In this paper, we provide the solution for physically challenged people like hearing impaired people .It is a
smart application works for the hearing impaired people. People with hearing loss have move through the
activities of daily living at home, at work and in business situations. People may face the difficulty in hearing
the environment sounds and identifying the sounds. Our main contribution for the hearing impaired people is
to make them understand the type of sounds which is useful to them. The conventional sound recognition
techniques are not directly applicable since the background noise and reverberations are high which leads to
low performance. A deep neural network which is capable of classifying and predicting the information from
unstructured data such as image, text or sounds that makes the machine to get the environmental sounds. In
this paper, a deep learning algorithm called CNN(convolution neural network) which classify the sound audio
clips. This model will results the accuracy of 80% which is higher than the conventional technique .It achieves
good results comparable to other approaches.
deep learning; convolution neural network; feature extraction; sound recognition; sound event
classification.
Flooding is considered one of the most devastating natural disasters in the world. In countries like India with
climatic conditions occurrence of heavy rain fall and subsequent discharge of water leads to Flood. Flooding
creates major damages to life , their habitats and the economy By installing of flood alerting systems near
major waterways vital information can be provide so that lives and property can be protected. Normal Weather
monitoring and alerting systems are not quick and accurate enough to predict floods in time to prevent personal or
environmental damages. The government has to spend tons of money in flood mitigation plans to help the victims
and also to reduce the number in the long run damages that can occur after flooding. Since Most of the flood alerting
systems involves high cost they are deployed on select locations based on priority.In this project we make use of a
cost effective system using raspberry pi board and sensors, to measure flood flow rate and rise of water level in
revvers and water bodies and alert government authorities and people instantly by transmitting information using
IOT. In the present work we have used thingspeak-IOT platform . The data can be accessed from android smart
phones using thingsView mobile application at any time from anywhere in the world.
Our future battle field system will have more difficulties to maintain security, because of increasing military competitive. Ability to understand, predict and adopt the vast array of inter-networked things is very difficult. Unwanted fire, unauthorized human intervention and other object movement will play major important role for affecting military environment. This project aims to help our future military environment by introducing new technology LoRaWAN in IoT (Internet of Things). LoRaWAN (Long Range Wide Area Network) is a state -of- art commercial of the self (COTS) technology. This project consist of sensors, embedded microcontrollers equipped with LoRaWAN, embedded processors equipped with LoRaWAN and cloud technology. By introducing this new technology in our future military environment we can easily find out criminal activities and fire hazards.
The challenging problem faced by quadriplegics and paralyzed people is their need for independent mobility. They need
external help to perform their daily activities. The main objective of this project is to provide an automated system for
disabled people to control the motor rotation of wheelchair based on neck movement of physically challenged person. To
facilitate these people for their independent movement, tilt sensor is fitted on person neck. Based on the neck movements,
the accelerometer (tilt sensor) will drive the motor fitted to the wheelchair. The wheel chair can be driven in any of the
four directions and it can also be controlled by using android app (Blynk app). The automated wheelchair is based on
simple electronic control system and the mechanical arrangement that is controlled by a Controller. The ultrasonic
sensors help to avoid obstacles, using the environment information gathered during navigation. The temperature sensor
and heartbeat sensor constantly measure the parameters and display it on LCD.
Wildlife entering in to populated areas has
recently become very Popular. The space for wild
animals is decreasing as humans are encroaching
forests. It creates great loss to property and life
when wild animals enter in to cities. We use latest
advances in technology such as Internet of Things
(IoT) to create an alert system of possible wildlife
leaving the forest and also the message will send to
the users Mobile to alert them. We use low cost
motion detectors and Passive Infrared sensors to
achieve this. We relay information of such motion
to a control centre to take further actions. We also
include making loud noise through speakers in
which the animals cannot enter in to land. The
basic idea of IoT is to connect different sensors
and establish communication and also provide
services. In this article, we make use of several IoT
devices at the periphery of natural reserve to
create an alert system. This system can also be
used to find out smugglers and other people
illegally entering in to the forest.
Flooding is considered one of the most devastating natural disasters in the world. In countries like India with
climatic conditions occurrence of heavy rain fall and subsequent discharge of water leads to Flood. Flooding
creates major damages to life , their habitats and the economy By installing of flood alerting systems near
major waterways vital information can be provide so that lives and property can be protected. Normal Weather
monitoring and alerting systems are not quick and accurate enough to predict floods in time to prevent personal or
environmental damages. The government has to spend tons of money in flood mitigation plans to help the victims
and also to reduce the number in the long run damages that can occur after flooding. Since Most of the flood alerting
systems involves high cost they are deployed on select locations based on priority.In this project we make use of a
cost effective system using raspberry pi board and sensors, to measure flood flow rate and rise of water level in
revvers and water bodies and alert government authorities and people instantly by transmitting information using
IOT. In the present work we have used thingspeak-IOT platform . The data can be accessed from android smart
phones using thingsView mobile application at any time from anywhere in the world.
Our future battle field system will have more difficulties to maintain security, because of increasing military competitive. Ability to understand, predict and adopt the vast array of inter-networked things is very difficult. Unwanted fire, unauthorized human intervention and other object movement will play major important role for affecting military environment. This project aims to help our future military environment by introducing new technology LoRaWAN in IoT (Internet of Things). LoRaWAN (Long Range Wide Area Network) is a state -of- art commercial of the self (COTS) technology. This project consist of sensors, embedded microcontrollers equipped with LoRaWAN, embedded processors equipped with LoRaWAN and cloud technology. By introducing this new technology in our future military environment we can easily find out criminal activities and fire hazards.
