Streamlining College Enquiries: Integrating Amazon Lex and Twilio for WhatsApp Chatbot Accessibility
In the current technological landscape, remote access to information holds significant importance in societal interaction. With the increasing reliance on digital connectivity, individuals seek succinct and readily available responses to their inquiries. The creation of a chatbot for college inquiries using Amazon Lex exemplifies a strategic utilization of modern technology to enrich user experience and streamline information retrieval within the educational sector. This initiative aims to harness the capabilities of Amazon Lex, a robust conversational interface platform, to establish a user-friendly and effective system for addressing various college-related queries. Leveraging Cloud services like Amazon Lex and messaging services such as Twilio, the chatbot will proficiently comprehend and respond toa wide range of queries regarding admissions, courses, schedules, facilities, and other relevant information. Deploying the chatbot across platforms like websites and messaging apps will offer students, parents, and faculty members seamless access to pertinent information, thereby enhancing engagement, reducing response times, and optimizing administrative processes within the college environment. Through this project, the transformative potential of chatbot technology in fostering personalized and interactive communication channels within educational institutions will be realized, contributing to a more connected and efficient learning environment.
Authors
- N Sneha (ORCID: https://orcid.org/0000-0003-2782-1805)
- B. Keerthana (ORCID: https://orcid.org/0009-0000-6820-514X)
- M K Kavyashree
- SnehaHaridas Anupama (ORCID: https://orcid.org/0000-0003-0728-8468)
- Kruthi Krishnagiri
- H U Spoorthy
Institutions
- JSS Science and Technology University (IN)
Publication Details
- Published
- 2024-12-12
- DOI
- https://doi.org/10.1109/ocit65031.2024.00078
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00