the performance of the proposed method in real time, the model obtained was then implemented on the Arduino microcontroller. With four anchor nodes, an average 2D localization error of 0.2953 m has been achieved with a 12-12-2 neural network structure. The proposed method can also be implemented on any other embedded microcontroller system.
Reliable and Efficient Data Acquisition in Wireless Sensor NetworkIJMTST Journal
The sensors in the WSN sense the surrounding, collects the data and transfers the data to the sink node. It
has been observed that the sensor nodes are deactivated or damaged when exposed to certain radiations or
due to energy problems. This damage leads to the temporary isolation of the nodes from the network which
results in the formation of the holes. These holes are dynamic in nature and can grow and shrink depending
upon the factors causing the damage to the sensor nodes. So a solution has been presented in the base paper
where the dual mode i.e. Radio frequency and the Acoustic mode are considered so that the data can be
transferred easily. Based on this a survey has been done where several factors are studied so that the
performance of the system can be increased.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Wide-band spectrum sensing with convolution neural network using spectral cor...IJECEIAES
Recognition of signals is a spectrum sensing challenge requiring simultaneous detection, temporal and spectral localization, and classification. In this approach, we present the convolution neural network (CNN) architecture, a powerful portrayal of the cyclo-stationarity trademark, for remote range detection and sign acknowledgment. Spectral correlation function is used along with CNN. In two scenarios, method-1 and method-2, the suggested approach is used to categorize wireless signals without any previous knowledge. Signals are detected and classified simultaneously in method-1. In method-2, the sensing and classification procedures take place sequentially. In contrast to conventional spectrum sensing techniques, the proposed CNN technique need not bother with a factual judgment process or past information on the signs’ separating qualities. The method beats both conventional sensing methods and signal-classifying deep learning networks when used to analyze real-world, over-the-air data in cellular bands. Despite the implementation’s emphasis on cellular signals, any signal having cyclo-stationary properties may be detected and classified using the provided approach. The proposed model has achieved more than 90% of testing accuracy at 15 dB.
The automotive industry requires an automated system to sort different sizes and shapes
objects, images which are the mainly used component in the industry, to improve the overall
productivity. There are things at which humans are still way ahead of the machines in terms of
efficiency one of such thing is the recognition especially pattern recognition. There are several
methods which are tested for giving the machines the intelligence in efficient way for pattern
recognition purpose. The artificial neural network is one of the most optimization techniques used
for training the networks for efficient recognition. Computer vision is the science and technology of
machines that can see. The machine is made by integration of many parts to extract information from
an image in order to solve some task. Principle component analysis is a technique that will be
suitably used for the application purpose for sorting, inspection, fault diagnosis in various field.
Review of Deep Neural Network Detectors in SM MIMO Systemijtsrd
A deep neural network detector for SM MIMO has been proposed. Its detection principle is deep learning. For this a neural network must be trained first, and then used for detection purpose. It doesn’t need any channel model and instantaneous channel state information CSI . It can provide better bit error performance compared with conventional viterbi detector VD and also it can detect any length of sequences. For a MIMO system, the channel estimation complexity can be avoided. It can detect in real time as arrives the receiver. The main benefit is it can be used where the channel model is difficult to design and also the channel is continuously varying with time. Ruksana. P | Radhika. P "Review of Deep Neural Network Detectors in SM-MIMO System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30535.pdf Paper Url :https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/30535/review-of-deep-neural-network-detectors-in-smmimo-system/ruksana-p
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Optimized Projected Strategy for Enhancement of WSN Using Genetic AlgorithmsIJMER
This paper put forward a new strategy for selecting the most favorable cluster head in Stable
Election Protocol (SEP). The planned approach selects a node as cluster head if it has the maximum
energy among all the available nodes in that particular cluster. It considers diverse nodes and divides
nodes among normal, transitional and advance nodes. To handle the heterogeneity of the nodes, different
optimized probability density functions are selected. First node dead time explain the network stability
period and last node dead explain the overall network lifetime. The main pressure is to increase the time
when first node dies and also when last node dies. The projected strategy is designed and implemented in
the Matlab using mathematics toolbox. The projected algorithm is also compared with the some prominent
protocols like leach, E-LEACH, SEP and extended SEP
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Model of Differential Equation for Genetic Algorithm with Neural Network (GAN...Sarvesh Kumar
The work is carried on the application of differential equation (DE) and its computational technique of genetic algorithm and neural (GANN) in C#, which is frequently used in globalised world by human wings. Diagrammatical and flow chart presentation is the major concerned for easy undertaking of these two concepts with indication of its present and future application is the new initiative taken in this paper along with computational approaches in C#. Little observation has been also pointed during working, functioning and development process of above algorithm in C# under given boundary value condition of DE for genetic and neural. Operations of fitness function and Genetic operations were completed for behavioural transmission of chromosome.
