Volume-4 , Issue-4 , Apr - 2016 Go Back

Radio Frequency Identification (RFID) is an auto-identification technology which uses Radio Frequencies (between 30 kHz and 2.5GHz) to identify objects remotely. The automated toll collection system using Radio Frequency Identification (RFID) tag which emerges as a good solution to a manual toll collection system at toll gates. It is used for automatic toll collection at the tollgates and to detect the stolen car at the toll plaza which can help the police to find the stolen car. The RFID tag is a unique ID which is given by the RTO (Regional Transport Office) authority. With respect to these RFID tag ID, all the basic information about the customer and his history is stored. It stores information regarding the tolls, a particular user’s vehicle passes and the amount deducted. The tag detection sensor in the reader creates the electromagnetic medium in which the incoming vehicle’s RFID tag is detected, the toll amount will be deducted from his prepaid balance and the new balance is updated. Time and efficiency are a very major priority of the project in the present day. These make the toll plaza transaction more convenient for the public use, it saves a lot of time and it also helps to conserve the environment by reducing the pollution.

RFID Reader, RFID Tag,Toll Collection,Prepaid Account,Toll Automationrs232,RTO

[1] Sachin Bhosale, Dnyaneshwar Natha Wavhal ,“AUTOMATED TOLLPLAZA SYSTEM USING RFID”,ISSN: 2278 – 7798, International Journal of Science, Engineering and Technology Research (IJSETR), Volume 2, Issue 1, January 2013
[2] Kadali Sridhar, K. Naga Divya and D. Sree Lakshmi, "A Fingerprint and RFID Tag Based Authentication System for Driving", International Journal of Computer Sciences and Engineering, Volume-03, Issue-09, Page No (71-76), Sep -2015, E-ISSN: 2347-2693
[3] Rakhi Kalantri, Anand Parekar, Akshay Mohite, Rohan Kankapurkar,” Rfid Based Toll Collection System”, International Journal Of Computer Science And Information Technologies,Volume 5 (2) , Page No. (2582-2585),2014.
[4] Pranoti Salunke, Poonam Malle, Kirtidatir, Jayshreedukale,”Automated Toll Collection System Using RFID”, IOSR Journal Of Computer Engineering (IOSR-JCE),Volume 9, Issue 2 ,Page No.(61-66) ,Jan. - Feb. 2013.

Kerav Shah, Gourav Inani, Darshan Rupareliya, Rupesh Bagwe and Bharathi H N, "RFID Based Toll Automation System," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.51-54, 2016.

Face Tracking and face recognition using Multiagent System that will help us to identify and then recognize the human face as an image provided to it.face recognition system is a computer application used to automatically identify or verify a person from a digital image from a video source. This is usually achieved through the comparison of selected facial features from the image and a facial database. Typically used in security systems and comparable to other biometrics like fingerprint or eye iris recognition systems, facial recognition software is based on the ability to recognize a face by measuring the various features of the face.

MAS(Multi Agent System), JADE(Java Agent Dvelopment Environment), OpenCV(Open Source Computer Vision), ACL (Agent communication Language),Agent,Face Recognition,Face detection

[1] Yanfei Zhu, Qruqi, “Face Feature Extraction Based on Agents with Multi-camera System” International Journal of Information and Computer Science IJICS Volume 1, Issue 2, May 2012 PP. 34-38
[2] Cahit Gürel,, Prof. Dr. Abdulkadir Erden “FACE DETECTION ALGORTIHM WITH FACIAL FEATURE EXTRACTION FOR FACE RECOGNITION SYSTEM” The 20th Int. Conf. on Mechatronics and Machine Vision in Practice- M2ViP 2013 September 18-20, 2013, Ankara, Turkey
[3]Akram Qureshi and Ashok Kajla, "Intelligent Face Recognition", International Journal of Computer Sciences and Engineering, Volume-04, Issue-02, Page No (128-133), Feb -2016, E-ISSN: 2347-2693
[4] OpenCV, opencv.org/ ,15th March 2016
[5] Face Detection, www.researchgate.net/publication/272487406_FACIAL_FEATURE_DECTION_AND_RECOGNITION_FOR_VARYING_POSES, 1st March 2016
[6] Face Recognition, www.researchgate.net/publication/262875649_ Design_of_a_Face_Recognition_System ,29th February 2016
[7] MAS(Multi Agent System), www.masfoundations.org/, 19th February 2016

Wasim Shaikh, Hemant Shinde and Grishma Sharma, "Face Recognition Using Multi-Agent System," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.55-58, 2016.