The challenging problem faced by quadriplegics and paralyzed people is their need for independent mobility. They need
external help to perform their daily activities. The main objective of this project is to provide an automated system for
disabled people to control the motor rotation of wheelchair based on neck movement of physically challenged person. To
facilitate these people for their independent movement, tilt sensor is fitted on person neck. Based on the neck movements,
the accelerometer (tilt sensor) will drive the motor fitted to the wheelchair. The wheel chair can be driven in any of the
four directions and it can also be controlled by using android app (Blynk app). The automated wheelchair is based on
simple electronic control system and the mechanical arrangement that is controlled by a Controller. The ultrasonic
sensors help to avoid obstacles, using the environment information gathered during navigation. The temperature sensor
and heartbeat sensor constantly measure the parameters and display it on LCD.
Wildlife entering in to populated areas has
recently become very Popular. The space for wild
animals is decreasing as humans are encroaching
forests. It creates great loss to property and life
when wild animals enter in to cities. We use latest
advances in technology such as Internet of Things
(IoT) to create an alert system of possible wildlife
leaving the forest and also the message will send to
the users Mobile to alert them. We use low cost
motion detectors and Passive Infrared sensors to
achieve this. We relay information of such motion
to a control centre to take further actions. We also
include making loud noise through speakers in
which the animals cannot enter in to land. The
basic idea of IoT is to connect different sensors
and establish communication and also provide
services. In this article, we make use of several IoT
devices at the periphery of natural reserve to
create an alert system. This system can also be
used to find out smugglers and other people
illegally entering in to the forest.
These days heart diseases are
considered as the major health issue. It
includes heart attack and cardiac arrest.
Heart attack is the global leading cause
of death for both the genders and
occurrence is not always know.
Sometimes heart attack is often
compared with other type of pain and
not often dealt with it. Hence, this
project is to implement the heart rate
monitoring using IOT. The patients are
expected to carry or wear a hardware
sensor. The sensor with note the heart
rate and transmits it through internet.
The patient may be expected to set the
high and low heart rate individually. On
reaching the high rate or going below
the expected heart rate, an emergency
alert notification is sent to the patient’s,
guardian, doctor and
ambulance(optional) android devices.
Survey of a Symptoms Monitoring System for Covid-19vivatechijri
The Internet of Things (IOT) depicts the organization of actual items that are implanted with sensors, programming, and different advances for the point of interfacing and trading information with different gadgets and frameworks over the web . In this day and age, there are numerous IOT based, these IOT based gadgets and machines range from wearable like brilliant watches to RFID stock following chips. IOT associated gadgets convey by means of organizations or cloud-based stages associated with the snare of Things. Among the applications that Internet of Things (IOT) encouraged to the planet , Healthcare applications are generally imperative . There are numerous wellbeing checking gadgets accessible. These framework comprises two sensors that is Heartbeat and blood heat sensor and furthermore contains Arduino UNO. This versatile gadget will screen heartbeat and blood heat utilizing sensors. The framework utilizes Arduino board which is associated with heart beat sensor and temperature sensor. The framework will take contribution from the guts beat and blood heat sensors and can send the data to Arduino. The Arduino will send the information of two sensors to LCD alphanumeric presentation . This presentation will show the perusing of the heartbeat sensor and blood heat sensor in BPM (Beats Per Minute) and in Celsius or Fahrenheit.
Io t based water level monitoring system of dams insangamesh kumbar
IoT-BASED WATER LEVEL MONITORING SYSTEM OF DAMS IN KARNATAKA,This project proposes a wireless solution, based on Global System for Mobile Communication (GSM) network for the monitoring and controlling of the dams water level parameter.
The equipment uses an ultrasonic sensor device to accurately measure and determine the waters in real time.
The standalone Water Level Monitoring System is equipped with solar panel and makes use of an ultrasonic sensor to measure the rate of change of water level using the principle similar to radar and sonar.
The sensor calculates the time interval between sending the signal and receiving the echo to determine the water level.
The information collected is then transmitted to a central server at a predefined interval, via SMS.
The most of the technical challenges for the society to detect and find a solution for visually impaired, with increased security and service motto towards the society helped to bring a solution which would help the visually impaired in the industries and other companies. Here we had come out with a prototype as a way of finding a solution to the visually impaired. The navigation assistant technology using RFID Tag Grid minimizes the dependency. The reader used in this system is embedded in the mobile and shoes to avoid dependency on travel. The RFID reader matches with the information specified to that ID and a voice signal is generated. Wireless RF links is placed in the Bluetooth device/ headphone for voice guidance. The proximity sensing unit is an auxiliary unit is added as a solution to address unexpected and non-mapped obstacles in the user’s path. Basically it contains ultrasonic Sensor Unit interfaced with microcontroller which is inter-linked to a vibrator that would be activated when nearing obstacles. This system is technically and economically feasible and may offer a maximum benefit to the disabled.
In our paper several issues of sustainable transport is brought into the spotlight. In this fast paced world
everyone wants everything to happen just in the tick of a second and the wink of an eye. It is widely
acknowledged that traffic congestion threatens economic growth and irritates today’s pacing world. With
the increasing use of transport worldwide, it is necessary to derive solutions to ease traffic. Moreover
transportation now accounts for about 40 per cent of the total use of energy in the world. As a result, there
is an increased focus on how best to make it easier and more attractive for people to use public transport.
For the last two decades IT (Electronics + Computer) has been positioned as the instrument for travel
substitution. IT has been successful in all fields it has been applied to. Similarly it would definitely be a
great help to the strange challenge that transport poses on environment. There are three main things which
we must concentrate on congestion avoidance, accident avoidance,driver assistance and automize only in
needed situations with zone detection. it is much more important in this present day to derive a method
for disabled personalities to drive with ease. Developing special vehicles discriminate them from the
normal man and also it may not be cost feasible. Our project will be a globalised solution which will be
applicable to mankind of all categories. It may be applied to any nation (developed, developing or under
developed).We proudly state that it is location transparent. Every nation has started their development
process in ITS. ITS USA has announced that they expect the industry to be fully grown by 2030 and we
hope that ours would be a small contribution to the world ITS.
