AI_on_Chip_Fever_Detection_Presentation (1).pptx

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1. AI-on-Chip for Early Fever Detection via Skin Thermodynamics Modeling

2. Problem Statement Traditional fever detection relies on reactive temperature monitoring. - No early warning. - Infrequent sampling. - Cannot detect nuanced thermal changes. Edge AI solutions for real-time fever prediction are underexplored.

3. Research Gap • Lack of AI-on-chip systems for continuous thermal monitoring. • Most existing systems depend on cloud-based inference. • No skin thermodynamics modeling in existing wearables. • No integration of AI + thermal modeling + low-power wearable electronics.

4. Proposed System: Block Diagram

5. Research Objectives 1. Model skin thermodynamics for personalized fever detection. 2. Design low-power wearable sensor patch. 3. Develop AI model for on-chip inference. 4. Implement system on SoC/FPGA. 5. Validate with clinical datasets and prototypes.

6. Literature Review Highlights - Wearable thermometers: Focus on spot readings, not trends. - AI in health wearables: Mostly cloud-based, few on-chip. - Thermodynamics modeling: Rare in wearable tech. - FPGA/SoC in health monitoring: Underutilized for thermal sensing.

7. Journals & Patent Scope 🔬 Possible Journals: - IEEE Transactions on Biomedical Circuits and Systems - IEEE Sensors Journal - Nature Electronics - Biosensors and Bioelectronics 💡 Patent Scope: - Real-time on-chip thermal modeling - AI-driven fever detection hardware - Smart sensor integration for health diagnostics