Payments for Outsourced Computations Android

Payments for Outsourced Computations

ABSTRACT:

With the recent advent of cloud computing, the concept of outsourcing computations, initiated by volunteer computing efforts, is being revamped. While the two paradigms differ in several dimensions, they also share challenges, stemming from the lack of trust between outsourcers and workers. In this work, we propose a unifying trust framework, where correct participation is financially rewarded: neither participant is trusted, yet outsourced computations are efficiently verified and validly remunerated. We propose three solutions for this problem, relying on an offline bank to generate and redeem payments; the bank is oblivious to interactions between outsourcers and workers. We propose several attacks that can be launched against our framework and study the effectiveness of our solutions. We implemented our most secure solution and our experiments show that it is efficient: the bank can perform hundreds of payment transactions per second and the overheads imposed on outsourcers and workers are negligible.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

In the existing system, Motivated by the ability of computer owners to donate CPU resources, volunteer computing takes advantage of the parallelizable nature of several large compute problems to distribute jobs to available computers over the internet.

In Existing system the problem of existing outsourcing computations in distributed environments has several security challenges. These challenges stem from the lack of trust between the outsourcer and a worker. Previous work has extensively considered one side of the trust problem – the efficient verification of the completion of the outsourced computation. We believe this to be the first work that simultaneously addresses the other side of trust – ensuring valid remuneration for the work. Outsourcers have computing jobs they cannot complete in a timely fashion, whereas workers are willing to spend CPU cycles to run parts of such jobs. Outsourcers do not trust the workers to correctly perform computations and workers do not trust outsourcers to pay for completed jobs. Motivated by the ability of computer owners is to donate CPU resources and volunteer computing takes advantage of the parallelizable nature of several large compute problems to distribute jobs to available computers over the internet.

DISADVANTAGES OF EXISTING SYSTEM:

  • Main problem is that address the lack of trust of outsourcers on workers, the lack of trust of a worker in the outsourcer is not addressed.
  • Workers do not have any verification process. So malicious outsourcer enter into the process.
  • Sometimes the intruders make misuses the outsourcing process.

PROPOSED SYSTEM:

We propose a unifying trust framework, where correct participation is financially rewarded: neither participant is trusted, yet outsourced computations are efficiently verified and validly remunerated.

We propose solutions that address both issues of trust. In our proposed system we introduce payment outsourced scheme for outsourcing computation that is only based on traditional electronic cash systems. To avoid the problem in an existing system, we use the following three solutions are,

In our first solution, it requires outsourcer to split the key used to obfuscate the payment and hides the sub keys into pre computed, randomly chosen parts of the job. The worker is entitled to a probabilistic verification of the payment received before beginning the computation. However, a malicious outsourcer that generates a single incorrect subkey may pass the verification step but prevent an honest worker from recovering the payment. In our second solution, outsourcer uses threshold sharing to divide the payment into multiple shares and obfuscates a randomly chosen subset of the shares with solutions to parts of the job. The worker needs to retrieve only a subset of the shares in order to reconstruct the payment. This significantly improves the worker’s chance of retrieving the payment even in the presence of a malicious outsourcer generating incorrect shares. However, this solution provides the worker with an unfair advantage in recovering the payment before completing the job: fewer shares need to be discovered. In our third solution, we use exact secret sharing to compute shares of the payment token—all the shares are needed to reconstruct the payment. Instead of generating a single ringer set, outsourcer generates a ringer set for each payment share and uses a function of the ringer set to “hide” the share. Worker and outsourcer run a verification protocol, where all but one share are revealed and the correctness of the last share is proved in zero knowledge.

ADVANTAGES OF PROPOSED SYSTEM: 

  • It improves the worker’s chance of retrieving the payment even in the presence of a malicious outsourcer generating incorrect shares.
  • This solution provides the worker with an unfair advantage in recovering the payment before completing the job: fewer shares need to be discovered.
  • It provides the full trust to the service provider (worker) and Outsourcers (outsourcer).

ALGORITHM AND TECHNIQUES:

Symmetric key algorithm:

            Symmetric-key algorithms are a class of algorithms for cryptography that use the same cryptographic keys for both encryption of plaintext and decryption of cipher text. The keys may be identical or there may be a simple transformation to go between the two keys. The keys, in practice, represent a shared secret between two or more parties that can be used to maintain a private information link. This requirement that both parties have access to the secret key is one of the main drawbacks of symmetric key encryption, in comparison to public-key encryption.

Secret sharing techniques:

          Secret sharing techniques refers to method for distributing a secret amongst a group of participants, each of whom is allocated a share of the secret. The secret can be reconstructed only when a sufficient number, of possibly different types, of shares are combined together; individual shares are of no use on their own. Secret sharing schemes are ideal for storing information that is highly sensitive and highly important. Examples include: encryption keys, missile launch codes, and numbered bank accounts. Each of these pieces of information must be kept highly confidential, as their exposure could be disastrous; however, it is also critical that they not be lost. Traditional methods for encryption are ill-suited for simultaneously achieving high levels of confidentiality and reliability. This is because when storing the encryption key, one must choose between keeping a single copy of the key in one location for maximum secrecy, and keeping multiple copies of the key in different locations for greater reliability. Increasing reliability of the key by storing multiple copies lowers confidentiality by creating additional attack vectors; there are more opportunities for a copy to fall into the wrong hands. Secret sharing schemes address this problem, and allow arbitrarily high levels of confidentiality and reliability to be achieved.

MODULES:

  • Initiate process
    • Business login
    • Personal login
  • Banking process
  • Payment process
  • Verification Process
  • Manage files process

MODULES DESCRIPTION 

INITIATE PROCESS:

          Initiate process is the first step to enter the payment outsourcing process. Initiate process is the Login process. Before entering the account the Outsourcer need to register their personal details. In this step the registration process contains the two different types of registration for Outsourcer convenient. These processes are Business login and Personal Login. Business login is the process to register the details of user who needs to make the business in the online purpose. In this process the Outsourcers should enter the all personal details and also need to enter the storage capacity as their process need. If the Business process required storage capacity of 5GB, they need to pay 20$, and etc. If the personal login required storage capacity of 2 GB, they no need to pay money. In this register process, after submitting this register key (code) will send to the particular user’s mail id. The register key (code) is used for authentication purpose.

BANKING PROCESS:

          Banking Process contains the process of manage the banking details. Before enter the banking process, the Outsourcer need to submit the details about him. Details of the banking needs Name, Address, Country, State, Area, Pin code, Phone number and Email id. After the submitting the account creation of bank, the key and credit card number will send to his own mail id. This key provides the more authentications to both the Outsourcers and servers. And then the Outsourcer enters into the bank process using name and code which are sent his mail id. Banking process have the following items are, Account details, Deposit, with draw and logout. In account detail process, it has the items of Account number and code (generated in their own mail id). After entering the details, the process used to view the account process. In deposit process, it has the items of Enter amount, Enter code and Account number. After entering the details amount will deposit in their account. In withdraw process; it has the items of Enter amount, Enter code and Account number. After entering the details amount will withdraw by the Outsourcer.