The emergence of cloud computing paradigm offers attractive and innovative computing services through resource pooling and virtualization techniques. It shifts the delivery and maintenance of software, databases and storage to the internet, transforming them into Pay-As-You-Go (PAYG) services, which accessed through a small business user’s web-browser. This technology introduces a new concern for enterprises and business organizations regarding their privacy and security. Security as a service in a cloud model integrates their security services into a corporate infrastructure. In corporate infrastructure it mainly concentrates on security systems developed to store and maintain documents over the cloud platform. The proposed work focused on the security platform to store and retrieve files on the cloud with onetime password protection. The main contribution of this research is to authenticate file while uploading and downloading from server with onetime password protection. The files are distributed to the employees of an organization by administrator and it can be downloaded by user with onetime password protection. This feature helps to secure the data before viewed by user or any unauthorized user who is act as a third party to that organization.

Pay-As-You-Go, privacy and security, onetime password protection

[1] Papadimitriou P and Garcia-Molina, “Data Leakage Detection” Knowledge and Data Engineering, IEEE Transactions on Volume: 23, Issue: 1, Page No (51-63), Jan 2011.
[2] Michael Miller, “Cloud Computing - Web-Based Applications that change the way you work and Collaborate Online” , Pearson Education, 2012 .
[3] Kumar Ajay, Goyal Ankit, Kumar Ashwani, Chaudhary Navneet Kumar and Sowmya Kamath, “Comparative evaluation of algorithms for effective data leakage detection”, Information & Communication Technologies (ICT), 2013 IEEE Conference, ISBN 978-1-4673-5759- 3, Page No(177-182), April 11-12, 2013.
[4] Chandni Bhatt et al, “Data Leakage Detection”, International Journal of Computer Science and Information Technologies, 2014
[5] Ankit Tale, Mayuresh Gunjal and B.A. Ahire, “Data Leakage Detection Using Information Hiding Techniques”, International Journal of Computer Sciences and Engineering, E-ISSN : 2347 - 2693, Volume-2, Issue-3 Page No (155-158), March - 2014.

K. Mythili, S. Rajalakshmi and D. Vidhya, "Data Leakage Detection in Cloud Computing using Identity Services," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.59-63, 2016.

This Wireless sensor network is deal with sensing the information from deployed area. For data transmission from source node to destination node various routing protocols is used. Due to routing the energy consumption occurred in the network. In wireless sensor network energy consumption is one of the main problems because every node is operated by battery. In wireless sensor network energy utilization is one of the primary issues in light of the fact that each node is operated by battery. In wireless sensor networks, sensors expend energy both in detecting information and transmitting the detected information to a base station. The power utilization for transmitting information is an exponential function of the separation from the sensor to the base station. Power utilization for detecting information is controlled by the kind of sensor and in addition the routing protocol. The issue in this paper is to build the life time of the sensor systems. To have expansive system life time’s everything nodes need to minimize their energy utilization.

Wireless Sensor Networks, Applications of WSN, Routing in WSN, Intrusion Detection System, Sinkhole Attack

