I3H-DCES | Ts. Dr. Syazwan Aizat Ismail

The Unmet Challenge

Passive IAQ Logging vs Undetected Sick Building Syndrome

Traditional Building Management Systems (BMS) passively log indoor air quality parameters without tracking occupant health. Compliant sensor readings frequently mask actual Sick Building Syndrome (SBS) symptoms experienced by office occupants, hospital staff, and factory personnel.

The On-Device TinyML Innovation

I3H-DCES deploys TinyML directly on an ESP32 microcontroller at the edge. It systematically correlates multi-sensor telemetry (CO₂, TVOC, HCHO, PM2.5, PM10) with subjective occupant feedback at synchronized 15-minute intervals to generate instant, localized Health Risk Estimates without relying on cloud computation.

15 Min Synchronous Telemetry Correlation

TinyML On-Device Autonomous Risk Engine

Wall-Mount Facility Deployment Unit

TRL 7 Prototype Development Baseline

Research Leadership

About the Principal Investigator

Leading translational research in toxicovigilance, occupational health informatics, and smart environmental health technologies.

SA

Ts. Dr. Syazwan Aizat Ismail

Senior Research Officer / Principal Investigator

National Poison Centre (Pusat Racun Negara)

Universiti Sains Malaysia (USM)

Ts. (MBOT) Lead Inventor

Translating Toxicology & Edge AI Into Preventative Practice

Ts. Dr. Syazwan Aizat Ismail serves at the National Poison Centre (Pusat Racun Negara), Universiti Sains Malaysia — the national integrated reference center for clinical toxicological guidance, poison prevention, and chemical risk assessment.

Registered as a Professional Technologist with the Malaysia Board of Technologists (MBOT), his specialized research bridges toxicovigilance informatics, occupational exposure monitoring, and on-device edge intelligence (TinyML). His work transforms reactive symptom logging into autonomous, pre-emptive health governance systems for modern buildings and industry.

🔬 Research Focus

Occupational health toxicology, chemical risk surveillance, and symptom correlation.

⚡ Edge TinyML

On-device neural inference on low-power microcontrollers (ESP32/ARM Cortex).

📋 Intellectual Property

Patent Application PI2026000049 filed under Universiti Sains Malaysia.

🤝 Industrial Collaboration

Translational factory deployments under executed LOA and university matching grants.

Video Demonstration

See I3H-DCES In Operation

Watch how the embedded machine learning model processes multi-sensor arrays and triggers immediate environmental alerts.

Validated Metrics

Commercial Traction & Strategic Funding

Bridging laboratory R&D into verified factory environments with intellectual property protection and industrial sponsorship.

Signed Sponsorship (LOA)

RM 150,000.00

Sponsorship from UIS Technologies Sdn. Bhd. under a signed Letter of Award (LOA) for sub-micron metrology analytics and factory ergonomics deployment.

Includes RM10,000 IP License Fee

Grant Matching Synergy

RM 50,000.00

Endorsed for the maximum matching fund under the USM PRIME Grant Initiative, establishing a cumulative RM 200,000.00 gross pre-commercialization funding pool.

Factory Floor TRL 7 Deployment

Exhibition Recognition

GOLD MEDAL

Awarded at the National Digital & AI for Smart Health Festival (DASH 2026) for Exhibition Innovation in Healthcare Artificial Intelligence.

Health Campus USM

Live Demonstration at DASH 2026 Innovation Competition

DASH 2026 Gold Medal Award Ceremony Presentation

Collaborate & Deploy

Request a Pilot Trial Unit or Collaboration

Coordinate on-site evaluation, pilot deployment, licensing inquiries, or technical training programs.

Principal Investigator

Ts. Dr. Syazwan Aizat Ismail

National Poison Centre (Pusat Racun Negara)

Universiti Sains Malaysia (USM)

drsai@usm.my Phone: 04-6532081