PAYMENT PROCESS:

          Payment processes have the process of Mail ID, Card Number, Code and Storage cost. Before entering the payment process the process needs the banking process. Because the payment process need the storage cost, so the amount form the Outsourcer is get from the bank through the banking details. After the banking process is completed the Outsourcer enters the payment process. Verification of the payment based on the shape verification and code verification. If wrong shape is draw means the process not entered into the account. After the submitting of correct shape, then only the process enters into the payment account.

VERIFICATION PROCESS:

          Main process of the payment for outsourced computation is Authentication. For Authentication purpose the process should perform the verification step of the Outsourcer. This process has the two types of verification are Code verification and Shape verification. Code verification are the process, that done in after the submitting the bank process and the payment account process. The code or key of the process is send to our own mail id (as we providing in the personal details).  After verifying of the code, then only the next process is done. Shape verification is the process of verification done by the shape model. Outsourcer need to draw the shape that is given in the login page. After completing the correct shape, then only the Outsourcer get inside the process.

MANAGE FILES PROCESS:

          Managing file process is the process that is maintained in the payment process. In this process, the process maintains the item sets of Home, Account Details, File Folders and Logout process. Home processes have the process of Upload, New folder and delete file options. Upload file has the elements that are secure file and zip file for securing the uploaded data. Secure files used for Encrypt and Decrypt the data files. Zip file used for compressing the data. Account detail process provides the personal details of the Outsourcer and it also provides the date of expiry. File Folder process used for searching the files using file name, file size, folder name and available size. This process also used for download the file data.

SYSTEM ARCHITECTURE:

                                                    

SYSTEM MODELS

HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard

Mobile                            :    ANDROID MOBILE

SOFTWARE REQUIREMENT

Operating System:  Android

Language           :  ANDROID SDK 2.3

Documentation   :    Ms-Office

REFERENCE:

Bogdan Carbunar and Mahesh V. Tripunitara, “Payments for Outsourced Computations”, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL.23, NO.2, FEBRUARY 2012.

Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute-based Encryption

Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute-based Encryption

ABSTRACT:

Personal health record (PHR) is an emerging patient-centric model of health information exchange, which is often outsourced to be stored at a third party, such as cloud providers. However, there have been wide privacy concerns as personal health information could be exposed to those third party servers and to unauthorized parties. To assure the patients’ control over access to their own PHRs, it is a promising method to encrypt the PHRs before outsourcing. Yet, issues such as risks of privacy exposure, scalability in key management, flexible access and efficient user revocation, have remained the most important challenges toward achieving fine-grained, cryptographically enforced data access control. In this paper, we propose a novel patient-centric framework and a suite of mechanisms for data access control to PHRs stored in semi-trusted servers. To achieve fine-grained and scalable data access control for PHRs, we leverage attribute based encryption (ABE) techniques to encrypt each patient’s PHR file. Different from previous works in secure data outsourcing, we focus on the multiple data owner scenario, and divide the users in the PHR system into multiple security domains that greatly reduces the key management complexity for owners and users. A high degree of patient privacy is guaranteed simultaneously by exploiting multi-authority ABE. Our scheme also enables dynamic modification of access policies or file attributes, supports efficient on-demand user/attribute revocation and break-glass access under emergency scenarios. Extensive analytical and experimental results are presented which show the security, scalability and efficiency of our proposed scheme.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

ARCHITECTURE:

EXISTING SYSTEM:

A PHR service allows a patient to create, manage, and control her personal health data in one place through the web, which has made the storage, retrieval, and sharing of the the medical information more efficient. Especially, each patient is promised the full control of her medical records and can share her health data with a wide range of users, including healthcare providers, family members or friends. Due to the high cost of building and maintaining specialized data centers, many PHR services are outsourced to or provided by third-party service providers, for example, Microsoft HealthVault

While it is exciting to have convenient PHR services for everyone, there are many security and privacy risks which could impede its wide adoption. The main concern is about whether the patients could actually control the sharing of their sensitive personal health information (PHI), especially when they are stored on a third-party server which people may not fully trust. On the one hand, although there exist healthcare regulations such as HIPAA which is recently amended to incorporate business associates [4], cloud providers are usually not covered entities. On the other hand, due to the high value of the sensitive personal health information (PHI), the third-party storage servers are often the targets of various malicious behaviors which may lead to exposure of the PHI.

DISADVANTAGES OF EXISTING SYSTEM:

A Department of Veterans Affairs database containing sensitive PHI of 26.5 million military veterans, including their social security numbers and health problems was stolen by an employee who took the data home without authorization

PROPOSED SYSTEM:

A feasible and promising approach would be to encrypt the data before outsourcing. Basically, the PHR owner herself should decide how to encrypt her files and to allow which set of users to obtain access to each file. A PHR file should only be available to the users who are given the corresponding decryption key, while remain confidential to the rest of users. Furthermore, the patient shall always retain the right to not only grant, but also revoke access privileges when they feel it is necessary In this paper, we endeavor to study the patientcentric, secure sharing of PHRs stored on semi-trusted servers, and focus on addressing the complicated and challenging key management issues. In order to protect the personal health data stored on a semi-trusted server, we adopt attribute-based encryption (ABE) as the main encryption primitive. Using ABE, access policies are expressed based on the attributes of users or data, which enables a patient to selectively share her PHR among a set of users by encrypting the file under a set of attributes, without the need to know a complete list of users. The complexities per encryption, key generation and decryption are only linear with the number of attributes involved.

ADVANTAGESF OF PROPOSED SYSTEM:

To ensure patient-centric privacy control over their own PHRs, it is essential to have fine-grained data access control mechanisms that work with semi-trusted servers.

MODULES

  1. Registration
  2. Upload files
  3. ABE for Fine-grained Data Access Control
  4. Setup and Key Distribution

MODULES DESCRIPTION

Registration

In this module normal registration for the multiple users. There are multiple owners, multiple AAs, and multiple users. The attribute hierarchy of files – leaf nodes is atomic file categories while internal nodes are compound categories. Dark boxes are the categories that a PSD’s data reader have access to.

Two ABE systems are involved: for each PSD the revocable KP-ABE scheme is adopted for each PUD, our proposed revocable MA-ABE scheme.

  • PUD – public domains
  • PSD – personal domains
  • AA – attribute authority
  • MA-ABE –  multi-authority ABE
  • KP-ABE – key policy ABE

 Upload files

In this module, users upload their files with secure key probabilities. The owners upload ABE-encrypted PHR files to the server. Each owner’s PHR file encrypted both under a certain fine grained model.