[1] S. Misra, P.V. Krishna, K.I. Abraham “Energy efficient learning solution for intrusion detection in Wireless Sensor Networks” Second International Conference on Communication Systems and Networks, pp. 1-6, 2010.
[2] Satish Kumar, "A Study of Wireless Sensor Networks- A Review", International Journal of Computer Sciences and Engineering, Volume-04, Issue-03, Page No (23-27), Mar -2016.
[3] J. Petajajarvi, H. Karvonen “Soft handover method for mobile wireless sensor networks based on 6LoWPAN” International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS), 2011, pp. 1 – 6, DOI: 10.1109/DCOSS.2011.5982208
[4] Qingtian Sun, Shunfu Jin, Chen Chen “Energy analysis of sensor nodes in WSN based on discrete-time queueing model with a setup” Chinese Control and Decision Conference (CCDC), 2010, pp. 4114 – 4118, DOI: 10.1109/CCDC.2010.5498425.
[5] J.M.L.P. Caldeira, J.J.P.C. Rodrigues, P. Lorenz, L. Shu “Intra-mobility handover enhancement in healthcare wireless sensor networks” 14th International Conference one-Health Networking, Applications and Services (Healthcom), 2012, pp. 261 – 266.
[6] R. Silva, J. Sa Silva, M. Simek, F. Boavida “A new approach for multi-sink environments in WSNs” International Symposium on Integrated Network Management, 2009. IM '09. IFIP/IEEE, pp. 109 – 112.
[7] X. Chen, P. Yu “Research on hierarchical mobile wireless sensor network architecture with mobile sensor nodes” IEEE 3rd International Conference on Biomedical Engineering and Informatics (BMEI), 2010, pp. 2863 – 2867.
[8] Yong-Sik Choi, Young-Jun Jeon, Sang-Hyun Park “A study on sensor nodes attestation protocol in a Wireless Sensor Network”, IEEE 12th International Conference on Advanced Communication Technology (ICACT), 2010, Volume: 1, pp. 574-579.
[9] S. Kwon, J. H. Ko, Jeong kyu Kim and Cheeha Kim, “Dynamic timeout for data aggregation in wireless sensor networks”, Elsevier Journal of Computer Networks, 21 February 2011, pp. 650-664.
[10] R. L. Balla, V. Kotoju, "Sinkhole Attack Detection And Prevention in Manet & Improving The Performance of AODV Protocol", Compusoft, An International Journal of Advanced Computer Technology, 2013, PP 210-214.
[11] X. Wang, G. Xing, Y. Zhang, C. Lu, R. Pless, and C. Gill, "Integrated Coverage and Connectivity Configuration in Wireless Sensor Networks," IEEE Conference on WSN, 2003, pp 23-32.
[12] L. Doherty, K. S. J. Pister, and L. E. Ghaoui, "Convex Position Estimation in Wireless Sensor Networks," International conference on INFOCOM, 2001, pp 230-241.
[13] T. Dimitriou, I. Krontiris, T. Giannetsos and M. Mpasoukos, “Intrusion Detection of Sinkhole Attacks in Wireless Sensor Networks”, In Algorithmic Aspects of Wireless Sensor Networks, pp. 150-161.Springer Berlin Heidelberg, 2008.
[14] E. C. H. Ngai, J. Liu, and M. R. Lyu, “An Efficient Intruder Detection Algorithm against Sinkhole Attacks in Wireless Sensor Networks,” Computer Communications, vol. 30, pp. 2353-2364, 2007.
[15] Charanpreet Kaur and Amit Chhabra, "An Energy Efficient Multihop Routing Protocol for Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Volume-03, Issue-07, Page No (86-91), Jul -2015.
[16] Liping Teng, Yongping Zhang, "Sera: A Secure Routing Algorithm against Sinkhole Attacks For Mobile Wireless Sensor Networks", Second International Conference on Computer Modeling and Simulation 2010, PP 79-82.
[17] Nisarg Gandhewar, Rahila Patel, "Detection & Prevention of Sinkhole Attack on AODV Protocol in Mobile Adhoc Network", Fourth International Conference on Computational Intelligence and Communication Networks, 2012, PP 714-718.
[18] I. Krontiris, T. Dimitriou, F.C. “Freiling Towards intrusion detection in wireless sensor networks”. In: Proceedings of the 13th European Wireless Conference, Paris, France (April 2007).
[19] Gisung Kim, Younggoo Han, Sehun Kim, “A cooperative-sinkhole detection method for mobile ad hoc networks”, International Journal of Electronics and Communication 64 (2010) 390–397
[20] NS-2, The ns Manual (formally known as NS Documentation) available at following link:http: //www. isi.edu/nsnam/ ns/do

Rohit Aggarwal and Khushboo Bansal , "An Efficient Intruder Detection System against Sinkhole Attack in Wireless Sensor Networks: A Review," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.64-68, 2016.

With the expanding volume of pictures clients offer through social locales, keeping up security has turned into a noteworthy issue, as exhibited by a late influx of advanced episodes where clients unintentionally shared individual data. In light of these episodes, the need of apparatuses to offer clients some assistance with controlling access to their common substance is evident. Toward tending to this need, we propose an Adaptive Privacy Policy Prediction (A3P) framework to offer clients some assistance with composing protection settings for their pictures. We look at the part of social connection, picture substance, and metadata as could be expected under the circumstances pointers of clients' security inclinations. We propose a two-level system which as indicated by the client's accessible history on the site, decides the best accessible security approach for the client's pictures being transferred. Our solution relies on an image classification framework for image categories which may be associated with similar policies, and on a policy prediction algorithm to automatically generate a policy for each newly uploaded image, also according to users’ social features. Over time, the generated policies will follow the evolution of users’ privacy attitude. We provide the results of our extensive evaluation over 5,000 policies, which demonstrate the effectiveness of our system, with prediction accuracies over 90 percent.