These days heart diseases are
considered as the major health issue. It
includes heart attack and cardiac arrest.
Heart attack is the global leading cause
of death for both the genders and
occurrence is not always know.
Sometimes heart attack is often
compared with other type of pain and
not often dealt with it. Hence, this
project is to implement the heart rate
monitoring using IOT. The patients are
expected to carry or wear a hardware
sensor. The sensor with note the heart
rate and transmits it through internet.
The patient may be expected to set the
high and low heart rate individually. On
reaching the high rate or going below
the expected heart rate, an emergency
alert notification is sent to the patient’s,
guardian, doctor and
ambulance(optional) android devices.
Survey of a Symptoms Monitoring System for Covid-19vivatechijri
The Internet of Things (IOT) depicts the organization of actual items that are implanted with sensors, programming, and different advances for the point of interfacing and trading information with different gadgets and frameworks over the web . In this day and age, there are numerous IOT based, these IOT based gadgets and machines range from wearable like brilliant watches to RFID stock following chips. IOT associated gadgets convey by means of organizations or cloud-based stages associated with the snare of Things. Among the applications that Internet of Things (IOT) encouraged to the planet , Healthcare applications are generally imperative . There are numerous wellbeing checking gadgets accessible. These framework comprises two sensors that is Heartbeat and blood heat sensor and furthermore contains Arduino UNO. This versatile gadget will screen heartbeat and blood heat utilizing sensors. The framework utilizes Arduino board which is associated with heart beat sensor and temperature sensor. The framework will take contribution from the guts beat and blood heat sensors and can send the data to Arduino. The Arduino will send the information of two sensors to LCD alphanumeric presentation . This presentation will show the perusing of the heartbeat sensor and blood heat sensor in BPM (Beats Per Minute) and in Celsius or Fahrenheit.
Io t based water level monitoring system of dams insangamesh kumbar
IoT-BASED WATER LEVEL MONITORING SYSTEM OF DAMS IN KARNATAKA,This project proposes a wireless solution, based on Global System for Mobile Communication (GSM) network for the monitoring and controlling of the dams water level parameter.
The equipment uses an ultrasonic sensor device to accurately measure and determine the waters in real time.
The standalone Water Level Monitoring System is equipped with solar panel and makes use of an ultrasonic sensor to measure the rate of change of water level using the principle similar to radar and sonar.
The sensor calculates the time interval between sending the signal and receiving the echo to determine the water level.
The information collected is then transmitted to a central server at a predefined interval, via SMS.
The most of the technical challenges for the society to detect and find a solution for visually impaired, with increased security and service motto towards the society helped to bring a solution which would help the visually impaired in the industries and other companies. Here we had come out with a prototype as a way of finding a solution to the visually impaired. The navigation assistant technology using RFID Tag Grid minimizes the dependency. The reader used in this system is embedded in the mobile and shoes to avoid dependency on travel. The RFID reader matches with the information specified to that ID and a voice signal is generated. Wireless RF links is placed in the Bluetooth device/ headphone for voice guidance. The proximity sensing unit is an auxiliary unit is added as a solution to address unexpected and non-mapped obstacles in the user’s path. Basically it contains ultrasonic Sensor Unit interfaced with microcontroller which is inter-linked to a vibrator that would be activated when nearing obstacles. This system is technically and economically feasible and may offer a maximum benefit to the disabled.
In our paper several issues of sustainable transport is brought into the spotlight. In this fast paced world
everyone wants everything to happen just in the tick of a second and the wink of an eye. It is widely
acknowledged that traffic congestion threatens economic growth and irritates today’s pacing world. With
the increasing use of transport worldwide, it is necessary to derive solutions to ease traffic. Moreover
transportation now accounts for about 40 per cent of the total use of energy in the world. As a result, there
is an increased focus on how best to make it easier and more attractive for people to use public transport.
For the last two decades IT (Electronics + Computer) has been positioned as the instrument for travel
substitution. IT has been successful in all fields it has been applied to. Similarly it would definitely be a
great help to the strange challenge that transport poses on environment. There are three main things which
we must concentrate on congestion avoidance, accident avoidance,driver assistance and automize only in
needed situations with zone detection. it is much more important in this present day to derive a method
for disabled personalities to drive with ease. Developing special vehicles discriminate them from the
normal man and also it may not be cost feasible. Our project will be a globalised solution which will be
applicable to mankind of all categories. It may be applied to any nation (developed, developing or under
developed).We proudly state that it is location transparent. Every nation has started their development
process in ITS. ITS USA has announced that they expect the industry to be fully grown by 2030 and we
hope that ours would be a small contribution to the world ITS.
Human Computer Interface Glove for Sign Language TranslationPARNIKA GUPTA
A human computer interface glove was developed with the aim of translating sign language to text & speech. The glove utilizes five flex sensors and an inertial measurement unit to accurately capture hand gestures. All components were placed on the backside of the glove providing the user with full range of motion, and not restricting the user from performing other tasks while wearing the glove.
