Android Best Titles – 2014 -2015

1. Mobiflage: Deniable Storage Encryption for Mobile Devices

2. Domain specific search of nearest hospital and Healthcare Management System

3. Personal emergency notification application design for mobile devices

4. Using Smart-Phones and Floor Plans for Indoor Location Tracking

5. An Approach for Object Detection in Android Device

6. A new tool for lightweight encryption on android

7. Hand Gesture Recognition Using an Android Device

8. User behavior based automatically navigation system on Android platform

9. Android "Health-Dr." Application for Synchronous Information Sharing

10. Establishing an alternative communication network in disaster situations using smart

devices

11. Position-aware activity recognition on mobile phones

12. Sober-Drive: A Smartphone-assisted drowsy driving detection system

Abstracts

1. Mobiflage: Deniable Storage Encryption for Mobile Devices

Data confidentiality can be effectively preserved through encryption. In certain situations, this is

inadequate, as users may be coerced into disclosing their decryption keys. Steganographic

techniques and deniable encryption algorithms have been devised to hide the very existence of

encrypted data. We examine the feasibility and efficacy of deniable encryption for mobile

devices. To address obstacles that can compromise plausibly deniable encryption (PDE) in a

mobile environment, we design a system called Mobiflage. Mobiflage enables PDE on mobile

devices by hiding encrypted volumes within random data in a devices free storage space. We

leverage lessons learned from deniable encryption in the desktop environment, and design new

countermeasures for threats specific to mobile systems. We provide two implementations for the

Android OS, to assess the feasibility and performance of Mobiflage on different hardware

profiles. MF-SD is designed for use on devices with FAT32 removable SD cards. Our MF-MTP

variant supports devices that instead share a single internal partition for both apps and user

accessible data. MF-MTP leverages certain Ext4 file system mechanisms and uses an adjusted

data-block allocator. These new techniques for soring hidden volumes in Ext4 file systems can

also be applied to other file systems to enable deniable encryption for desktop OSes and other

mobile platforms.

2. Domain specific search of nearest hospital and Healthcare Management System

Developed and developing countries have recognized the importance of Electronic Health  

Record in Healthcare Management System. Emergency Medical System (EMS) is a

revolutionary approach to emergency medical treatment in some medical emergency. It also

describes a mobile system that enables electronic healthcare data storage, update and retrieval

using Cloud Computing. It observed that people in unknown area are in severe danger if they

don't able to find hospital quickly. In emergency case a single minute counts so it is very

important that automatic applications must be used for decision making, maintain up to date

status of the hospital. Saving the time which can be save life of the patient. When the doctor or

family receives the alarm message, they can immediately take measures to rescue the user. It can

also manage the health record of the user. The user can take online medical to send their physical

condition and then get prescription from doctor who will send the prescription on the user's

phone. The proposed system locates nearest available hospital, contacts its ambulance

emergency system, accesses a Electronic Health Record of emergency patient that can critically

assist in pre-hospital treatments. The system will identify availability of the nearest available

specialized hospital all through EMS server which provides continuous information about the

incoming patient to the hospital. This paper proposes Android Based Tracking for EMS

(Emergency Medical System) on cloud.

3. Personal emergency notification application design for mobile devices

In most recent years, many interesting applications for mobile devices are designed to improve

our living quality and deal with house care issues under Android framework. In this paper, an

emergency notification application for mobile devices will be designed using a Freeware, named

APP Inventor. In the application, the position function of GPS and an easy used interface capable

for sending emergency notification messages or phone calls are included.

4. Using Smart-Phones and Floor Plans for Indoor Location Tracking

We implement pedestrian dead reckoning (PDR) for indoor localization. With a waist-

mounted PDR based system on a smart-phone, we estimate the user's step length that utilizes the

height change of the waist based on the Pythagorean Theorem. We propose a zero velocity

update (ZUPT) method to address sensor drift error: Simple harmonic motion and a low-pass

filtering mechanism combined with the analysis of gait characteristics. This method does not

require training to develop the step length model. Exploiting the geometric similarity between

the user trajectory and the floor map, our map matching algorithm includes three different filters

to calibrate the direction errors from the gyro usingbuilding floor plans. A sliding-window-based

algorithm detects corners. The system achieved 98% accuracy in estimating user walking

distance with a waist-mounted phone and 97% accuracy when the phone is in the user's pocket.

ZUPT improves sensor drift error (the accuracy drops from 98% to 84% without ZUPT) using 8

Hz as the cut-off frequency to filter out sensor noise. Corner length impacted the corner detection

algorithm. In our experiments, the overall location error is about 0.48 meter.

5. An Approach for Object Detection in Android Device

Object detection is a computer technology related to computer vision and image processing that

deals with detecting instances of semantic objects of a certain class in digital images and videos.

An attempt is made in this study to detect and extract objects in an image implemented

on android platform. Color images are converted to binary  images using the thresholding

technique. Morphological opening and closing filters are used in sequence for object detection.

Contour based learning techniques are adopted for drawing contours of the objects detected. In

the process objects are extracted and stored in an array for further analysis. OpenCV functions

are used to implement these algorithms on android.

6. A new tool for lightweight encryption on android

Theft or loss of a mobile device could be an information security risk as it can result in loss

of con fidential personal data. Traditional cryptographic algorithms are not suitable for resource

constrained and handheld devices. In this paper, we have developed an efficient and user friendly

tool called “NCRYPT” on Android platform. “NCRYPT” application is used to secure the data

at rest on Android thus making it inaccessible to unauthorized users. It is based on lightweight

encryption scheme i.e. Hummingbird-2. The application provides secure storage by making use

of password based authentication so that an adversary cannot access the confidential data stored

on the mobile device. The cryptographic key is derived through the password based key

generation method PBKDF2 from the standard SUN JCE cryptographic provider. Various tools

for encryption are available in the market which are based on AES or DES encryption schemes.

