Maintaining discipline in public transport system is need of today. since traffic on the roads is increasing day by day and so the pollution. Traffic signals plays very important role in maintaining discipline in public/local transportation systems in urban cities like Mumbai, Pune in India. Many underage children drives vehicles , and driving without license may cause accidents. Maintaining the discipline in public transport is core responsibility of each and every citizen. Due to corruption and non adherence to rules are major hurdle in maintaining the local transport discipline of India. Proposed , "Bio metric based Challan system for RTO" which makes use of human characteristics such as fingure prints and Eris to perform verification process against the RTO database stored under "licensed users", which will help to reduce the rate of corruption and make people think to maintain the discipline in local transport which may reduce the count of traffic rule brake cases.

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In current scenario all organizations whether it is commercial, financial or educational, face the problem of maintaining and processing huge data. If we consider the case of educational institute, here thousands of student attendance records are generated per day. This will multiply per day, week and year as a result generates vast amount of data and subsequently increases the processing time apart from cost. In order to process the data efficiently, we have proposed MapReduce based algorithm (AcdMR) for processing of an academic data in our first paper. This work describes practical implementation of AcdMR and performance analysis based on distinct cluster configuration over dataset size (1GB, 5GB).

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