Motion of curtains using Natural Language Processingijtsrd
Consider a scenario of a paraplegic person who is on the bed reading a book and wishes to close the door because of the noise outside. The old system would probably comprise of calling someone either the maid, or relative etc. to close the door. This project aims to automate many of the home items by the use of voice. It can be implemented using an embedded system such as a processor capable of processing natural language and a mechanical system to cause motion on the item accordingly. For a user of the system, all the person would need to do is give commands like “Open Doorâ€, “Close Door†etc. and the door would perform motion as per the instruction. To demonstrate the concept, we are automating the closing and opening of curtains purely based on voice instructions. Here, voice is taken as input by a microphone, sent to a processor, and is processed. This project is based on upcoming technologies and has wide scope throughout. Appropriate changes will have to be made depending upon the application and mechanical system used for the implementation but the core concept remains using voice as input to automate items, in particular household items. Minu Mariya Vilson | Menon Bhavana Rajan | Mithu Raveendran | Namitha Gopinath | Nelson Varghese | Mrs. Ann Rija Paul ""Motion of curtains using Natural Language Processing"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-3 , April 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23199.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/23199/motion-of-curtains-using-natural-language-processing/minu-mariya-vilson
In this Project, a multi-input DC-DC converter is proposed and studied for hybrid electric vehicles (HEVs). Compared to conventional works, the output gain is enhanced, photovoltaic (PV) panel and energy storage system (ESS) are the input sources for proposed converter. The Super capacitor is considered as the main power supply and roof-top PV is employed to charge the battery, increase the efficiency and reduce fuel economy. The converter has the capability of providing the demanded power by load in absence of one or two resources. Moreover, power management strategy is described and applied in control method. A prototype of the converter is also implemented and tested to verify the analysis.
A mobile application which can save time, effort and money by giving technical video explanation based on the recognized image for learners. The collected video information contains all the detailed explanation of the scanned image done by the user. This application groups Augmented reality , 3d objects , sound , video , AI for image recognition into an easy and compact application for the benefit of the every learner. This web application is built C#, UNITY, VUFORIA with the help of Vuforia server connected by asserts. This mobile application serves as an easier way to access details and documentaries related to recognized object. It includes an automatic AR Camera and image target along with the video player which makes it easier for recognizing the image and to learn. The database is done with Vuforia cloud database. The UI provides an excellent user friendly environment that makes the communication more interactive.
Agricultural research has strengthened the optimized
economical profit, internationally and is very vast and
important field to gain more benefits.
In future agriculture is the only scope for all the people. But
today number of people having land, but they don’t know how
to yield the crops.
So many of people are doing useless agriculture by
cultivating the crop on improper soil. To implement the
application to identify the types of soil,water source of that
land whether that land is based on rain or bore water. And
suggest what of crop is suitable for that soil. So through this
application provide application for the people to know about
the agriculture. There is no any application to know about the
cultivation. However, it can be enhanced by the use of different
technological resources, tool, and procedures. Predict the type
of crop which one is suitable for that particular soil, weather
condition, temperature and so on. So for, using machine
learning with the set of data set are identified the crop for the
corresponding soil.
In this engaged life, people tend to forget
scheduling their meetings and events that are very
important in their day to day life. They wish to have
someone who keeps on prompting them to lineup the work
and to make sure that they accomplished the scheduled
task on time. The solution to this problem is proposed
through an Android Application named “Nudge” using
artificial intelligence. This application is built using
Android Studio IDE 3.3 released by the Google. The
application is used to trigger alarms based on locations,
where the user can set a reminder to a location and select a
range within which the alarm should be triggered. Once
the user move into that range, the alarm goes on. This
application is also used to set reminders based on the mails
the user receives. Suppose, if a user receives a mail
containing any schedule for a meeting or an event, this
application will automatically set a reminder to that
particular event in the OS calendar. This application also
includes facility to directly set a reminder to the OS
calendar.
Keywords-Location, reminder, alarm, calendar, gmail, date
In the EXISTING SYSTEM, Ballot
based Voting is present, but still there is no system to
avoid Proxy Casting and Recasting is implemented.
We do not have an option to see our casted Vote also.
There is no security in this current application. In the
PROPOSED SYSTEM, a novel electronic voting
system based on Blockchain that addresses some of
the limitations in existing systems and evaluates some
of the popular blockchain frameworks for the purpose
of constructing a blockchain-based e-voting system.
In the MODIFICATION part of the project, we
integrate Aadhaar card linked mobile number for
OTP generation, only then the voter can cast the vote,
this system prevents casting and re-casting of proxies.
The Android application is widely used in all
sectors. In our application it helps to track the
location of the bus. By waiting near the bus stop
for a long time this application helps to reduce the
waiting time of the students using Google map. The
arrival time of a bus is calculated based upon the
pickup point and the starting time of a bus in the
shuttle routes. Providing the accurate bus timing
will be helpful for all the students, staff to catch the
bus at the right time. In a college bus driver is
assigned with a mobile phone where we can use to
track the current location of the bus. Notification
will be sending to the students and parents once
the bus is nearby pick up point and drop point by
using Geo-fencing. Quick Response code is used to
track the attendance of the student whether they
boarded the bus at the pickup point. Common
alert message will be sent to students, staffs and
faculty about the holidays or any crucial
information.
Geo-fencing, Google map, GPS
(Global Positioning System)
The objective of this paper is to use the
Android mobile application to purchase grocery
items. This would help the consumers to purchase the
grocery items through their mobile application and
get the grocery items delivered to their home, office
or anywhere else directly. The users can also select
the nearby provision store or any other supermarket
which is present in their location and then select their
items. The application is thoroughly built only in the
Android platform and is supported only for Android
mobiles. Thus, the application guarantee about userfriendly
in use, provides help desk, security services
etc. This would save the time of the purchaser instead
of going to the grocery store to snap up the items and
standing on a big queue for debiting the products
andwould also help the shop proprietor to develop
their business which will not depreciate their business
revenue for adapting this system by the consumers. It
also helps retailers to create brand awareness so that
the consumers feel self-assured to themselves about
the products procure through online. This would lead
the consumers to increase their familiarity in
purchasing grocery products through an online
application using the internet. The shopkeepers
should also ensure timely delivery of ordered grocery
products without any imperfection in the products
and also ensuring the damage to the products at the
time of deliverance.