ABE for Fine-grained Data Access Control

In this module ABE to realize fine-grained access control for outsourced data especially, there has been an increasing interest in applying ABE to secure electronic healthcare records (EHRs). An attribute-based infrastructure for EHR systems, where each patient’s EHR files are encrypted using a broadcast variant of CP-ABE that allows direct revocation. However, the cipher text length grows linearly with the number of un revoked users. In a variant of ABE that allows delegation of access rights is proposed for encrypted EHRs applied cipher text policy ABE (CP-ABE) to manage the sharing of PHRs, and introduced the concept of social/professional domains investigated using ABE to generate self-protecting EMRs, which can either be stored on cloud servers or cell phones so that EMR could be accessed when the health provider is offline.

Setup and Key Distribution

In this module the system first defines a common universe of data attributes shared by every PSD, such as “basic profile”, “medical history”, “allergies”, and “prescriptions”. An emergency attribute is also defined for break-glass access.

Each PHR owner’s client application generates its corresponding public/master keys. The public keys can be published via user’s profile in an online healthcare social-network (HSN)

There are two ways for distributing secret keys.

  • First, when first using the PHR service, a PHR owner can specify the access privilege of a data reader in her PSD, and let her application generate and distribute corresponding key to the latter, in a way resembling invitations in GoogleDoc.
  • Second, a reader in PSD could obtain the secret key by sending a request (indicating which types of files she wants to access) to the PHR owner via HSN, and the owner will grant her a subset of requested data types. Based on that, the policy engine of the application automatically derives an access structure, and runs keygen of KP-ABE to generate the user secret key that embeds her access structure.

SYSTEM MODELS

HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard

Mobile                            :    ANDROID MOBILE

SOFTWARE REQUIREMENT

Operating System:  Android

Language           :  ANDROID SDK 2.3

Documentation   :    Ms-Office

REFERENCE:

Ming Li, Shucheng Yu, Yao Zheng, Kui Ren, and Wenjing Lou, “Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute- based Encryption”, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, Vol. XX, No. XX, XX 2012.

The Three-Tier Security Scheme in Wireless Sensor Networks with Mobile Sinks Android

The Three-Tier Security Scheme in Wireless Sensor Networks with Mobile Sinks

ABSTRACT:

Mobile sinks (MSs) are vital in many wireless sensor network (WSN) applications for efficient data accumulation, localized sensor reprogramming, and for distinguishing and revoking compromised sensors. However, in sensor networks that make use of the existing key pre-distribution schemes for pair-wise key establishment and authentication between sensor nodes and mobile sinks, the employment of mobile sinks for data collection elevates a new security challenge: in the basic probabilistic and q-composite key pre-distribution schemes, an attacker can easily obtain a large number of keys by capturing a small fraction of nodes, and hence, can gain control of the network by deploying a replicated mobile sink preloaded with some compromised keys. This article describes a three-tier general framework that permits the use of any pair wise key pre-distribution scheme as its basic component. The new framework requires two separate key pools, one for the mobile sink to access the network, and one for pair wise key establishment between the sensors. To further reduce the damages caused by stationary access node replication attacks, we have strengthened the authentication mechanism between the sensor and the stationary access node in the proposed framework. Through detailed analysis, we show that our security framework has a higher network resilience to a mobile sink replication attack as compared to the polynomial pool-based scheme.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

ARCHITECTURE:

EXISTING SYSTEM:

  • The Existing Systems used various techniques such as:
    • Asymmetric key technique for the key exchange technique.
    • Probabilistic key predistribution scheme
    • Two key predistribution schemes
  • Although the above security approach makes the network more resilient to mobile sink replication attacks compared to the single polynomial pool-based key pre-distribution scheme, it is still vulnerable to stationary access node replication attacks. In these types of attacks, the attacker is able to launch a replication attack similar to the mobile sink replication attack. After a fraction of sensor nodes have been compromised by an adversary, captured static polynomials can be loaded into a replicated stationary access node that transmits the recorded mobile sink’s data request messages to trigger sensor nodes to send their aggregated data.
  • The problem of authentication and pair wise key establishment in sensor networks with MSs is still not solved in the face of mobile sink replication attacks.

DISADVANTAGES OF EXISTING SYSTEM:

For the basic probabilistic and q-composite key pre-distribution schemes, an attacker can easily obtain a large number of keys by capturing a small fraction of the network sensor nodes, making it possible for the attacker to take control of the entire network by deploying a replicated mobile sink, preloaded with some compromised keys to authenticate and then initiate data communication with any sensor node.

PROPOSED SYSTEM:

To address the above-mentioned problem, we have developed a general framework that permits the use of any pair wise key pre-distribution scheme as its basic component, to provide authentication and pair-wise key establishment between sensor nodes and MSs.

To facilitate the study of a new security technique, we first cultivated a general three-tier security framework for authentication and pair wise key establishment, based on the polynomial pool-based key predistribution scheme

To make the three-tier security scheme more robust against a stationary access node replication attack, we have strengthened the authentication mechanism between the stationary access nodes and sensor nodes using one-way hash chains algorithm [20] in conjunction with the static polynomial pool-based scheme [14]. Our analytical results indicate that the new security technique makes the network more resilient to both mobile sink replication attacks and stationary access nodes replication attacks compared to the single polynomial pool-based approach.

ADVANTAGES OF PROPOSED SYSTEM:

The proposed technique will substantially improve network resilience to mobile sink replication attacks compared to the single polynomial pool-based key pre distribution approach, as an attacker would have to compromise many more sensor nodes to launch a successful mobile sink replication attack.

MODULES:

  • Sensor Module
  • Access Pont Module
  • Mobile Sink Module
  • Pair-wise Key Establishment Scheme Module
  • Key Distribution scheme Module
  • Static and Mobile Polynomial Pre-distribution module
  • Key discovery

MODULE DESCRIPTION:

Sensor Module

We know that Wireless Sensor Networks (WSN) are  sensing, computing and communication infrastructure that are able to observe and respond to phenomena in the natural environment and in our physical and cyber infrastructure. The sensors themselves can range from small passive micro sensors to larger scale, controllable weather-sensing platforms.

 Access Point Module

In this module first we develop the access point module. In WSN, these access point module acts as an intermediate between the sensor node and sink node.

Mobile Sink Module

In this module first we develop the Mobile Sink Module, where the data are to be delivered or reached as destination.

 Pair-wise Key Establishment Scheme

A hybrid cryptosystem can be constructed using any two separate cryptosystems:

  • A key encapsulation scheme, which is a public-key cryptosystem, and
  • A data encapsulation scheme, which is a symmetric-key cryptosystem.

