Automated Exam Room Allotment Using Cloud-Serverless Computing

¹ Assistant Professor, Department of Artificial Intelligence & Machine Learning, BMS Institute of Technology & Management, Bengaluru, Karnataka, India
² Assistant Professor, Department of Artificial Intelligence & Machine Learning, BMS Institute of Technology & Management, Bengaluru, Karnataka, India
³ Assistant Professor, Department of Artificial Intelligence & Machine Learning, BMS Institute of Technology & Management, Bengaluru, Karnataka, India
⁴ Assistant Professor, Department of Artificial Intelligence & Machine Learning, BMS Institute of Technology & Management, Bengaluru, Karnataka, India

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Abstract

Effective room allocation for examinations is an important administrative problem in educational institutions. Common methods, both manual and automated, do not succeed in avoiding clustering of students enrolled in the same course, hence there is a possibility of cheating. In this paper, we present an adaptive multiple constraint-based approach for room allocation implemented via a serverless cloud-based architecture hosted on Amazon Web Services (AWS). The approach considers subject-based distribution, department balancing, and an adaptive soft constraint based on which the number of students from the same subject per room is limited, along with automatic fallback to other departments where available. Moreover, the proposed method takes dynamic input parameters such as the room size and number of rooms during the execution process. The proposed algorithm runs on AWS Lambda, with data stored in Amazon S3 and request handling via the API Gateway. The experimental analysis shows that our approach ensures balanced room allocation without clustering of the same subjects in the same room without any constraints violations regardless of the dataset size.