A3P, Metadata, Policies, Content sharing, Privacy, Prediction

[1] Mr. Pankaj Sareen and Dr. Tripat Deep Singh “Data Security in Cloud”, International Journal of Computer Science Engineering (IJCSE) ISSN : 2319-7323, Vol. 4 No.05 Sep 2015
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[5] M. Ames and M. Naaman, “Why we tag: Motivations for annotation in mobile and online media,” in Proc. Conf. Human Factors Comput. Syst., 2007, pp. 971–980.
[6] A. Besmer and H. Lipford, “Tagged photos: Concerns, perceptions, and protections,” in Proc. 27th Int. Conf. Extended Abstracts Human Factors Comput. Syst., 2009, pp. 4585–4590.
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Kavitha S and H Girisha, "An Adaptive Privacy Policy Prediction for Classifying the Images as Public and Private for Secured Transaction," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.69-72, 2016.

In current world where software companies are moving towards sustainable rapid development and deployment model, it’s very important to automate the process of software development, build, testing and deployment to avoid the delay in software release. In software development process many developers are involved during software product development. It is very significant that there should be framework which must notify the compilation and build error at least once is a day, so that reported error can be corrected. In most of the cases developer writes a unit test case to test their own written method. So as soon as new code stored into the shared repository there should be a way that we can perform all the unit test cases execution automatically and publish the result to all the developers. The next part of the problem domain is, how fast we deploy the newly build product version on the test environment and execute the test automation suite and publish the result to the all-stake holder on the new build. The last part of the problem domain is as soon as product got passed from the test environment, it must move to the next (Staging / Production like environment) automatically where again we must perform the basic sanity testing and on successful result framework must deploy the product finally to production environment automatically.

Continuous Integration ;Continuous Deployment; Software Development; Regression Testing; Code Coverage, Unit Test; Shared Repository

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[2] Paul Ammann, Jeff Offutt (2013). Introduction to Software Testing. Cambridge University Press.
[3] Eldh, Sigrid, et al. "Towards a Test Automation Improvement Model (TAIM)." Software Testing, Verification and Validation Workshops (ICSTW), 2014 IEEE Seventh International Conference on. IEEE, 2014.
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deployment automation. Pearson Education, 2010.
[6] Jenkins https://jenkins.io/doc/, 2015.
[7] Jacoco http://eclemma.org/jacoco/trunk/doc/, 2015.
[8] Git https://git-scm.com/doc , 2015.

Vivek Verma and Vinay M, "Continuous Integration and Deployment Modern Technique's," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.73-75, 2016.

In the modern times, more sensitive data is being stored on third party servers which are untrusted, so data on these sites need to be in encrypted form. Every now and then new encryption techniques are put forward. Attribute Based Encryption (ABE) is one such cryptographic technique that secures the data and provides fine-grained access control. However, The Computational complexities of ABE key issuing and decryption are getting too high due to the high expressiveness of ABE approach which affects the efficiency of ABE. To tackle this, many Outsourced Variants of ABE have been proposed to improve the efficiency of ABE such that it could be widely deployed. In this paper, a survey is done on various ABE techniques that have been proposed and their advantages and disadvantages are also discussed.

Attribute-based encryption; Key Generation Service Provider; Decryption Service Provider; Access control; Outsourcing computation; Key issuing; Checkability

[1] A. Sahai and B. Waters, ‘‘Fuzzy Identity-Based Encryption,’’ in Proc. Adv. Cryptol.-EUROCRYPT, LNCS 3494, R. Cramer, Ed., Berlin, Germany, 2005, pp. 457-473, Springer-Verlag.
[2] M. Green, S. Hohenberger, and B. Waters, ‘‘Outsourcing the Decryption of ABE Ciphertexts,’’ in Proc. 20th USENIX Conf. SEC, 2011, p. 34.
[3] Z. Zhou and D. Huang, ‘‘Efficient and Secure Data Storage Operations for Mobile Cloud Computing,’’ in Cryptology ePrint Archive, Report 2011/185, 2011.
[4] P. Golle and I. Mironov, ‘‘Uncheatable Distributed Computations,’’ in Proc. Conf. Topics Cryptol., CT-RSA, 2001, pp. 425-440.
[5] V. Goyal, O. Pandey, A. Sahai, and B. Waters, ‘‘Attribute-Based Encryption for Fine-Grained Access Control of Encrypted Data,’’ in Proc. 13th ACM Conf. Comput. Commun. Security, 2006, pp. 89-98.