To encrypt a message addressed to Alice in a hybrid cryptosystem, Bob does the following:

  1. Obtains Alice’s public key.
  2. Generates a fresh symmetric key for the data encapsulation scheme.
  3. Encrypts the message under the data encapsulation scheme, using the symmetric key just generated.
  4. Encrypt the symmetric key under the key encapsulation scheme, using Alice’s public key.
  5. Send both of these encryptions to Alice.

To decrypt this hybrid ciphertext, Alice does the following:

  1. Uses her private key to decrypt the symmetric key contained in the key encapsulation segment.
  2. Uses this symmetric key to decrypt the message contained in the data encapsulation segment.

Key Distribution scheme Module

  • This protocol uses two separate key management schemes; one for group-wide and individual keys and another for sub-network key management.
  • The group-wide key is used for non-critical broadcast messages between The individual keys are used for secure communication between nodes creating a subnetwork and setting up a subnetwork key. The second key management scheme is creating and distributing the keys for the dynamically created subnetworks.
  • Securely distributing the keys for the subnetworks created by events within the sensor network is a non-trivial problem since the subnetworks may contain any arbitrary set of neighboring nodes. These nodes all must have a mechanism to securely communicate with each other to distribute the subnetwork key to all the subnetwork members.

Static and Mobile Polynomial Pre-distribution:

This module is performed before the nodes are deployed. A mobile polynomial pool and a static polynomial pool are generated along with the polynomial identifiers. All mobile sinks and stationary access nodes are randomly given. one polynomial from Mobile polynomial pool. The number of mobile polynomials in every mobile sink is more than the number of mobile polynomials in every stationary access node. This assures that a mobile node shares a common mobile polynomial with a stationary access node with high probability and reduces the number of compromised mobile polynomials when the stationary access nodes are captured. All sensor nodes and the preselected stationary access nodes randomly pick a subset of key from static pool.

Key discovery

This module is performed after the module Static and mobile polynomial pre distribution. In this module Key discovery between mobile node and stationary node , To establish a direct pair-wise key between sensor node and mobile sink, a sensor node needs to find a stationary access node in its neighborhood, such that, stationary access node can establish pair-wise keys with both mobile sink and sensor node. In other words, a stationary access node needs to establish pair-wise keys with both the mobile sink and the sensor node. It has to find a common mobile polynomial with the mobile sink and a common static polynomial with the sensor node.

SYSTEM MODELS

HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard

Mobile                            :    ANDROID MOBILE

SOFTWARE REQUIREMENT

  • Operating System: Android
  • Language :  ANDROID SDK 2.3
  • Documentation :    Ms-Office

REFERENCE:

Amar Rasheed and Rabi N. Mahapatra, “The Three-Tier Security Scheme in Wireless Sensor Networks with Mobile Sinks”, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 23, NO.5, MAY 2012.

SPOC A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emergency

SPOC A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emergency

ABSTRACT:

With the pervasiveness of smart phones and the advance of wireless body sensor networks (BSNs), mobile Healthcare (m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security and privacy preservation. In this paper, we propose a secure and privacy-preserving opportunistic computing framework, called SPOC, for m-Healthcare emergency. With SPOC, smart phone resources including computing power and energy can be opportunistically gathered to process the computing-intensive personal health information (PHI) during m-Healthcare emergency with minimal privacy disclosure. In specific, to leverage the PHI privacy disclosure and the high reliability of PHI process and transmission in m-Healthcare emergency, we introduce an efficient user-centric privacy access control in SPOC framework, which is based on an attribute-based access control and a new privacy-preserving scalar product computation (PPSPC) technique, and allows a medical user to decide who can participate in the opportunistic computing to assist in processing his overwhelming PHI data. Detailed security analysis shows that the proposed SPOC framework can efficiently achieve user-centric privacy access control in m-Healthcare emergency. In addition, performance evaluations via extensive simulations demonstrate the SPOC’s effectiveness in term of providing high reliable PHI process and transmission while minimizing the privacy disclosure during m-Healthcare emergency.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

ARCHITECTURE:

EXISTING SYSTEM

The study of opportunistic computing has gained the great interest from the research community recently.

The existing systems introduce the opportunistic computing paradigm in wireless sensor network to solve the problem of storing and executing an application that exceeds the memory resources available on a single sensor node. Especially, their solution is based on the idea of partitioning the application code into a number of opportunistically cooperating modules, and each node contributes to the execution of the original application by running a subset of the application tasks and providing service to the neighboring nodes.

Passarella et al. evaluate the performance of service execution in opportunistic computing. Specifically, they first abstract resources in pervasive computing as services, that are opportunistically contributed by providers and invoked by seekers. Then, they present a complete analytical model to depict the service invocation process between seekers and providers, and derive the optimal number of replicas to be spawned on encountered nodes, in order to minimize the execution time and optimize the computational and bandwidth resources used.

PROPOSED SYSTEM

In this paper, we propose a new secure and privacy preserving opportunistic computing framework, called SPOC, to address this challenge. With the proposed SPOC framework, each medical user in emergency can achieve the user-centric privacy access control to allow only those qualified helpers to participate in the opportunistic computing to balance the high-reliability of PHI process and minimizing PHI privacy disclosure in m-Healthcare emergency. Specifically, the main contributions of this paper are threefold. • First, we propose SPOC, a secure and privacy-preserving opportunistic computing framework for m-Healthcare emergency. With SPOC, the resources available on other opportunistically contacted medical users’ smartphones can be gathered together to deal with the computingintensive PHI process in emergency situation. Since the PHI will be disclosed during the process in opportunistic computing, to minimize the PHI privacy disclosure, SPOC introduces a user-centric two-phase privacy access control to only allow those medical users who have similar symptoms to participate in opportunistic computing. • Second, to achieve user-centric privacy access control in opportunistic computing, we present an efficient attributebased access control and a novel non-homomorphic encryption based privacy-preserving scalar product computation (PPSPC) protocol, where the attributed-based access control can help a medical user in emergency to identify other medical users, and PPSPC protocol can further control only those medical users who have similar symptoms to participate in the opportunistic computing while without directly revealing users’ symptoms. Note that, although PPSPC protocols have been well studied in privacy-preserving data mining, yet most of them are relying on time-consuming homomorphic encryption technique. To the best of our knowledge, our novel non-homomorphic encryption based PPSPC protocol is the most efficient one in terms of computational and communication overheads. • Third, to validate the effectiveness of the proposed SPOC framework in m-Healthcare emergency, we also develop a custom simulator built in Java. Extensive simulation results show that the proposed SPOC framework can help medical users to balance the high-reliability of PHI process and minimizing the PHI privacy disclosure in m-Healthcare emergency

Modules

  • Medical User Module
    • Register User
    • Emergency Call
    • Send Report
    • View Report
    • Settings
  • Trusted Authority Module

Modules Description:

Medical User:

In this module an application for Android smart phone is developed, to register the medical user, then send and view their heal reports.