—In a laboratory experiment was conducted on
the utilization of Ethanol-Diesel emulsion in a single
cylinder direct injection diesel engine, a single cylinder,
water cooled, four stroke diesel engine was used. The
principal goals of the present work are to obtain emission
data and combustion characteristics for this type of Diesel
Engine, and to identify the ratio of Emulsion which is
effective in reducing emissions. Experiments were
conducted with emulsions viz (90%diesel + 10%ethanol),
(80% diesel + 20% ethanol), (70% diesel + 30%ethanol) as
fuel. While AVL smoke meter was employed to measure
the smoke density in HSU, the exhaust gas analyzer was
used to measure the NOx emission. High volume sampler
was employed to measure the particulate matter emitted at
the exhaust. The combustion characteristics were studied
using AVL combustion analyser. From the experimental
investigation it was found that the smoke, particulate
matter and Oxides of Nitrogen emissions were reduced
marginally. From the pressure curve and cumulative heat
release curve, it was observed that the combustion started
earlier and the rate of pressure rise increased marginally.
The present research work demonstrates the
preparation of Copper Oxide Nanoparticles (CuO NPs) and
investigates the thermo mechanical properties of the CuO NPs
embedded in the polymer composites experimentally. In this study,
CuO NPs were produced by aqueous precipitation method and
morphology of the NPs was studied using Field Emission
Transmission Electron Microscope (FESEM). Epoxy resin and glass microsphere were considered the base material for the preparation of
the Nano based polymer composites. In order to fabricate the Nano
based polymer composites, CuO NPs with 1.0wtpercentage were
embedded in the base material by means of compression moulding
press. Nano composites proved higher thermal conductivity
enhancement rather than the base material. While comparing to the
base material, the maximum four-point bending strength of 415 MPa
was obtained from the Nano based polymer composites. The test
results obtained from the TG study revealed that an addition of CuO
NPs had acted as the thermal retardant and CuO NPs had delayed
thermal degradation of the Nano based polymer composites. Based
on the test results, it can be suggested that the newly fabricated
nanocomposites have achieved the improved thermal and mechanical
properties.
The Surface roughness prediction method using
artificial neural network (ANN) and Adaptive Neuro Fuzzy
Inference System (ANFIS) are developed to investigate the
effects of cutting conditions during turning of EN8 material.
The ANN model of surface roughness parameters (Ra) is
developed with the cutting conditions such as cutting speed,
feed rate and depth of cut as the affecting process
parameters.
The experiments are planned and totally 27 settings
with three levels defined for each of the factors in order to
develop the knowledge based system. The ANN training
method is used for back-propagation training algorithm
(BPTA) and also for training the Adaptive neuro fuzzy
inference system (ANFIS). We have compared the
Artificial Neural Network and Adaptive neuro fuzzy
inference systems.
The main objective of this paper is to
determine casting defects generally happening in an
aluminium die casting process and efforts have been
taken to identify the tools which eliminate the casting
defects. In global prospective this study briefs the
application of the various tools that are used in the
industries for improvement of quality in foundry
industry. In our national prospective these tools are not
so popular, hence this study will help us to utilise the
available technology through which the productivity is
enhanced with safe and economical means. The QC
tools were used to analyse the casting condition of the
given pattern with three dimensional simulations for the
result preparation. This work has been carried out to
improve the quality of the pattern which is made with
gravity die casting process and this was achieved
through continuous quality control operation with QC
tools, then it was taken to test in some simulation
software. The latest trend available in casting and
foundry shops are the scientific approach in
optimization of all kind of fields including optimization
of defects in castings. These trends are incorporated in
the analysis of aluminium die casting.
Friction Stir Welding, a type of welding which was
discovered in the year of 1991 with a few countable methods
and processes. But today it is one of the necessary and
important type of welding techniques. To develop it, several
researchers showed their interests in this technique. Today,
it acts as the heart of welding of automobiles. Thousands of
inventions has been made in field of Friction Stir Welding
and also successfully being implemented. If a researcher
tries to make some research in this field, he has to go
through thousands of journals where hours of time is being
consumed. To solve that problem several Re-view journals
are being published and also successfully solved this issue
of time consumption. In this paper, similarly a re-view of
several important and different types of papers are discussed
with their results, outcomes, the parameters being performed
for analysis.
This paper also discusses about various methods and various
metals as tools and job materials. It will be much easier and
lenient to understand from this paper to research. The
authors of the papers also clearly explained about the usages
and applications of their methods and provided several
statistical data for clear observation of their methods
Pure and Al substituted Langanite
(La3Ga5.5Nb0.5O14) ceramics have been synthesized
by solid state sintering method and studied their
structural, dielectric and electrical properties. The
crystalline nature was confirmed by powder XRD
studies. The ac conductivity and dielectric
properties of La3Ga5.5-xAlxNb0.5O14 samples were
examined by using complex impedance technique.
Surface morphology and elemental composition
were studied by energy-dispersive x-ray
spectroscopy and scanning electron microscopy.
The frequency dependence of dielectric constant,
dielectric loss and AC conductivity were studied in
the frequency range of 100 KHz to 3 MHz at
different temperatures. The activation energy was
calculated using Arrhenius plot. The lattice
parameter, grain size, dielectric constant and AC
conductivity of pure LGN ceramics were deeply
affected by Al substitution in pure LGN.
In this paper, the non-invasive
methodology for removing Fetal Electrocardiogram
(FECG) is gained by subtracting the balanced
variation of maternal electrocardiogram (MECG)
movement from the abdominal electrocardiogram
(AECG) banner. The banner assessed from the
mother's guts (AECG) is regularly overpowered by
maternal heartbeat. The maternal portion of the
AECG is the nonlinearly changed variation of
MECG. This paper uses an Adaptive Neuro-Fuzzy
Interference System (ANFIS) structure. It is used
for finding the non-direct change and the ensuing
banner are set up with people based request
figurings. This strategy involves some specific
issues which are a direct result of the low force of
the fetal ECG which is sullied by various
wellsprings of checks. It joins maternal ECG,
electromyogram (EMG) signals, power line
impedances and sporadic electronic upheavals.