1. Ramanpreet Kaur, Jaspal Singh / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1843-1847
Neural Based Sensor Signal Change Detection By Using Radial
Bias Function
Ramanpreet Kaur1, Jaspal Singh2
1
M-Tech (ECE), R.I.E.I.T Ropar , Punjab, India
2
Professor, Electronics and Communication R.I.E.I.T, Ropar , Punjab, India
ABSTRACT
The paper describes the basic techniques The goal of the research presented in this paper is to
involved on the detection of sensor signal develop a detection system, which warns about a
changes, and describes their possible change of sensor signals in complex network
implementation on the lower level in sensor systems by comparison of currently acquired
networks. Embedded into the communication measurement results against an association model
protocols, the signal change detection will allow derived during execution. The detector operation
data compression for improving network should minimize probabilities of missing the change
efficiency. It might enhance reliability and (false negative) and/or false positive alarms
security also. The algorithms utilizes a neural (recognizing a ―normal‖ deviation, which is due to
network function prediction methodology in the inaccuracy of measurement results, as a change).
order to determine if the sensor signals have Normally measurement results fluctuate with some
changed. The literature survey is done and the degree, which does not constitute any significant
different algorithms are studied based on their change. The detection should be performed by
performance and parameter choice and the comparison of imprecise data against uncertain
relationship between the threshold values and models.
false positive and negative rates are studied the Change detection is as an identification of
basis algorithms involved in this work are MLP unforeseen change in general characteristics and
and RBF Algorithms. parameters of the signal observed. The case
involving time series is one of the most interesting
Keywords:- Multi layer Perceptron , Radial applications of the problem, attracting much
Basis Function , Sensor networks, Artificial attention, while being more complicated than an
Neural networks outlier detection .A number of different approaches
and algorithm which did not produce a generic
INTRODUCTION solution, have been proposed for change detection.
A wireless sensor network is a collection of New results in the development of a neural network
nodes organized into a cooperative network. Each based change detector. This describes the
node consists of processing capability (one or more architecture of the change detection system based on
microcontrollers, CPUs or DSP chips), may contain the neural network function predictor. The neural
multiple types of memory (program, data and flash network inputs a few different sensor signals that
memories), have a RF transceiver (usually with a allows detecting changes not in one signal only but
single omni-directional antenna), have a power also in the relationships between signals. This
source (e.g., batteries and solar cells), and feature improves detection reliability.
accommodate various sensors and actuators. The
nodes communicate wirelessly and often self- NEURAL NETWORK SIGNAL CHANGE
organize after being deployed in an ad hoc fashion. DETECTION
Systems of 1000s or even 10,000 nodes are Neural networks are computational models
anticipated. Such systems can revolutionize the way that share some of the properties of the brain. These
we live and work. networks consist of many simple ―units‖ working in
SENSOR networks (SN) technology has parallel with no central control, and learning takes
the potential of becoming the backbone of a new place by modifying the weights between
generation of real intelligent systems, capable of connections. The basic components of an ANN are
achieving symbiosis with the environment and ―neurons‖, weights, and learning rules.
embracing the methods and mechanisms that exist in In general, neural networks are utilized to
natural intelligent systems. In order to accomplish establish a relationship between a set of inputs and a
this goal, sensor networks have to adopt some set of outputs. ANNs are made up of three different
elements of cognition in addition to collecting data types of ―neurons‖: (1) input neurons, (2) hidden
from the environment and communicating them neurons, and (3) output neurons. Inputs are provided
,such as continuous self-development and self- to the input neurons, such as machine parameters,
modification with the goal to significantly improve and outputs are provided to the output neurons.
self-reliability, efficiency, and security. These outputs may be a measurement of the
1843 | P a g e
2. Ramanpreet Kaur, Jaspal Singh / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1843-1847
performance of the process, such as part output. An error is determined for the output and
measurements. The network is trained by propagated backwards through the layers. Finally,
establishing the weighted connections between the these errors are used to adjust the connections
input neurons and output neurons via the hidden between nodes. The backpropagation algorithm
neurons. Weights are continuously modified until allows for movement to a minimal error over the
the neural network is able to predict the outputs course of the training process. Each time the weights
from the given set of inputs within an acceptable are changed, the direction and magnitude of their
user-defined error level. change is determined so as to make a move towards
Although change detection in signals had the minimal error.
been investigated for a considerable time, over the The main idea of the methodology is
last two decades there have been new important 1. To perform change detection on a set of
developments. The literature on change novelty networked sensor signals based on the differences
detection is rapidly growing due to applications in between current signal values and predicted ones.
engineering, financial mathematics and economics. 2. A neural network is employed to produce
These detection techniques have developed into these signal predictions from a recent history of
various models. From a generic point of view, ANN sensor measurements.
models seem to be appropriate as a base for 3. The neural networks can be utilized with
developing fundamental algorithms utilizing no priori information on the data distribution of
opportunities, which arise from networking of the domain and without specifying other
sensor systems. parameters related to the data.