User Registration

The user is prompt to register with trusted authority to send the report and view diagnosis, on the time of registration user need to give their personal information such as name, age, address, contact number, email id. And username, password to login and send the reports, User need to give the emergency contact number to call immediately in emergency situations.

Emergency Call

The user can call the emergency number by pressing a simple button, no need to open their dialer and entering the number or search the contacts and call the number, the user is prompt to give the emergency number to call at the time of registration, that number is called when the user in emergency situation by pressing a simple button.

Send Report

User periodically sends their health information (PHI) such as Pulse rate, Blood sugar, Blood pressure and Body temperature to the Trusted Authority. The values are compared with threshold values and status is given as Normal or Emergency.

View Report

User can view the report sent to the Trusted Authority and the diagnosis received from the trusted authority, then they can do the need full based on the diagnosis.

Settings

User has the options to update their personal information, username, password and emergency number when they needed.

Trusted Authority

This module is developed as PHP project, Trusted Authority can login in the web application running in the server and review all medical user PHI reports, time of the report and status, and have the options to filter by the medical user name to view the particular medical user report, then sent the diagnosis to the medical user based on their PHI status to their Smartphone application, The user can receive the diagnosis as the email in the address given at the time of registration, and can receive the report in SMS in the number given.

HARDWARE REQUIREMENT

  • CPU type          :    Intel Pentium 4
  • Clock speed :    0 GHz
  • Ram size :    512 MB
  • Hard disk capacity :    40 GB
  • Monitor type :    15 Inch color monitor
  • Keyboard type :     internet keyboard

SOFTWARE REQUIREMENT

  • Operating System: Android
  • Language :  ANDROID SDK 2.3
  • Back End :    SQLite
  • Documentation :    Ms-Office

REFERENCE:

Rongxing Lu, Xiaodong Lin, and Xuemin (Sherman) Shen, “SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emergency”, IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. XX, NO.XX, XX 2012.

Learn to Personalized Image Search from the Photo Sharing Websites

Learn to Personalized Image Search from the Photo Sharing Websites

ABSTRACT:

Increasingly developed social sharing websites, like Flickr and Youtube, allow users to create, share, annotate and comment medias. The large-scale user-generated meta-data not only facilitate users in sharing and organizing multimedia content, but provide useful information to improve media retrieval and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework simultaneously considering the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too sparse for topic modeling, we need to enrich users’ annotation pool before user-specific topic spaces construction. The proposed framework contains two components: 1) A Ranking based Multi-correlation Tensor Factorization model is proposed to perform annotation prediction, which is considered as users’ potential annotations for the images; 2) We introduce User-specific Topic Modeling to map the query relevance and user preference into the same user-specific topic space. For performance evaluation, two resources involved with users’ social activities are employed. Experiments on a large-scale Flickr dataset demonstrate the effectiveness of the proposed method.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

ARCHITECTURE:

The proposed framework contains two components:

1) A Ranking based Multi-correlation Tensor Factorization model is proposed to perform annotation prediction, which is considered as users’ potential annotations for the images;

2) We introduce User-specific Topic Modeling to map the query relevance and user preference into the same user-specific topic space. For performance evaluation, two resources involved with users’ social activities are employed. Experiments on a large scale Flickr dataset demonstrate the effectiveness of the proposed method.

EXISTING SYSTEM:

In Existing System, Users may have different intentions for the same query, e.g., searching for “jaguar” by a car fan has a completely different meaning from searching by an animal specialist. One solution to address these problems is personalized search, where user-specific information is considered to distinguish the exact intentions of the user queries and re-rank the list results. Given the large and growing importance of search engines, personalized search has the potential to significantly improve searching experience.

PROPOSED SYSTEM:

In Proposed System We propose a novel personalized image search framework by simultaneously considering user and query information. The user’s preferences over images under certain query are estimated by how probable he/she assigns the query-related tags to the images.

  • A ranking based tensor factorization model named RMTF is proposed to predict users’ annotations to the images.
  • To better represent the query-tag relationship, we build user-specific topics and map the queries as well as the users’ preferences onto the learned topic spaces.

MODULES:

  1. User-Specific Topic Modeling
  2. Personalized Image Search
  3. Ranking – Multi Correlation based

MODULES DESCRIPTION:

  1. User-Specific Topic Modeling

Users may have different intentions for the same query, e.g., searching for “jaguar” by a car fan has a completely different meaning from searching by an animal specialist. One solution to address these problems is personalized search, where user-specific information is considered to distinguish the exact intentions of the user queries and re-rank the list results. Given the large and growing importance of search engines, personalized search has the potential to significantly improve searching experience.

  1. Personalized Image Search

In the research community of personalized search, evaluation is not an easy task since relevance judgment can only be evaluated by the searchers themselves. The most widely accepted approach is user study, where participants are asked to judge the search results. Obviously this approach is very costly. In addition, a common problem for user study is that the results are likely to be biased as the participants know that they are being tested. Another extensively used approach is by user query logs or click through history. However, this needs a large-scale real search log, which is not available for most of the researchers.

Social sharing websites provide rich resources that can be exploited for personalized search evaluation. User’s social activities, such as rating, tagging and commenting, indicate the user’s interest and preference in a specific document. Recently, two types of such user feedback are utilized for personalized search evaluation. The first approach is to use social annotations. The main assumption behind is that the documents tagged by user with tag will be considered relevant for the personalized query. Another evaluation approach is proposed for personalized image search on Flickr, where the images marked Favorite by the user u are treated as relevant when u issues queries.

The two evaluation approaches have their pros and cons and supplement for each other.

  1. Ranking – Multi Correlation based

Photo sharing websites differentiate from other social tagging systems by its characteristic of self-tagging: most images are only tagged by their owners. The #tagger statistics for Flickr and the webpage tagging system Del.icio.us. We can see that in Flickr, 90% images have no more than 4 taggers and the average number of tagger for each image is about 1.9. However, the average tagger for each webpage in Del.icio.us is 6.1. The severe sparsity problem calls for external resources to enable information propagation. In addition to the ternary interrelations, we also collect multiple intra-relations among users, images and tags. We assume that two items with high affinities should be mapped close to each other in the learnt factor subspaces. In the following, we first introduce how to construct the tag affinity graph, and then incorporate them into the tensor factorization framework.

SYSTEM MODELS

HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard

SOFTWARE REQUIREMENT 

Operating System   :  Android

Language              :  ANDROID SDK 2.3

Back End                       :    SQLite

Documentation      :    Ms-Office

REFERENCE:

Jitao Sang, Changsheng Xu, Dongyuan Lu, “Learn to Personalized Image Search from the Photo Sharing Websites”, IEEE TRANSACTIONS ON MULTIMEDIA, VOL. X, NO. X, 2012.

