AI CHILD BUDDY
| dc.contributor.author | Aaron Voon Wu Chun | |
| dc.date.accessioned | 2026-04-22T06:19:28Z | |
| dc.date.issued | 2025 | |
| dc.description | This project introduces Jang, a voice-activated AI companion designed to provide emotional support and educational interaction for children. Built using Python, Flask, and machine learning tools, Jang operates as a stand-alone Raspberry Pi-based system equipped with voice input/output, emotion recognition, and a simple animated face interface. The primary aim is to foster safe, offline child engagement through natural conversation, basic quizzes, and empathetic responses. Jang also integrates parental monitoring via event logging, allowing guardians to track interactions without direct access to conversations. This paper discusses the full development cycle, from requirement analysis and system design to implementation and testing. Functional and non-functional testing confirmed that Jang is effective in recognising user intent, responding appropriately, and maintaining usability standards. While limited by hardware constraints and local-only processing, Jang demonstrates the potential of affordable, voice-driven AI for child-centred use cases. Future work includes expanding Jang’s emotional intelligence and refining the parental dashboard experience. | |
| dc.identifier.uri | https://scholarhub.unimas.my/handle/123456789/458 | |
| dc.language.iso | English | |
| dc.publisher | Universiti Malaysia Sarawak (UNIMAS) | |
| dc.relation.ispartofseries | Faculty of Computer Science and Information Technology | |
| dc.subject | child buddy | |
| dc.title | AI CHILD BUDDY | |
| dc.type | Final Year Project |