HyperHack-2023_eCampusBOT - An Automated Examination Processing System

eCapmusBOT - An Automated Examination Processing System

Use Case Description

Problem Statement: Examination Processing Automation System

With a growing number of students appearing for various examinations each year, the examination process, particularly the tasks related to application form processing and answer sheets processing, is becoming increasingly cumbersome, time-consuming, and error prone. The current manual system not only involves a high level of human intervention but also requires substantial effort to maintain data consistency and accuracy. The challenges faced in the current scenario include:
• Manual data extraction from application forms and answer sheets can lead to potential errors and inconsistencies.
• Manual business rule validation, often leading to discrepancies and inefficiencies in the process of Straight-Through Processing.
• The physical cropping of photos and signatures from application forms and answer sheets for verification and fraud detection purposes is not only a tedious task but also allows room for error.
• Manual uploading of data into the database can lead to data redundancy, data entry errors, and slow data processing times.
• Manual generation and dispatching of Examination Authority Letters and Rejection/Offer Letters is time-consuming and inefficient, leading to potential delays and miscommunication.

Proposed Solution

In order to mitigate these challenges, there is a need for an intelligent Examination Processing Automation System that leverages the UiPath platform to automate tasks associated with application forms and answer sheets. The system must include advanced OCR capabilities for data extraction, business rule engine for validations, image processing capabilities like cropping photos and signatures, robust database interaction for data management, keep the integrity of the candidate details by 2-way matching, and automated email systems for efficient communication. By doing so, the system aims to streamline the examination process, improve data accuracy, and reduce manual workload, ultimately leading to cost and time efficiency.
There are two separate processes in this automation system.

Process 1: Automation of Application Form Tasks

• Data Extraction from Application Forms: Utilizing UiPath’s Document Understanding suite to parse application forms, employing advanced Optical Character Recognition (OCR) technology to convert the scanned forms into usable, structured data.
• Straight-Through Processing (STP) and Business Rule Application: Implementing automation workflows to apply predefined business rules, ensuring data quality, consistency, and completeness. This process will make use of decision-making and exception handling functionalities.
• Image Processing: Leveraging UiPath’s capabilities to identify and extract photo and signature elements from the application forms, subsequently saving them for future use.
• Data Management: Utilizing Database Activities in UiPath to upload the extracted and validated data to UiPath Data Services Entities for data storage and retrieval.
• Communication Automation: Automating the creation and dispatch of Examination Authority Letters, integrating the candidate’s extracted photos into the document, and using UiPath Integration Service with eMail connectors to email these letters to the candidates.

Process 2: Automation of Answer Sheet Tasks

• Data Extraction from Answer Sheets: Again, employing UiPath’s Document Understanding framework to extract data from answer sheets, including recognizing and interpreting multiple-choice responses.
• Straight-Through Processing (STP) and Business Rule Application: Creating an automation workflow to apply business rules to the extracted data, ensuring its consistency and completeness, thereby reducing error-prone manual intervention.
• Signature Extraction for Fraud Checking: UiPath’s image processing capabilities to identify, extract, and save signatures from answer sheets, enabling further verification and fraud detection using the Signature Comparison Machine Learning model from UiPath AI Center.
• Data Validation: Implementing two-way matching to cross-verify the extracted data from answer sheets (ID and name) against the data from application forms.
• Answer Scoring: Utilizing automation workflows to apply scoring rules to the extracted answers against pre-defined answer keys, thereby determining the candidate’s score.
• Communication Automation: Automating the generation and dispatch of Rejection/Offer letters, incorporating the candidate’s photo, and using UiPath Integration Service with eMail connectors to email these letters to the candidates based on their score.


Other information about the use case

Industry categories for this use case: Universities Academy

Skill level required: Advanced

UiPath Products that were used: UiPath Studio, UiPath Action Center, UiPath AI Center, UiPath Assistant, UiPath Data Services, UiPath Document Understanding, UiPath Orchestrator

Other applications that were used: Microsoft Word

Other resources:

What is the top ROI driver for this use case?: Minimize risk and ensure compliance in operations

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