Development of an Arduino- and Internet of Things (IoT)-Based Early Warning Bell System for Bullying Against Autistic Children

Bullying in educational settings remains a critical issue, particularly for students with Autism Spectrum Disorder (ASD) who often struggle with verbal communication and social cues. This research addresses the lack of affordable and non-invasive early warning systems designed specifically for the sensory needs of autistic children. The primary objective was to develop and test an Arduino- and Internet of Things (IoT)-based early warning bell system to empower ASD students to report bullying incidents in real time. Using a Research and Development (R&D) approach with the 4D development model (Define, Design, Develop), the system was tested by 50 stakeholders, including special education teachers and experts. Results indicate a high level of system effectiveness, with a 94% rapid warning response rate and a 90% increase in students' perceived sense of safety. Statistical analysis yielded a Cronbach’s Alpha of 0.948, confirming high reliability. This study concludes that integrating simple IoT push-button technology with Telegram notifications provides a feasible, low-cost solution for inclusive schools. It shifts the safety paradigm from passive monitoring to active student empowerment, offering a sustainable protection strategy for vulnerable learners.