Design and Implementation of Improved Authentication System for Android Smartphone Users

Design and Implementation of Improved Authentication System for Android Smartphone Users

ABSTRACT:

The devices most often used for IT services are changing from PCs and laptops to smart phones and tablets. These devices need to be small for increased portability. These technologies are convenient, but as the devices start to contain increasing amounts of important personal information, better security is required. Security systems are rapidly being developed, as well as solutions such as remote control systems. However, even with these solutions, major problems could still result after a mobile device is lost. In this thesis, we present our upgraded Lock Screen system, which is able to support authentication for the user’s convenience and provide a good security system for smart phones. We also suggest an upgraded authentication system for Android smart phones.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

ARCHITECTURE:

EXISTING SYSTEM:

Slide Lock: This is a Lock Screen provided by Android and IOS and it is a “touch–horizontal slide” form of screen. It does not serve as a security system and necessitates extra security applications.

Glass Lock: This is a Lock Screen based on the Android OS and is provided on Samsung devices. It works the same as a Slide Lock can be dragged in all directions. It is like putting a glass on the screen.

Keypad Lock: This scheme requires a four-digit password, so it provides key space from 0 to 9999. Repetitive input touching of the smartphone is required, presenting an inconvenience factor.

Pattern Lock: This is well matched with the user interface. There are nine dots on the screen, each of which can be touched and dragged one dot at a time (redundancy input is not available) to make a password. Accordingly, it provides approximately one million (= 9P4 + 9P5 + 9P6 + 9P7 + 9P8 + 9!) of key space. It reduces repetitive touching and provides for easy dragging. However, if users enter an easy pattern for convenience, there is weak security power; if users enter a more complicated pattern, the scheme will not be comfortable to use.

Finger Scan: Atrix smartphone, made by Motorola, supplies a finger scanning system, which provides both good convenience and good security without touch-dragging. Overlapping processes on the screen and low speed are the main problems in this system.

DISADVANTAGES OF EXISTING SYSTEM:

  • It does not serve as a security system and necessitates extra security applications.
  • Repetitive input touching of the smartphone is required, presenting an inconvenience factor.
  • If users enter an easy pattern for convenience, there is weak security power; if users enter a more complicated pattern, the scheme will not be comfortable to use.
  • Overlapping processes on the screen and low speed are the main problems

PROPOSED SYSTEM:

This Lock Screen is shown in Figure. Redundancy input (re-touching the circle) is allowed and when the circle is touched more than once, it changes color (maximum of seven times) so that the user can identify the correct input. In our demonstration video, we allowed 20 inputs and were able to make over one quadrillion passwords. In the Home Launcher, the Guest mode can be entered by shaking the mobile phone. In the Guest mode, there are a limited number of apps allowed along with the Dockbar, in which we cannot use the Appdrawer button; we can only use the buttons that are freed by the user’s setting.

ADVANTAGES OF PROPOSED SYSTEM:

The Lock Screen consists of activities, so it is included in the Home Launcher application package. The Screen receives the “On/Off Broadcast Receiver” so it is processed with Intent from Screen-On, activating the Lock Screen Activity.

The Lock Screen Activity consists of Password settings and, to unlock the screen, a password must first be entered. After setting the password, two options are available: a user can either enter the password or shake the mobile phone.

Binding the Home key is different in Guest mode than it is in User mode. Comparing our system to the Pattern Lock and number password systems, the Pattern Lock has about one million key spaces, the number password system has about 10,000 key spaces, and our Lock Screen system has about ten million (6^9 = 10077696) key spaces. It can also be made larger by increasing the number of repetitive touches.

MODULES:

  • Device Background module
  • Configuration module
  • Lock screen module
  • Sending pattern in Mail module

MODULES DESCRIPTION:

Device Background

Our work reveals to identify user interaction with the phone, making calls, incoming calls and SMS and giving access to answer incoming call while screen is locked by our application. We also utilized a low level system resource than expensive sensors by consuming the resource when no other application accessing ie out application will require resource when device screen is off, which ultimately decrease the power consumption ie battery. Our device, which is a mobile smartphone, contains contacts, mails, and SMS as private information of the user. Encouraging results in protected user privacy and secure their data.

Configuration

First of all the user should configure their lock screen pattern, based on Redundancy input (re-touching the circle), user is allowed and when the circle is touched more than once, it changes color (maximum of seven times) so that the user can identify the correct input. Then the user can save the pattern he/she defined in the configuration screen

Lock Screen

The Screen receives the “On/Off Broadcast Receiver” so it is processed with Intent from Screen-On, activating the Lock Screen Activity. When the user click on the circle each time the color of circle will change, after entered the pattern user clicks Unlock button, and collect the pattern information is compared with the already configured pattern by user, if the pattern is match, then the screen allows user to enter into his mobile functionality, otherwise the message will be appear as wrong pattern.

Sending pattern in Mail module

If the user forget is password, he can’t access his phone, without giving correct pattern he already configured, so the pattern is send in mail to the mail id given by the user at the time of configuration.

SYSTEM MODELS

HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard

Mobile                       :        ANDROID MOBILE

 SOFTWARE REQUIREMENT 

Operating System   :  Android

Language              :  ANDROID SDK 2.3

Back End                       :    SQLite

Documentation      :    Ms-Office

REFERENCE:

Fukuoka-shi, “Design and Implementation of Improved Authentication System for Android Smartphone Users”, IEEE International Conference on Advanced Information Networking and Applications Workshops, 2012.

Research and design of chatting room system based on Android Bluetooth

Research and design of chatting room system based on Android Bluetooth

ABSTRACT:

Bluetooth provides a low-power and low-cost wireless connection among mobile devices and their accessories, which is an open standard for implementing a short-range wireless communication. Bluetooth is integrated into Android which is a mainstream smart phone platform as a mean of mobile communication. Android has attracted a large number of developers because of its character of open sourcing and powerful application AP I. This article takes designing a Bluetooth chat room for example to research Bluetooth and its architecture of android platform and introduce the process of realizing the Bluetooth communication in detail. Then we design and implement a chat room based on Bluetooth by using APIs of Android platform. At last, a further prospect of the function of this system was made.

ARCHITECTURE:

SYSTEM MODELS

HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard 

SOFTWARE REQUIREMENT 

Operating System   :  Android

Language              :  ANDROID SDK 2.3

Back End                       :    SQLite

Documentation      :    Ms-Office

REFERENCE:

Weihua Pan, “Research and design of chatting room system based on Android Bluetooth”, IEEE International Conference on Consumer Electronics,  Communications & Networks, 2012.