[6] J. Bethencourt, A. Sahai, and B. Waters, ‘‘Ciphertext-Policy Attribute-Based Encryption,’’ in Proc. IEEE Symp. Security Privacy, May 2007, pp. 321-334.
[7] Mewada, Shivlal, Pradeep Sharma, and S. S. Gautam. "Classification of Efficient Symmetric Key Cryptography Algorithms." International Journal of Computer Science and Information Security 14.2 (2016): pp(105-110).
[8] S. Hohenberger and A. Lysyanskaya, ‘‘How to Securely Outsource Cryptographic Computations,’’ in Proc. Theory Cryptogr., LNCS 3378, J. Kilian, Ed., Berlin, Germany, pp. 264-282, Springer- Verlag.
[9] S. Goldwasser, Y.T. Kalai, and G.N. Rothblum, ‘‘Delegating Computation: Interactive Proofs for Muggles,’’ in Proc. 40th Annu. ACM STOC, 2008, pp. 113-122.
[10] C. Gentry, ‘‘Fully Homomorphic Encryption Using Ideal Lattices,’’ in Proc. 41st Annu. ACM STOC, 2009, pp. 169-178.
[11] C.Gentry and S.Halevi, ‘‘ImplementingGentry’s Fully-Homomorphic Encryption Scheme,’’ in Proc. Adv. Cryptol.-EUROCRYPT, LNCS 6632, K. Paterson, Ed., Berlin, Germany, 2011, pp. 129-148, Springer-Verlag.
[12] J. Li, X. Chen, J. Li, C. Jia, J. Ma, and W. Lou, ‘‘Fine-Grained Access Control System Based on Outsourced Attribute-Based Encryption,’’ in Proc. 18th ESORICS, 2013, pp. 592-609.
[13] M.J. Atallah, K. Pantazopoulos, J.R. Rice, and E.E. Spafford, ‘‘Secure Outsourcing of Scientific Computations,’’ in Trends in Software Engineering, vol. 54, M.V. Zelkowitz, Ed. Amsterdam, The Netherlands: Elsevier, 2002, pp. 215-272.
[14] R. Gennaro, C. Gentry, and B. Parno, ‘‘Non-Interactive Verifiable Computing: Outsourcing Computation to Untrusted Workers,’’ in Proc. Adv. Cryptol.-CRYPTO, LNCS 6223, T. Rabin, Ed., Berlin, Germany, 2010, pp. 465-482, Springer-Verlag
[15] K.-M. Chung, Y.Kalai, F.-H. Liu, and R. Raz, ‘‘MemoryDelegation,’’ in Proc. Adv. Cryptol.-CRYPTO, LNCS 6841, P. Rogaway, Ed., Berlin, 2011, pp. 151-168, Springer-Verlag.
[16] D. Zeng, S. Guo, and J. Hu, ‘‘Reliable Bulk-Data Dissemination in Delay Tolerant Networks,’’ IEEE Trans. Parallel Distrib. Syst. http://doi.ieeecomputersociety.org/10.1109/TPDS.2013.221.

Hadiya Rafiq Mir and U. A. Jogalekar , "A Survey on Outsourced Attribute-Based Encryption Technique," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.76-81, 2016.