Ihe reported tool is based on Hummingbird-2 and is faster than most of the other existing

schemes. It is also resistant to most of attacks applicable to Block and Stream Ciphers.

Hummingbird-2 has been coded in C language and embedded in Android platform with the help

of JNI (Java Native Interface) for faster execution. This application provides choice for en

crypting the entire data on SD card or selective files on the smart phone and protect p ersonal or

confidential information available in such devices.

7. Hand Gesture Recognition Using an Android Device

In the field of image processing it is very interesting to recognize the human gesture for

general life applications. Gesture recognition is a growing field of research among various

human computer interactions, hand gesture recognition is very popular for interacting between

human and machines. It is nonverbal way of communication and this research area is full of

innovative approaches. This paper aims at recognizing 40 basic hand gestures. The main

features used are centroid in the hand, presence of thumb and number of peaks in

the hand gesture. That is the algorithm is based on shape based features by keeping in mind that

shape of human hand is same for all human beings except in some situations.

The recognition approach used in this paper is artificial neural network among back propagation

algorithm. This approach can be adapted to real time system very easily. In this paper for image

acquisition android camera is used, after that frames are send to the server and edge detection of

the video is done which is followed by thinning that reduce the noise, tokens are being created

from thinning image after tokens are fetched. The paper briefly describes the schemes of

capturing the image from android device, image detection, processing the image to recognize

the gestures as well as few results.

8. User behavior based automatically navigation system on Android platform

Nowadays, navigation applications in smartphones are widely used in our daily lives. But

the problem existing in using the applications is that a lot of operations between users and

smartphones are needed, such as destination setting, options setting and zooming in/out.

Potential dangers may bring to theusers when they are walking on the street or especially driving.

In this paper, we study providing an automatical navigation system, in which the number

of users' operations is largely reduced. Thenavigation system can automatically predict user's

future possible destinations and routes without any operation from users. The prediction is

performed by analyzing both user's current position and historical tracing data. We implement

the proposed system on the Android platform. The experimental results show that the application

works effectively to provide anticipated routes and destinations for a single user.

9. Android "Health-Dr." Application for Synchronous Information Sharing

Android "Health-DR." is innovative idea for ambulatory appliances. In rapid developing

technology, we are providing "Health-DR." application for the insurance agent, dispensary,

patients, physician, annals management (security) for annals. So principally, the ample of record

are maintain in to the hospitals. The application just needs to be installed in the customer site

with IT environment. Main purpose of ourapplication is to provide the healthy environment to

the patient. Our cream focus is on the "Health-DR."application meet to the patient regiment. For

the personal use of member, we provide authentication service strategy for "Health-

DR." application. Prospective strategy includes: Professional Authentications (User

Authentication) by doctor to the patient, actuary and dispensary. Remote access is available to

the medical annals, doctor affability and patient affability. "Health-DR." provides expertness

anytime and anywhere. The application is middleware to isolate the information from affability

management, client discovery and transit of database. Annotations of records are kept in the

bibliography. Mainly, this paper focuses on the conversion of E-Health application with flexible

surroundings.

10. Establishing an alternative communication network in disaster situations using

smart devices

This study aims to set up an alternative communication network which enables rescue crew

to communicate with each other and disaster victims in case of a cellular network breakdown or

overload in a natural disaster such as earthquake or storm. The communication network is

created viaestablishing mesh network by using Wi-fi interface of smart devices.

Commonly used smart phones with Android operating systems are preferred as smart devices. A

“push to talk” appliction is developed on Android. Open source software MANET Manager

framework is used for creating mesh network. A series of tests on Android devices and

computers are applied by creating mesh network with a softwareusing OLSR (Optimized Link

State Routing) routing protocol. As a result of the tests, communicationamong devices is

succeeded.

11. Position-aware activity recognition on mobile phones

Activity recognition (AR) or in other words context recognition is an active area of research

in the domain of pervasive and mobile computing that has direct applications about life quality

and health  of the users. Related studies aim to classify different daily human activities with

high accuracy rates using various types of sensors. Becoming a substantial part in our daily lives

with their sensing capabilities, smartphones are now feasible platforms that enable people to

make use of AR technologies without being obliged to use or wear some extra devices. However,

due to the fact that users carry these devices at different positions, such as in the pocket or in the

bag, it becomes a challenging task to attain accurate results by directly used classification

models. In this paper, we focus on phone positionuncertainty problem and compare the

classification results with position independent and positiondependent classification models.

12. Sober-Drive: A Smartphone-assisted drowsy driving detection system

Drowsy driving, a combination of sleepiness and driving, has become a worldwide problem

that often leads to tragic accidents and outcomes. Existing research findings have shown that the

percentage of closure of eyelid (a.k.a PERCLOS) is an effective indicator to evaluate the driver's

drowsiness. We present the Sober-Drive system, which leverages PERCLOS for on-

vehicle drowsy driving detectionusing smart phones. Specifically, Sober-Drive is built upon a

number of indicators that are discrete-approximated from PERCLOS, blink time and blink rate,

and it exploits the Neural Network to classify the eye “open/close” states. We developed

a Sober-Drive prototype on Android smart phones, and we conducted extensive real-world

experiments to evaluate its performance, the results of which show thatSober-Drive has a

high detection rate of more than 90% for drowsy driving behaviors.