GSM And IoT Based Smart Traffic System With Geofencing | Author : Ghouri , Malahim , Fatima1 ,Tayyab , Shakir | Abstract | Full Text | Abstract :This project is aimed at resolving severe traffic
congestion in most cities across the world by using latest
technologies. The world is heading towards IoT and shifting
daily routine manual processes to automatic systems. Current
traffic control system is based on fixed timer which becomes one
of the main reasons of transport blockage. In order to overcome
this problem, a framework has been designed to introduce the
concept of smart traffic system which includes Internet of
Things. The road side sensors attached to the Arduino Mega
send information to the cloud using NodeMCU where decision
is taken based on density, hence involving cloud computation to
turn a particular signal green. Moreover, we have also dealt
with emergency vehicles which bears the facility of turning
signal green using either RFID system or GSM based mobile.
Sound sensors are placed to confirm that the signal return to
normal condition once the emergency vehicle has crossed the
signal. Lastly, a geofencing based marketing app called
“Brando” has been designed using android studio to provide
location-based services from the nearest stations like shopping
malls to the people on road on their respective mobile phones |
| Design And Development Of Smart Parking Management System | Author : Arshad , Abdul Rehman , Ali , Syed Saad Azhar | Abstract | Full Text | Abstract :The parking systems in the modern age are under
tremendous stress as the number of vehicles on the roads are
increasing every year. Due to this increase, the current parking
lots do not suffice which leads to people driving for parking spaces thus wasting valuable time and adding to the greenhouse emissions. Therefore, new efficient and innovative solutions need to be developed which meets the ever- increasing demand for parking spaces and be as environmentally friendly as possible. The solution devised in this project is an enhancement of the current parking system with an integrated mobile application which allow drivers to remotely monitor parking lots, make reservation for a spot prior to visiting the parking lot and make in app payments for the parking services. This reduces the time spent in looking for parking spots as well as reduces the unnecessary carbon emissions while offering a practical and seamless parking experience to the users. |
| SHIFAYAAB – Centralized Platform For Vaccination Program | Author : Khizar Hayat , Mobeen Nazar , Taimoor Khalid , Wissam Amin | Abstract | Full Text | Abstract :Vaccinations are very essential for the
prevention of harmful diseases. However, the implementation
rate of vaccination varies in different parts of the world. Many
countries struggle to achieve the maximum immunization ratio
due to their vaccination practices and methodologies. However,
the authors have developed a solution to strengthen the
vaccination procedure. SHIFAYAAB, Proposed Methodology
in this paper provides a centralized platform for different
healthcare organizations and hospitals, working on various
vaccination programs. The idea is to collectively provide a
centralized database for the vaccination programs by
integrating the platform with the healthcare organizations and
hospitals, to enhance and improve the vaccination procedure
for the workers as well as the public. SHIFAYAAB proposes
automation of the vaccination procedure by replacing the old
school vaccine schedule card-reports with autonomous systemgenerated microplans. It will assemble the vaccination records
and provide a user-friendly platform for the vaccinators to
carry out the vaccination process. It will also provide children
parents a platform to keep track of their vaccination progress
by monitoring their microplan along with regular notification
reminders from the platform. |
| Review Of Security Issues In Internet Of Things (IoT) | Author : Imran, Syed Mubashir Ali, Muhammad Alam, Mazliham Mohd Su’ud | Abstract | Full Text | Abstract :It is brief according to the topic that it will focus
on IoT based security issues. This study will focus on
rigorous literature review which will provides us
trustworthy path to satisfy the industry need. In curtail IoT
is not just about interconnecting embedded devices or
gadgets to the Internet, however, it is also fast and
continuously growing to improve the ease or satisfaction of
life. The motive of IoT services is to connect the entire globe
through sensors. This study reviews the IoT methodologies
in the light of qualitative research. The data analysis and
synthesis focus over the last three years (2018 to 2020)
which are based on the PRISMA block diagram for
understanding. The review identifies the IoT privacy and
security issues from a different perspective and also finds
out which security issue is mostly discussed in the last few
years which elaborated as a basis for further research.
After a review of this paper, we can easily understand the
different problem faces of IoT devices with the help of
comparative analysis using summarize tables and graphical
representation of IoT in context of the privacy and security
challenges and issues face of IoT devices. After vigorous
survey, it is clear that in future most of the paper will
discuss data security and privacy, confidentiality, and
authenticity. |
| Interactive Automation of COVID-19 Classification through X-Ray Images using Machine Learning | Author : Ashura binti Hasmadi, Mehak Maqbool Memon, Manzoor Ahmed Hashmani | Abstract | Full Text | Abstract :Machine learning had given many
benefits to the humankind by implementing technology on
the daily human lives. To add, when the pandemic COVID19 hits Earth globally in early 2020, mankind is challenged
with the sudden emergence of the virus that costed many
lives. With the virus spreading fast, it has become a
challenge towards medical experts to keep their
environment clean from the virus. Scientists and medical
experts raced to find a cure and plausible methods to avoid
the virus from spreading, ranging from lockdowns to
standard operating procedures on daily routines. Studies
have also shown that geographical factors in the rural area
becomes a great challenge to experts on providing medical
attention towards the community that had been infected in
the rural areas. Fortunately, with the help of advanced
current technology, scientists and medical experts are able
to counter these problems. In this study, an experimental
model with an accuracy of 87% is used, and the application
to a web server is used via Python and Flask. The accuracy
is achieved by adjusting batch sizes and implementing
image augmentation using Keras’ ImageDataGenerator
feature. Therefore, this project focuses on utilizing
machine learning to classify COVID-19 patients through
X-ray images on a web server, which could further
improve the accessibility for humanity to seek for medical
attention. |
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