Along these lines, we are proposing an improved
multimode PSO estimation for overcoming this
issue. In addition, methods like wavelet change,
flexible filtering, thresholding are moreover used.
We have furthermore empowered the thoracic and
stomach signals using MATLAB programming. It
uses only two signs recorded at the thoracic and
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test shows that the proposed count can expel FECG
banner immediately in pregnancy period and that is
one of the basic focal points of figuring.
Almost since the first days of flight, man has been
concerned with the safe escape from an aircraft, which
was no longer flyable. Early escape equipment
consisted of a recovery parachute only. As aircraft
performance rapidly increased during World War II, it
became necessary to assist the crew members in
gaining clear safe separation from the aircraft. This
was accomplished with an ejector seat, which was
powered by a propellant driven catapult - the first use
of a propulsive element in aircrew escape Since then,
this collection of componentry has evolved through
several generations into today's relatively complex
systems, which are highly dependent upon propulsive
elements. Ejection seats are one of the most complex
pieces of equipment on any aircraft, and some consist
of thousands of parts. The purpose of the ejection seat
is simple: To lift the pilot straight out of the aircraft to
a safe distance, then deploy a parachute to allow the
pilot to land safely on the ground
The current paper is mainly about maintaining a secure
environment and also free from thefts that are happening
in our home. The present paper discusses about the
detection of intruders with the help of the various
devices and software.. OpenCV(open source computer
vision) is the major software that is being used in our
present work. For detecting faces we are using various
algorithms like Haar cascade, linear SVM, deep neural
network etc. The main method that we have proposed in
our work is, if any person comes in front of the pi
camera, first it will look for potential matches that we
have already stored in our system If the module finds a
match then it continues to record until any intruder
comes. If the face is not recognized then the unknown
person’s face will be captured and a snap shot will be
sent to the user’s email. The device is developed using
Raspberry Pi b+ with 1.4 GHz quad core processor,
raspberry pi camera module and a Wireless dongle to
communicate with user’s email.
OpenCV, Rassberry pi, python
The aim of this article is to explain the readers the technique of sending data from the sensor
through the Raspberry pi and communicating it to the Thingspeak cloud which is an IOT
platform. To explain the procedure a simple ultrasonic sensor HC-SR-04 which senses objects
up to a distance of 13 ft connected with a raspberry Pi board is used.
This tutorial describe about Raspberry Pi board, Ultrasonic sensor, circuit design for sensing of
data, Python programming script with step by step interpretation. Finally procedure for creating a
channel in ThinSpeak for uploading our data and to read the uploaded data from a remote
desktop/mobile is also included in this tutorial.
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garnet type and hexagaonal type is given in this review. The most interesting applications in electronic
devices High frequency devices and in biotechnology are discussed. Since its discovery in 1950,
hexaferrite has an increasing degree of interest and is still growing exponentially. Hexaferrites are the
extremely important material both commercially and technologically and it accounts for the bulk of the
total magnetic materials manufactured globally. Hence the classification of Hexaferrite is discussed in
detail in this review.
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Administering anesthesia at a slight excess range may cause fatal effect to patient, so it is with the anesthetist to keep it in
safe limit. In past few years the death toll due to improper anesthesia administration has increased, so it is high time to
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SMART APP FOR PHYSICALLY CHALLENGED PEOPLE USING INTERNET OF THINGS
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SMART APP FOR PHYSICALLY CHALLENGED
PEOPLE USING INTERNET OF THINGS
Mrs.V.Saraswathi1
,R.Pavithra2
.
1
Assistant professor , 2
Final year student , Department of computer science
S.A.Engineering College, Chennai – 77.
ABSTRACT
In this paper, we provide the solution for physically challenged people like hearing impaired people .It is a
smart application works for the hearing impaired people. People with hearing loss have move through the
activities of daily living at home, at work and in business situations. People may face the difficulty in hearing
the environment sounds and identifying the sounds. Our main contribution for the hearing impaired people is
to make them understand the type of sounds which is useful to them. The conventional sound recognition
techniques are not directly applicable since the background noise and reverberations are high which leads to
low performance. A deep neural network which is capable of classifying and predicting the information from
unstructured data such as image, text or sounds that makes the machine to get the environmental sounds. In
this paper, a deep learning algorithm called CNN(convolution neural network) which classify the sound audio
clips. This model will results the accuracy of 80% which is higher than the conventional technique .It achieves
good results comparable to other approaches.
Keywords- deep learning; convolution neural network; feature extraction; sound recognition; sound event
classification.
I.INTRODUCTION
Sound plays a vital role in everyone’s life by
sharing the information with other people.
Hearing impaired people will feel difficult to
understand the sound with background
noise. For example, Whoopi Goldberg, a
comic writer with hearing loss discovered a
portable listening platform for children to
prevent from the hearing loss. Sound
recognition is the only solution which guide
the hearing impaired people to overcome the
struggles of hearing the sound.
This Smart app is used for physically
challenged people like deaf and dumb
people using internet of things and deep
learning algorithm.The main aim is to give
an alarm in emergency situation for
physically challenged people .Alarm is
nothing but it is a silent notification for the
user. For example, the deaf and dumb
people who is working in front of desktop or
personal computer, they may not be aware
of their surroundings and environment.
This smart app gives an alarm/notification to
the user through the desktop/personal
computer. If a fire accident happens, then
the fire alarm will be on, the application will
detect the fire alarm sound and give the
notification as fire alarm is detected. By
using this notification, the physically
challenged people will prevent themselves
from the emergency situation. The urban
sound 8K datasets is used .
The CNN algorithm will detect the sound
and then it will analyze the type of sound.
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After analyzing the sound, it will recognize
the sound and gives a notification to the
user. Within a given area, the system will be
able to detect the type of sound. It will get
the sound using hardware implementation
using Internet of Things. After getting the
sound based on deep learning, train the data
sets. So based on the dataset it will analyze
the type of sound and notify it to the user via
notification. It will produce accurate result.
