Open Category Submission

379 – Smart Classroom Behavior Regulator with AI Technology

The classroom environment often proves challenging for children with autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and other developmental disabilities. With over 20 years of experience in special education, we have observed how these students struggle to maintain focus, while teachers face difficulties in sustaining engagement during classroom activities. To address these challenges, we propose an AI-based model that integrates sensory input to enhance engagement for students with autism and developmental disabilities. the behavior control device technology in the classroom environment works according to the theory of sensory integration for students with autism spectrum or attention deficit hyperactivity disorder, by providing appropriate and compatible sensory stimuli according to the signals issued by the student. Key innovations include: a. Use supervised machine learning techniques to train models on annotated video and sensor data to classify student behaviors such as agitation, distraction, or focus.
b. Integrate cameras, motion sensors, and physiological sensors for real-time input.
c. Build a wearable or desk-mounted device with embedded AI, connected via microcontrollers and capable of delivering sensory outputs.
The device monitors them and re-processes them to provide the appropriate stimulus (sound, light), which helps in treating the student’s stress situation and increases the time he/she sits in the classroom environment on a regular basis. By processing sensory information adaptively, the system helps students focus more effectively on tasks while reducing overstimulation. This sensory-friendly approach improves attention spans and participation levels, leading to better learning outcomes and a more inclusive classroom environment. The model’s customizable design ensures tailored interventions that meet each student’s unique needs, ultimately creating a more conducive learning experience. Potential impact include:
1. Modifying Student Behavior in the Classroom Environment.
2. Enhancing the Learning Experience.
3. Facilitating Communication Between Students and Teachers.
4. Supporting Students with Disabilities.

The classroom environment often proves challenging for children with autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and other developmental disabilities. With over 20 years of experience in special education, we have observed how these students struggle to maintain focus, while teachers face difficulties in sustaining engagement during classroom activities. To address these challenges, we propose an AI-based model that integrates sensory input to enhance engagement for students with autism and developmental disabilities. the behavior control device technology in the classroom environment works according to the theory of sensory integration for students with autism spectrum or attention deficit hyperactivity disorder, by providing appropriate and compatible sensory stimuli according to the signals issued by the student. The device monitors them and re-processes them to provide the appropriate stimulus (sound, light), which helps in treating the student’s stress situation and increases the time he sits in the classroom environment on a regular basis. By processing sensory information adaptively, the system helps students focus more effectively on tasks while reducing overstimulation. This sensory-friendly approach improves attention spans and participation levels, leading to better learning outcomes and a more inclusive classroom environment. The model’s customizable design ensures tailored interventions that meet each student’s unique needs, ultimately creating a more conducive learning experience.

*For all the information provided in all the sections، the English version was machine-translated from Arabic with AI-assisted proofreading for linguistic accuracy only. All technical content reflects original human authorship.

NA

1. Phase 1: AI Development and Hardware Integration
a. Use supervised machine learning techniques to train models (e.g., CNNs, RNNs) on annotated video and sensor data to classify student behaviors such as agitation, distraction, or focus.
b. Integrate cameras, motion sensors, and physiological sensors (e.g., heart rate, skin conductivity) for real-time input.
c. Build a wearable or desk-mounted device with embedded AI, connected via microcontrollers (e.g., Arduino, Raspberry Pi) and capable of delivering sensory outputs (LEDs, audio tones).
2. Phase 2: Intelligent Feedback System
a. Develop a reinforcement learning-based feedback loop that adapts sound/light stimuli based on real-time behavioral responses.
b. Implement a rule-based personalization module to allow therapists/teachers to define triggers and stimuli based on individual student needs.
3. Phase 3: Testing and Performance Evaluation
a. Validate model accuracy using precision, recall, and F1 scores for behavior detection.
b. Deploy the system in special education classrooms and measure key metrics such as on-task behavior time, frequency of outbursts, and teacher intervention rate.
4. Phase 4: Optimization and Real-Time Deployment
Note here, accuracy of behavior detection, response latency, user satisfaction (via surveys), and observable improvement in student engagement will serve as core evaluation benchmarks.

1. Modifying Student Behavior in the Classroom Environment:
• Improving Focus and Attention: Enhancing students' ability to concentrate and stay engaged during lessons.
• Reducing Negative Behaviors: Minimizing disruptive actions such as excessive movement or distractions.
• Encouraging Positive Participation: Promoting active and constructive involvement in classroom activities.
2. Enhancing the Learning Experience:
• Interactive and Adaptive Explanations: Providing tailored explanations that align with each student’s level of understanding.
• Immediate Assistance: Offering real-time support to students who face difficulties in comprehending the material.
3. Facilitating Communication Between Students and Teachers:
• Non-Verbal Expression of Needs: Enabling students to communicate their needs non-verbally, such as requesting a break or assistance.
• Behavioral Data for Teachers: Providing teachers with behavioral insights to refine their teaching strategies and approaches.
4. Supporting Students with Disabilities:
• Inclusive Learning Environment: Creating a supportive educational setting for students with autism, ADHD, ADHD, or any developmental disabilities.
The system may face challenges from certain supervisory bodies in educational environments. Additionally, it may require support for teachers in guiding educational practices for the rest of the students in the classroom setting.

Devices integrated with AI algorithms are more effective and sustainable. The model is designed with multiple modifiable capabilities, allowing it to adapt and evolve to address the most prominent behavioral challenges in the classroom environment through control and reprogramming. Due to its low overall cost and ease of reprogramming, the device can be used with multiple students at different levels. It will also be easy to support multiple languages. Future developments include supporting the device to address multiple behaviors, in addition to providing support and facilitating information so that students with developmental difficulties can monitor progress with their peers.

The device is designed for use in diverse educational settings and cultures. It effectively contributes to the integration of a large segment of learners into the educational process and aligns with the Sustainable Development Goals by promoting more inclusive and less restrictive learning environments (inclusive education). The social impact extends directly to the student and their family, as students with developmental disabilities will be more able to control their behavior and adjust more quickly, improving their integration into the classroom environment and peer acceptance. The device also saves families the hassle of transferring their child to another school or searching for a specialized school. The device provides direct and rapid support, facilitating the handling of the situation by non-specialists. This will be beneficial for the school administration, the student, and the family as a whole.

Personal Information Collection Statement (PICS):
1. The personal data collected in this form will be used for activity-organizing, record keeping and reporting only. The collected personal data will be purged within 6 years after the event.
2. Please note that it is obligatory to provide the personal data required.
3. Your personal data collected will be kept by the LTTC and will not be transferred to outside parties.
4. You have the right to request access to and correction of information held by us about you. If you wish to access or correct your personal data, please contact our staff at lttc@eduhk.hk.
5. The University’s Privacy Policy Statement can be access at https://www.eduhk.hk/en/privacy-policy.

• I have read and agree to the competition rules and privacy policy.