PROPOSAL: Smart Health Surveillance for Preventive Care

Tier 1: Multi-Modal Data Acquisition Layer

Wearable Sensors e.g., Smartwatch, Fitness Band

Ambient Home Sensors e.g., Sleep mat, Toilet sensor

Behavior: Sleep patterns, bathroom frequency

Symptoms: Mood, Pain, Medication Adherence

Connected Medical Devices e.g., BP Cuff, Glucometer

Clinical Data: Blood Pressure, Blood Glucose

Tier 2: Secure Data Transmission &amp; Aggregation

Smartphone Gateway App Data Cache & Pre-processing

Cloud/Edge Database Centralized & Secure Data Repository Structured for Time-Series Analysis

Tier 3: AI-Powered Analytics Engine

Data Preprocessing Cleaning, Normalization, Imputation of missing data

Feature Engineering Deriving meaningful biomarkers e.g., Sleep quality score, Activity trend

Model Types

Aggregate Risk Score Generation & Symptom Correlation

Tier 4: Actionable Output &amp; Intervention Layer

Real-Time User Alerts & Feedback Via Mobile App: Notifications, Health Dashboards, Personalized Recommendations

Yellow Alert: For User Suggest behavior change or log symptoms

Orange Alert: For Nurse Passive monitoring flag or phone check-in

Red Alert: For Physician Urgent notification suggesting telehealth or in-person visit

Clinical Dashboard for Providers Web-Based Portal: View patient cohorts, drill into individual trends & alerts

Tier 5: Closed Feedback Loop & System Learning

User Actions &amp; Outcomes e.g., Followed advice, saw a doctor, got a diagnosis

Provider Actions &amp; Diagnoses e.g., Confirmed event, adjusted treatment plan

Data Feedback into Analytics Engine Reinforcement Learning to improve model accuracy &amp; reduce false alarms