II.METHODOLOGY
The detection and classification of sound is
a multilevel process: Sound dataset, Audio
preprocessing, Feature extraction, CNN
classification model, Hardware
implementation, Sound classification,
Notification.
Sound Datasets: In this paper the urban
sound 8K dataset is used .It contains 8732
recording samples with 10 classes of
different sound sources such as: dog bark,
car horn, siren etc.Most of the above sound
samples have duration of 5-6 seconds. But
some of the sound samples can be as short
as 3 seconds. The urbansound8K are
subdivided into 10 subgroups for 10 fold
cross validation. The 8732 sound excerpts
are cropped from a smaller number of longer
recordings using librosa and it can result in
optimistic results. The sub divided 10 folds
will avoid the issues and make the results
accurate. The urban sound dataset contains
.wav format files. To convert the .wav files
into matrix of numbers (10X10) matrix [10
sound files] using the python sound file
library.
Figure.1
Audio preprocessing:To represent audio
clip in .wav files the data need to be
preprocessed. For audio processing the
librosa library provide useful functionalities.
Using librosa, audio files are loaded into a
numpy array which consists of amplitudes of
the corresponding audio clip. Theses
amplitudes are called as sampling rate which
is usually 22050Hz or 44100Hz.After
loading the audio clip into an array,
noisiness should be removed. To suppress
the noise in the audio, spectral gating
algorithm is used which is implemented
using noise reduce python library. In
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resulting audio clip the leading and trailing
parts are trimmed to get the noise reduced
audio file.
Figure.2
Feature Extraction: In general, without
feature extraction, the audio data is not
understandable by the classification modal.
To make it understand extract the audio
features from the preprocessed audio
clips.The absolute values of Short Time
Fourier Transform (STFT) will be extracted
from each audio clip.
1. To calculate STFT, find the window size
of STFT using FFT window size.
2.According to the equation,
n_stft=n_fft/2+1where n_stft is short
fourier transform window size and n_fft is
fourier transform window size from which
STFT frequency binsf is calculated.
3. Consider t no of audio samples, f no of
frequency bins in the STFT, h is the
windows hop length and w is the window
length.
4. Number of windows is calculated using
1+ (t-w)/h.
5. For each window,the amplitude of
frequency bins ranges from 0 to sampling
_rate/2 which is stored as a 2D array.
6. This 2D array is normalized to get a
common loudness level.
CNN Classification Model:From the
feature extracted, the modal is trained to
classify the audio events. Hence CNN
classification modal is used. For
classification, convert the data into
spectrogram, for which librosa is utilized.
After plotting and building a spectrogram of
data, implement the two layer neural
network which consists of input layer and
output layer. The weights are defined by the
hidden layer.It is used for mapping between
the input and the output layer .The last layer
of the neural network is the softmax layer is
in the output layer from which the
probability distribution for the audio clip is
identified. This paper shows that CNN is
used to classify the sound clips to the greater
accuracy to predict the sound
Figure.3
Hardware Implementation: The hardware
implementation is used for getting the
external sound. The hardware consists of
raspberry pi3 and microphone.
Raspberry Pi3:A raspberry pi 3 is an
electronic board where it has the special
features of recording the particular sound
and stores it in memory card when the Wi-Fi
is off. If the Wi-Fi is on,it will store the data
in cloud. The raspberry pi gives the high
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level performance when it is compared to
arduino.
Sound classification: The sound is then
processed by the classification part of the
CNN algorithm and it will analyze the type
of sound and then it will notify to the user
via notification.
Notification:It will send the notification to
the user through desktop or personal
computer when particular sound is detected.
It will be useful for hearing impaired people.
III.LITERATURE SURVEY
There are different methods of the sound
classification using Arduino and various
machine learning techniques.
Arushi Singh,L.Ezhilarasi et al[1]have
proposed a system which uses sound sensors
to detect the sound and then transmit the
sound data. They focus on sound pollution
monitoring system with sensing the sound
using raspberry Pi . A raspberry Pi module
interacts with the sensors and processes the
sound data and sends the alert to the
application. It can detect and monitor sound
pollution levels using IOT which further
send a mail or SMS to the system. In future
work, they planned to implement this
concept in the method of machine learning.
Baker Fleurys et al [2] have proposed a
system to perform certain task by
recognizing the sound in home automation
system. The system will generate poor
recognition results, when the noisy sounds
mixed with the target sound due to
occurrence of the sound simultaneously. To
solve this problem, this paper produces a
framework. The framework consists of the
sound verification and the sound separation
techniques based on wireless based sensor
networks. The applications of Wireless
Sensor Network are home automation
system, security system, power
management.
L. Korhonen, J. Pakka have proposed the
health care for the aged persons. The
monitoring can be done using the
telecommunication in the hospitals to reduce
the cost of hospitalization and also to
improve the comfort of the patients in the
hospital. In this paper the sound is classified
and detected in a noisy environment using
sound surveillance. There are two stages:
one detects the sound and extract the sound
from a signal flow. The sound classification
is the second stage is to identify the
unknown sounds and then it will be
validated. The future aim is to find the
fusion between the classification and the
analysis of the sound in a medical
telemonitoring system.
Lin Goldman et al[4] have proposed this
system for sensing the human behavior
using microphone which reveals the key
information. The person’s behavior is
produced by the key information. The
microphone will be present in the modern
smart phones or the laptop or pc. The
approach used for sensing the sound is
supervised learning which is the part of the
machine learning. The problem in this
system is time consuming and it is restricted
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to the various types of sounds. it explored
the general sound classification without
using explicit supervised training in the
smartphone. The supervised techniques will
produce better results compared to the fully
supervised DS.