—Neural networks are distributed nonlinear devices 4. This allows the network to detect changes
Their ability to deal with nonlinear, non stationary, and after that ―renormalize‖ itself by learning new
and non-Gaussian processes makes them attractive signal values to be used for further change
for WSN practical applications. Accordingly, ANN detection.
have the inherent ability to model underlying From a generic point of view, ANN models
nonlinearities contained in the physical mechanism seem to be appropriate as a base for developing
responsible for generating input data. fundamental algorithms utilizing opportunities,
—Neural networks, operating in a supervised which arise from networking of sensor systems. The
manner, are universal approximators basic techniques involved in signal change detection
They can approximate any continuous input-output is explained .
mapping to any desired degree of approximation, LEON REZNIK et al [1] (2005): develops
given a sufficient number of hidden units. intelligent protocols, based on the detection of
—A neural network consists of a massively parallel sensor signal changes. The signal change detection
processor that has the potential to be fault tolerant. will allow data compression for improving network
As MLP consists of a large number of neurons efficiency. The protocol utilizes a neural network
arranged in the form of layers with each neuron in a function prediction methodology to determine if the
particular layer connected to a large number of sensor signals have changed. The parameter choice
source nodes in the previous layer. This form of and relationship between the threshold values and
global interconnectivity has the potential to be fault false positive and negative rates are studied. Change
tolerant, in the sense that the performance degrades detection is based on the difference between current
gracefully under adverse operating conditions. If a signal values and the predicted values. Novelty
neuron or its synaptic links are damaged, the recall detection is utilized to detect changes and after that
quality of a stored pattern is impaired, but owing to to relearn new signal values to be used for further
the highly distributed nature of the network, the changes detection. The results of the experiments
damage has to be extensive before the performance conducted demonstrate that the change detection
is seriously affected. This property open an system is both accurate and reliable. These results
opportunity to design an ANN topology distributed confirm the benefits anticipated from the modified
over a SN infrastructure. neural network and demonstrate its usefulness in
—Neural networks have a natural ability to adapt sensor prediction and change detection.
their free parameters according to changes in the Tayeb Al Karim et al (2) (2011) The paper
environment in which they operate. describes the results of an empirical study aiming to
In this tuning of free parameters in a neural demonstrate that a cognition ability may be treated
network is a more straightforward task (and as a generic sensor network feature. The new
therefore easily accomplished by a non expert user) architecture with neural networks distributed over
than would be the case with other nonparametric the sensor network platforms was developed for
methods. sensor network engineering applications. The
Multi-Layer Perceptrons (MLPs) are neural detection system learns to detect the change of not
networks that have nodes arranged in multiple only the signal levels but also sensor signal shapes
layers, with connections from one layer to the next. and parameters that represent a more complicated
Data is feed forward through the network to produce task. The architecture allows for a significant
1844 | P a g e
3. Ramanpreet Kaur, Jaspal Singh / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1843-1847
reduction in resource consumption without sensor networks. The power savings are evaluated
compromising the change detection performance. from the perspective of the WSN nodes. Power
Implemented as an agent controlling the sensor mode switching is determined via change detection
network self-adjustment to the objects under in measured signals. The change detection is based
measurement in the sensor network composed from on the observation of number of signals which are
typical sensor motes, the novel neural network measured in the environment and the measurement
structures may achieve a significant saving in power results delivered to the base station for processing.
consumption and an increase in a possible network To perform this change detection ANN based
deployment time from a few days to a few years. intelligent agent has been developed and
The experiments prove that a neural-network-based implemented and a novel neural network topology
change detection system is feasible for sensor has was designed for wireless sensor networks. The
networks application designs and could be architecture is built upon a multilayer perceptron
successfully implemented on the technological neural network to reduce the number of connections
platforms currently available on the market. The between the layers. The experiment conducted
proposed MTBMLP architecture has been tested and confirms that this network decreases the resources
compared against a conventional MLP on changes such as time and power consumption required for its
of both frequencies and amplitudes signal implementation without causing any increase in
parameters and with different types of signals (sine false alarm rates.