Designing Mobile Language Learning Applications Using Multimedia

Designing Mobile Language Learning Applications Using Multimedia: Implications from a Small-scale Prospective Learner Study

ABSTRACT:

This paper sets out to provide a preliminary guidance on developing mobile language learning applications, with consideration for using multimedia. A set of initial findings are presented from a small-scale pilot learner study, along with other considerations from findings in the literature. These preliminary guidelines could be further developed in later iterations to provide an overall framework for developing and evaluating other multimedia elements in mobile language learning applications and possibly also other mobile learning applications that use multimedia extensively (e.g. musical learning).

EXISTINGS SYSTEM:

So far, there have been a few notable trials of language learning applications for mobile phones, dating as far back as 2001 (e.g. Stanford Learning Lab pilots). Chinnery provides a review of several mobile language learning developments since then, and while there have been some interesting uses of PDAs and iPods for language learning (e.g. the focus has generally been on delivering simple features such as vocabulary learning and quiz drills in text format. However, if the goal is to further exploit the use of multimedia capability for more complex learning applications, there needs to be a more focused effort in developing design guidelines for these applications.

DISADVANTAGES OF EXISTINGS SYSTEM:

One of the first issues that need to be addressed is to systematically and comprehensively explore the affordance and design issues for mobile devices in language learning. There is a suggestion that mobile devices are unique in their ability to offer a personal and portable solution for learning as compared to ordinary computer-based learning. However, they are also constrained by their physical properties (generally smaller screen sizes, etc.) and these properties ought to be taken into account in the design phase of any learning solution. As language learning can involve many different modalities (e.g. audio, text, static pictures), and there are a wide variety of different kinds of mobile devices that can be used for learning (e.g. game-based devices, blackberry, iOS and Android phones).

PROPOSED SYSTEM:
A set of initial findings are presented from a small-scale pilot learner study, along with other considerations from findings in the literature. These preliminary guidelines could be further developed in later iterations to provide an overall framework for developing and evaluating other multimedia elements in mobile language learning applications and possibly also other mobile learning applications that use multimedia extensively

ADVANTAGES OF PROPOSED SYSTEM:

Advances in mobile computing have led to the development of a whole range of applications for providing education in a very diverse range of fields, from in situ education in school children with augmented reality, to museum guides, to developing bird watching skills. It has been argued that new mobile technologies allow for learning programmes to be developed that (by comparison to traditional learning) are more personalised, learner-centered, situated, collaborative, ubiquitous and lifelong. An additional advantage often overlooked (particularly for mobile phones) is that there is a natural affordance for phones to speak into and listen from (i.e. audio interaction). In this way, applications that involve speaking and listening may actually be better suited to mobile phones than the PC environment

MODULES:

1) Participants Module

2) Course Module

3) Test Module

4) Result Module

5) Analysis Module

MODULES DESCRIPTION:

1) Participants Module

In this module, user authentication is done according to the role based access control. A new user has to register for access the content of our system. Registered user logins with the registered username and password.

2) Course Module

The new user/student will take up the course material module first. Before that the user/student should select the course which he/she is going to take up. Example: Java or dot net or etc. After that the course contents are displayed and user should read the contents available. Then the user can navigate to the pages.

3) Test Module

After the Course material module, the user/student will be taking up the examination module. In the examination module, the user/student will be allocated some question and time for it.

4) Result Module

In the Result module, the user or participants results are displayed and the results are being analyzed. So that the participants status can be clearly known.

5) Analysis Module

In this module graph based analysis is done for the results generated by the users. The analysis module shows how the application is useful and the advantages of the proposed system clearly.

SYSTEM MODELS

 HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard

 SOFTWARE REQUIREMENT 

Operating System   :  Android

Language              :  ANDROID SDK 2.3

Back End                       :    SQLite

Documentation      :    Ms-Office

REFERENCE:

  1. Uther, “Designing Mobile Language Learning Applications Using Multimedia: Implications from a Small-scale Prospective Learner Study”, IEEE INTERNATIONAL CONFERENCE ON WIRELESS, MOBILE AND UBIQUITOUS TECHNOLOGY IN EDUCATION, 2012.

EduPad — A tablet based educational system for improving adult literacy in rural India

EduPad — A tablet based educational system for improving adult literacy in rural India

 ABSTRACT:

 The rate of Literacy is an important indicator of a society’s overall human development. The population of India, as in most other developing countries is concentrated in the rural areas. However, the rural areas of India are often at a disadvantage within the Indian Education System. An educational system called EduPad, to reduce the rural adult illiteracy using advancements in technology is proposed here. Such a system can be used to make up for lack of qualified personnel and adequate infrastructure in rural India. The device proposed here is an interactive Tablet, which is capable of teaching multiple languages. We propose to develop interactive educational software which can run on the tablet. The software helps the user to learn to write as well as spell the alphabets. Initially the software teaches alphabets and then moves onto words and sentences.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

EXISTING SYSTEM:

  • For language learning process users have book materials, video clips, Audio system. For using the book material user need some basic knowledge to read . In the case of video clips and Audio system user need proper platform and the existing system is also not it should not be an portable.

DISADVANTAGES OF EXISTING SYSTEM:

  • User need proper hardware device for learning purposes.
  • It should be difficult to use by literate people.

PROPOSED SYSTEM:

In proposed system we implement the learning process in mobile environment, it provide portable facilitate to the user. Android is an mobile operating system it helps the developer to simulate learning process to  our Android based mobile. The Android SDK provides the tools and APIs for developing applications on the Android platform using the Java programming language. Developers write programs in the Java language using Eclipse IDE.  Dalvik virtual machine is an interpreter for eclipse IDE it optimized for use on low power consumption, rich libraries, non-fragmented application programming interfaces, low memory devices like phones.

ADVANTAGES OF PROPOSED SYSTEM:

  • Android Application framework enabling reuse and replacement of components.
  • It provides better understanding about language to literate and unknown users.
  • The developed programming has ability to implement in pc, tablets, and mobiles.

 ARCHITECTURE:

MODULES:

  • Learning Alphabet Module
  • Alphabet Example Module
  • Writing Alphabet Module

MODULES DESCRIPTION:

Learning Alphabet

In our system the Alphabets in English language are showing one by one to the user (illiterate user), user having controls to move to the next and previous character, the Character is shown to the user in big screen, so even elder user can also read the alphabets, and user have the option to change from upper case to lower case and vice versa, the correspondent character in the screen to the user. User can listen to the alphabet while they seeing the alphabet in the screen. It helps the user to learn character and pronunciation too.

Alphabet Example

Example for the alphabet is shown to the user with the Object name and its picture, to easily understandable by the user by seeing the object in the screen, and name displayed. And the user has the controls to go to next and previous as in the learning module. When the user presses the play button, the sentence is read out to the user. User can easily understand the alphabet and its usage by listening the example sentence produced as sound.

