From the very outset, a strategic approach in conducting of the DS camps has been adopted especially to address the challenge of managing queues of thousands of people at the registration counters, as well as the scheme counters during the subsequent Camps scheduled across the State. This necessitated predictive analytics for queues at DS camps for ensuring beneficiary satisfaction and smooth functioning of the service counters in the camps through optimizing services and reducing waiting time.

In view of the above, AI driven trend and future prediction for better management of DS camps eg. queue management during peak hours, ensuring availability of specific departments for handling high demand of certain schemes in particular localities etc. have been implemented.

In the DS portal, we have used machine learning, an application of Artificial Intelligence (AI) that enables the DS Portal to learn and advance, based on initially held camp data without being specifically programmed. Machine Programme Predictive Algorithms using open source R language is incorporated in DS Portal to predict future queues at registration counters and Earmarked Social Benefit Scheme Counters using the historical data obtained from initial camp data.

This has helped deploy requisite officials in counters for delivering efficient services and minimise discomfort to citizens at the camps. The analysis has also led to the identification of peak hours or camps where congestion is highest.

From the experience of DS camps held during initial phase, a strategic approach was felt utmost necessary to address the burning challenges of managing queues of thousand peoples at the Registration Counter and Earmarked Social Benefit Scheme Counters during the forthcoming DS Camps scheduled across the state. This in turn necessitated the predictive analytics for queues at DS Camps for intending beneficiary satisfaction and smooth functioning of the service counters in the camps through optimizing the service and reduce the waiting time.

In view of the above, AI driven trend and future prediction & prescription for better management of DS camps e.g. queue management during peak hours, ensuring availability of specific departmental officials for handling high demand of certain beneficiary schemes in certain localities etc. are implemented.

In DS portal, we have used Machine learning, an application of Artificial Intelligence (AI) that enables the DS Portal to learn and advance based on initially held camp data without being clearly programmed. Machine Learning Predictive Algorithms using open source R language is incorporated in DS Portal to predict future queues in Registration Counter & Earmarked Social Benefit Scheme Counters using the historical data obtained from initial camp data.

This has helped to deploy requisite officials in counters for delivering efficient services and minimize the discomfort to the citizens in the camps. The analysis has also lead to the identification of the peak hours or camps where congestion is maximum.

We have used machine learning technique to predict the Queues by using R machine learning technique and then using Tableau for generating visualizations. We have created R functions which are used in Tableau by creating new calculated fields that dynamically invoke the R engine and pass values to R. The results are then returned back to Tableau for use by the Tableau visualization engine.