and square waves, constant values). LEON REZNIK et al 2008 puts the concept
LEON REZNIK et al [3] (2005) describes of cognitive sensor networks. This research paper
the design and implementation of a novel intelligent describes the results of an experimental study and
sensor network protocol that enhances reliability development of novel neural network intelligent
and security by detecting a change in sensor signals. technique for signal change detection in sensor
Neural network function prediction methodology is networks. The detection system learns to detect the
used to predict sensor outputs to determine if the change of not only the signal levels but also sensor
sensor outputs have changed. The experiments signal shapes and parameters. The ANN is capable
performed to the different training times and to handle detection with both problems as well as to
threshold values and these experiments adapt to the new pattern. The ANN architecture
demonstrates that the system performs better when maps with the ANN structure and reduces
presented with correlated data rather than randomly connectivity. Signal propagation through the ANN
generated data the difference between the false faster in both forward and backward directions that
alarm rates and detection for the correlated and allows increasing speed of the application. At the
uncorrelated sensor and changes have been seen same time novel structure reduces the consumption
and these results confirm the benefits anticipated of major resources network bandwidth processor
from the modified neural network and shows its power and memory usage.
usefulness in sensor prediction and novelty TAYEB AL KARIM et al (2005) In this
detection. Detection rates and false alarm rates research paper detection system is developed and
become better when data and changes presented to change of sensor signals in complex network
the system are correlated in positive. The limitation systems is studied by comparing currently acquired
is the system’s inability to learn properly long clock measurement results against an association model
signals. The second problem is the predetermined derived during execution. The detector operation
error threshold. The threshold can be set very high should minimize the probabilities of false negative
or very low causing a notable increase in the false or false positive alarms. Measurement results are
alarm rate and too high causing a drop in the not always accurate, they always fluctuate with
detection rate. some degree. This paper describes the architecture
GREGORY VON PLESS [4] et al of the change detection system based on the neural
introduces Modified time based multilayer network function predictor. Two function prediction
perceptron (MTBMLP), complex structure designs are compared based on the standard multi-
composed by a few time-based multilayer layer perceptron (MLP) and Radial basis function
perceptrons. This modification reduces connections, network (RBF).
isolates information for each function and produces It studies the dependence of the detection
knowledge about the system of functions as a whole. and false alarm rates on the threshold values for
It is powerful function predictor that converges different signals and changes. With respect to the
quickly and accurately predict cyclic sinusoid training time, the detection rates and false positive
functions. This neural network is applied for novelty rates remained unchanged with training times at any
and change detection in signals delivered by sensor given threshold. With respect to the threshold
networks and for edge detection in image detection rates went down with higher thresholds.
processing. MTBMLP performs much quicker than the MLP.
JODY PODPORA et al [5] (2008) develop Different experiments were conducted in this paper
an intelligent and power conservation scheme for which includes turning lights on/off, flickering
1845 | P a g e
4. Ramanpreet Kaur, Jaspal Singh / International Journal of Engineering Research and
Applications (IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 5, September- October 2012, pp.1843-1847
lights, gradual change of temperature with opening a
door.
1. PROBLEM FORMULATION
The analytical formulation of the research
is based on function prediction using neural network
.There is rapid enhancement in this field of
application and their comparative factor have to be
explored to generate recurrent priority. We have
different algorithms in neural networks for sensor
signal change detection. Multilayer perceptron
(MLP) and Radial basis network (RBF) are used to
determine change in sensor outputs. RBF performs
well than MLP for all parameters. Now days a
number of structures have been proposed for signal
change detection. Structure based on RBF function
is expected to perform better in predicting accuracy Fig 2: Relationship between threshold and detection
with low false alarm rates. Thus in this paper we
rates for MLP, RBF and improved RBF
purpose a structure based on RBF algorithm which
will improve the parameters (threshold and training
lengths) in signal change detection of the sensor
3. CONCLUSION
It is necessary to develop new ANN
networks then the existing.To improve the
topologies to produce the most efficient ANN based
performance of RBF by varying intrinsic parameters
applications on network platforms. Ideally the
(threshold & training length) is the major objective
topologies should be scalable over large networks
which we realise from the research gaps of the basic
and have made apparent an advantage in
literature survey.
performance and efficiency when using Radial Basis
activation for sensor network change detection
2. RESULTS AND DISCUSSIONS purposes. The greatest advantages are the greater
The RBF are able to predict the sensor
signal prediction accuracy. The learning rate
functions with greater accuracy. With the threshold advantage could be used most effectively for change
set to 0.1 these changes were detected with a rate of detection in sensor signals with changes that are
98%.This allows the use of a lower threshold value densely distributed over time. False alarms were
in the novelty detector. The improved RBF has its virtually nonexistent in the RBF network. A Radial
optimal performance at a lower threshold. At lower Basis activation function is clearly the better choice
threshold it is able to detect 100% of sensor signal for sensor signal change detection systems.
changes. The MLP operates optimally at the 0.5
threshold value, however the results are significantly
worse than that of the RBF. With 100% detections,
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