F.Pachet and D.Cazaly et al [5] have a
proposed the system for classification of
audio signals. The characterization shared
by its members is music genre. The
characterization related to the instrument,
structure of the rhythm and the music of the
harmonic content. The music genres are
explored in a hierarchy from the automatic
classification of the audio signals. The
timbral texture, rhythmic content and pitch
content are the three important feature sets
have been proposed. The audio classification
is done here. The techniques include in the
audio classification are music and non-
music sounds. The audio signals are
classified into the music, speech and
laughter.And it also detects the
environmental sounds .The melody
extraction is a hard problem which is not
solved for general audio using from
imperfect melody extraction algorithms. The
pattern recognition, sound recognition is
contained in the C++ server.
N.Morgan, G.Dahl et al [6] have proposed
the system for speech recognition using
convolution neural network and hybrid
neural network .Hidden Markov model is
used to increase the accuracy of speech
recognition. Some types of speech
variability is accommodated by the
convolution neural network structure. It will
recognize the speech alone and it is not
recognized in the phone. The CNN can be
pre trained to improve the performance of
the recognition. The speech is recognized in
the method of the speech datasets.
Y.Peng,C.Lin et al [7] have proposed the
system for sound event classification using
semi supervised learning. In this paper, they
mainly focus on sound classification in a
large datasets., manually labeling the sound
data is expensive, so the large amount of sound
data will be available to public. It makes use of
the semi supervised learning in the approach of
the sound analysis. The future work will
focus on large unlabeled datasets to detect,
analyze and to classify what the sound is.
B.Najali,N.Noury etal [8] has proposed the
system for flats to recognize the sound and
speech. They placed eight microphones to
detect the sound which is trained the
environmental sounds. it will automatically
analyze and sort the different types of
sounds recorded in the flat. This paper
produces a complete sound and speech
recognition using unsupervised learning real
time conditions. After testing the event, it
will produce the results for sound
recognition is good and produce the accurate
results.
Y. LeCun, L. Bottou, Y. Bengio et al [9]
have proposed this for environmental sound
classification using convolution neural
network. Based on the 3 public data sets of
environmental and urban sounds are
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evaluated and produce the accuracy of the
sound. For significant progress in numerous
pattern recognition tasks, convolution neural
networks are used. The size of the datasets
influences the performances of the
supervised deep model. Increase in the size
of the dataset will improve the performance
of the trained models. it will detect the
environmental sound using machine learning
algorithm which uses convolution neural
network.
J. G. Ryan and R. A. Goubran et al [10]
have proposed a system for detecting
different type of sounds in a given area and
determining both the location and type of
the sound. For nonspeech audio segments,
additional features are computed to perform
audio classification, which determines the
nature of the sound (e.g., wind noise,
closing, footsteps ,door opening or closing,
fan noise).it is capable of working in a
signal to noise ratio (SNR) and degradation
environment is done by using speech/non
speech algorithm.This paper proposed a
security monitoring instrument that can
classify and detect the nature and location of
different sounds in a room.
IV.CONCLUSION AND FUTURE
WORK
A summary of the performance of the sound
detection and classifications of sound in the
system is evaluated. From the smart web
application for physically challenged people,
the sound event classification and detection
is proposed using internet of things and
machine learning algorithm.
In future work, this web application can be
made as a mobile application. Because
compared to web app, usage of mobile app
is more and it will work efficiently in mobile
application and it can also be done using
various deep learning algorithm.
V.REFERENCES
[1]Arnab Kumar Saha1, Sachet Sircar2,
Priyasha Chatterjee3, Souvik Dutta4,
Anwesha Mitra4,Aiswarya Chatterjee4,
Soummyo Priyo Chattopadhyay1, Himadri
Nath Saha1.,2018,”A Raspberry Pi
Controlled Cloud Based Air and Sound
Pollution Monitoring System with
Temperature and Humidity Sensing”., in
IEEE transaction paper.
[2]Jia-Ching Wang, Chang-Hong Lin,
Ernestasia Siahaan, Bo-Wei Chen, and
Hsiang-Lung Chuang.,2014,”Mixed Sound
Event Verification on Wireless Sensor
Network for Home Automation”., in IEEE
transactions on industrial informatics,vol.10.
[3]Dan Istrate, Eric Castelli, Michel Vacher,
Laurent Besacier, and Jean-Francois
Serignat.,2006.,”Information Extraction
From Sound for Medical Telemonitoring”.,
in IEEE transactions on information
technology in biomedicine,vol,10.
[4]Daniel Kelly and Brian Caulfield,
2015.”Pervasive Sound Sensing: A Weakly
Supervised Training Approach”, in IEEE
transactions on cybernetics.
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[5]George Tzanetakis, and Perry Cook.,
2002.”Musical Genre Classification of
Audio Signals”, in IEEE transactions on
speech and audio processing, vol.10.
[6]Osama Abdel-Hamid, Abdel-rahman
Mohamed, Hui Jiang, Li Deng, Gerald Penn,
and Dong Yu.,2014.,”Convolutional Neural
Networks for Speech Recognition”.,in
IEEE/ACM transactions on audio,speech
andlanguageprocessing,vol.22.,
[7]Zixing Zhang and Bjorn Schuller.,
2012.”Semi-
Supervisedlearninghelpsinsound event
classification”, in IEEEProc. Int. Conf
acoustics, speech, signalprocessing
(ICASSP)
[8]A. Fleury, N. Noury, M. Vacher, H.
Glasson and J.-F. Serignat, 2010.,”Sound
and Speech Detection and Classification in a
Health Smart Home”, in IEEE.
[9]Karol J. Piczak., 2015.”Environmental-
sound classification with convolutional
neural networks “ IEEE International
Workshop on Machine Learning for Signal
Processing.
[10]Ahmad R. Abu-El-Quran,Rafik A.
Goubran, and Adrian D. C.
Chan.,2006.,”Security Monitoring Using
Microphone Arrays and Audio
Classification”in IEEE Transactions On
Instrumentation And Measurement, Vol. 55