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Role of Information Systems and DNA Fingerprinting in Crime Investigation

Rana, Aditya (2016-09-28)

Role of Information Systems and DNA Fingerprinting in Crime Investigation

Rana, Aditya
(28.09.2016)

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Information handling is an important and demanding process in any organization. Information systems are used for collecting, saving and manipulating the information. Benefits of information systems are realized when they are used in big organizations handling big and complex data. Crime investigation involves big data handling and involves the complex data for example, DNA sequences of humans.

This research is focusing on the benefits which arise with the implementation of information system in crime investigation department in India. Research describes the role of DNA Fingerprinting in crime scenes, DNA Fingerprinting through automation and the role of embedded computing in DNA Fingerprinting.

The requirements gathered are being used to develop the prototype of the software system which is aimed to enhance the crime investigation process and to perform paternity cases efficiently. The software systems is aimed to be available in all the districts with platform independency and hosted on World Wide Web for accessibility with secured logins.

The main benefit of the software system is the introduction of new three loci which makes system more validate as compared to systems installed in some countries. It is observed that the system being developed has three new features which include the alert generation, addition of three more loci, and information of local police station.

The installation of this system in the local police stations will give an easy access to the administrator to compare and edit the records of the particular case. The administrator can update the criminal’s information if criminal is involved in new crime.

The inclusion of Big Data (Hadoop) in the system is beneficial to handle the large amount of data as per the country requirements. The comparison of the two databases (SQL and Hadoop) is done to show how fast big data responds to the requests. The comparison is done on the basis of time taken by both the databases to read and write the requests from the same amount of data.
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