Cloud computing is the next generation of internet-based comprehensive computing systems which in it, the computing resources are provided “as a service”. Cloud computing is an important structure with great potential in lessening the costs by recuperating and developing functionality and cost-effective outcome which in turn can increase cooperation, rate and scalability acceptance to comprehensible degree. This technology has provide large organizations and IT companies with lots of opportunities in developed countries but these opportunities face many challenges and barriers which is one of the main concerns in cloud computing field. This paper focuses on a range of considered issues from a broad cross section of areas of expertise required to ensure a successful cloud computing adoption. It presents in detail the various factors which are key to a successful cloud computing adoption. It also explains how the prominence on collaboration between clients and vendor is necessary for successful adoption of cloud computing. If the organisation feels free, confident and secure to use cloud services then it is more likely that the adoption rate will increase. As Cloud Computing is referred to both the applications delivered as services over the Internet and the infrastructures (i.e., the hardware and systems software in the data centres) that provide those services , we present the security concerns in terms of the diverse applications and infrastructures. More concerns on security issues, such as availability, confidentiality, integrity control, authorization and so on, should be taken into explanation. The rest of the paper will be organized as highlighting the basic cloud computing definitions and architecture, presenting the barriers and challenges to adoption of cloud computing and then the paper will be concluded along with the future research scope.

Cloud; Organisational Challenges; Adoption; SLA’s

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[14] B. Mahesh Kumar and V. Savitha, “A Survey on Emergence of Cloud Computing using Brokering Services”, International Journal of Computer Sciences and Engineering,Volume-04,Issue-02,Page No(85-91),Feb-2016,E-ISSN: 2347-2693

Isra Masood, Ankur Bhardwaj and Pushpneel Verma, "Barriers Faced In Cloud Computing Adoption," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.82-85, 2016.

Face Recognition using robotics is a hardware-software system process for recognizing the face whichever provided to it. This project aims to provide flexibility in work where user needs to monitor robots and its features. We will have robots for this purpose; they are programmed and will function accordingly. As there are Robots so we need Arduino Microcontroller and we need to be familiar with Arduino Programming. We have a system where a face as an input suspect will be provided. Robots will search for particular face within some area and accordingly responses to the user machine. The system will be having OpenCV with JavaCV for processing of face. And the versions of OpenCV and JavaCV must be compatible with each other.

Arduino, OpenCV (Open Source Compute Vision), JavaCV (Java Computer Vision), Bluetooth, IC (Integrated Circuit)

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[3] http://www.instructables.com/id/Face-detection-and-tracking-with-Arduino-and-OpenC/
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Nitesh Pandey, Abhishek Dubey and Bhavesh Pandekar, "Face Recognition Using Robotics," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.86-90, 2016.

The benefits of remote access advanced the world day by day, create enormous volume of continuous information ( for the most part alluded to the expression "Huge Data"), where understanding data has a potential importance if gathered and totaled viably. In today's period, there is an incredible arrangement added to ongoing remote detecting Big Data than it appears at initially, and separating the helpful data in a proficient way drives a framework toward a noteworthy computational difficulties, for example, to examine, total, and store, where information are remotely gathered. Keeping in perspective the aforementioned components, there is a requirement for planning a framework engineering that invites both real-time, and in addition disconnected from the net information handling. Along these lines, in this paper, we propose constant Big Data expository design for remote detecting satellite application. The proposed design contains three primary units, for example, 1) remote detecting Big Data securing unit (RSDU); 2) information preparing unit (DPU); and 3) information investigation choice unit (DADU). To begin with, RSDU secures information from the satellite and sends this information to the Base Station, where beginning preparing happens. Second, DPU assumes a fundamental part in engineering for proficient handling of constant Big Data by giving filtration, load adjusting, and parallel preparing. Third, DADU is the upper layer unit of the proposed design, which is in charge of assemblage, stockpiling of the outcomes, and era of choice in light of the outcomes got from DPU. The proposed design has the capacity of partitioning, burden adjusting, and parallel handling of just valuable information. In this manner, it results in proficiently dissecting continuous remote detecting Big Data utilizing earth observatory framework. Moreover, the proposed design has the capacity of putting away approaching crude information to perform disconnected from the net investigation on to a great extent put away dumps, when required. At last, an itemized examination of remotely detected earth observatory Big Data for area and ocean territory are given utilizing Hadoop. What's more, different calculations are proposed for every level of RSDU, DPU, and DADU to recognize land and in addition ocean ranges to expound the working of a design.

Big data, remote sensing, DPU, Hadoop

[1] Real-Time Big Data Analytical Architecture for Remote Sensing Application Muhammad Mazhar Ullah Rathore, Anand Paul, Senior Member, IEEE, Awais Ahmad, Student Member, IEEE,Bo-Wei Chen, Member, IEEE, Bormin Huang, and Wen Ji, Member, IEEE
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