Writing Alphabet

In this module the step by step writing animation for each alphabet is shown to the user. User can try to write the alphabet in the screen itself, by following the animation shown in the screen. User has the option to navigate to the next and previous alphabet and can learn to write all English alphabets.

SYSTEM MODELS

 HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard

 

SOFTWARE REQUIREMENT 

Operating System   :  Android

Language              :  ANDROID SDK 2.3

Back End                       :    SQLite

Documentation      :    Ms-Office

REFERENCE:

 R.K. MEGALINGAM, “EDUPAD – A TABLET BASED EDUCATIONAL SYSTEM FOR IMPROVING ADULT LITERACY IN RURAL INDIA”, IEEE International Conference on Technology Enhaced Education (ICTEE), 2012.

Safe Driving Using Mobile Phones

Safe Driving Using Mobile Phones

ABSTRACT:

As vehicle manufacturers continue to increase their emphasis on safety with advanced driver-as assistance systems (ADASs), we propose a device that is not only already in abundance but portable enough as well to be one of the most effective multipurpose devices that are able to analyze and advise on safety conditions. Mobile smart phones today are equipped with numerous sensors that can help to aid in safety enhancements for drivers on the road. In this paper, we use the three-axis accelerometer of an Android-based smart phone to record and analyze various driver behaviors and external road conditions that could potentially be hazardous to the health of the driver, the neighboring public, and the automobile. Effective use of these data can educate a potentially dangerous driver on how to safely and efficiently operate a vehicle. With real-time analysis and auditory alerts of these factors, we can increase a driver’s overall awareness to maximize safety.

PROJECT OUTPUT VIDEO: (Click the below link to see the project output video):

 

FEATURES:

  • Uses the accelerometer sensors from Android mobile to match the Drunk and drive pattern.
  • Automatically sends a message for Help.
  • Displays on the Screen a message.

EXISTING SYSTEM:

Analysis of external sensors data for vehicle performance is a large area of study. Some work has been done in the form of theoretical research and development in a practical design. The main ideas of our work focus on mapping anomalies of a road’s surface and classifying different driving behaviors. There has been some work in the field of road analysis, specifically road anomaly detection. Nericell [1] is a system researched and developed by Microsoft that detects traffic honking, bumps, and vehicle braking using external sensors. For detection, it uses multiple external sensors such as a microphone, GPS, accelerometer, and Global System for Mobile communications radio for traffic localization. Pothole Patrol [15] is another system that monitors road conditions using GPS and an external accelerometer. The system was deployed for testing in taxis using a convenient method to identify fatigued surfaces of a road.

PROPOSED SYSTEM:

In this paper, we use the three-axis accelerometer of an Android-based Smartphone to record and analyze various driver behaviors and external road conditions that could potentially be hazardous to the health of the driver, the neighboring public, and the automobile. Effective use of these data can educate a potentially dangerous driver on how to safely and efficiently operate a vehicle. With real-time analysis and auditory alerts of these factors, we can increase a driver’s overall awareness to maximize safety.

MODULES:

  • Device Background module
  • Phone Orientation and Location module
  • Road Anomaly Detection module
  • Sending data Alert SMS module

MODULES DESCRIPTION:

Device Background

Our work reveals to identify not only potholes but also bumps and rough, uneven, and smooth roads using multiple axes of the accelerometer. We also utilized a single measuring device rather than expensive external sensors placed in numerous places around the vehicle, which ultimately increases infrastructure costs. Our device, which is a mobile smartphone, contains GPS, microphones, and an accelerometer offering flexibility in methodology and user implementation. Encouraging results in identifying numerous road anomalies and sudden driving maneuvers allow for our system to evaluate an entire road’s condition and help advise drivers on unsafe characteristics, respectively, both of which are distinguishable factors that can determine safety on the road.

  • Accelerometer sensor is going to sense x, y & z direction value.
  • If the vehicle is moving in normal position, then it will show x & y direction values.
  • If vehicle is out of control, then it will follow x, y & z direction.

Phone Orientation and Location

The orientation of the phone is a variable that may be constantly changing with the movement of the vehicle, and so might be arbitrarily placed inside the vehicle when the driver enters. The phone’s orientation for each experiment remained the same, with the y-axis pointing toward the front of the vehicle and the screen (z-axis) facing the roof. A holster that was provided with the phone was used along with velcro to secure the phone to the vehicle’s surface. To obtain appropriate data, the phone was tested in multiple locations for each experiment before a final decision was declared.

Road Anomaly Detection

Poor road conditions can lead to repavement methods that can cause an increase in both traffic congestion and travel time. A distressed road can also increase the chance of an accident. By expanding on work presented in [1] and [15], we extended road anomaly detection using a mobile phone’s accelerometer. The embedded accelerometer is capable of detecting subtle or extreme vibrations experienced inside the vehicle. For example, vibrations experienced as jerks can be caused by potholes or a rugged/damaged road from a rough road. Speed bumps and potholes are two nuisances that plague drivers on the road every day. Using a smartphone, we look for these road characteristics using a combination of the x-axis and z-axis of the accelerometer. When a vehicle experiences a bump, it ascends onto the bump, resulting in a quick rise or spike in the value of the z-axis. This also results in a subsequent increase in the x-axis, depending on the bump formation. At high speeds, the spike in the value of the z-axis is very prominent. However, for low speeds, this rise is not as obvious but still leaves an apparent impact. To detect bumps at low speeds, we compensate with the x-axis and a dynamic threshold based on speed. If the difference between two consecutive acceleration values of the z-axis exceeds the threshold, as well as an x-axis threshold, a bump can be assumed [15]. Differentiating a pothole from a bump can be a difficult task using only a z-axis threshold, as seen in [15], but both are distinguishable using this method. We visually illustrate this method with a bump formation in the z-axis with gravity, whereas we also show the secondary technique without gravity using the x-axis to help differentiate a bump from a pothole.

Sending data Alert SMS:

In this module, based on the variation of directions an alert messages is sent to the Owner with a data say car number or any etc.

SYSTEM MODELS

HARDWARE REQUIREMENT

CPU type                      :    Intel Pentium 4

Clock speed                   :    3.0 GHz

Ram size                       :    512 MB

Hard disk capacity         :    40 GB

Monitor type                 :    15 Inch color monitor

Keyboard type               :     internet keyboard

Mobile                            :    ANDROID MOBILE

SOFTWARE REQUIREMENT

Operating System:  Android

Language           :  ANDROID SDK 2.3

Documentation   :    Ms-Office 

REFERENCE:

Mohamed Fazeen, Brandon Gozick, Ram Dantu, Moiz Bhukhiya, and Marta C. González, “Safe Driving Using Mobile Phones” IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2012.