Externally-funded research led as Assistant Professor & Principal Investigator, SUNY Polytechnic Institute (2018–2021). Designed and deployed a low-cost, IoT-based platform for wireless structural monitoring of asphalt pavement, giving transportation agencies continuous visibility into pavement health (pressure, temperature, humidity, and strain response) so they can plan interventions before structural failure. Results published at IEEE iThings 2021.

Related prior work on pavement/asphalt characterization (validating second-order model assumptions and noise reduction methods for impact-resonance testing of asphalt concrete) published in the Journal of Nondestructive Evaluation, 2017 (Boz, Bekiroglu, Solaimanian, Tavassoti, Lagoa).

System architecture

• Sensor module — embedded sensors for pressure, temperature, humidity, and strain response
• Power module — photovoltaic panel installation for off-grid field deployment
• IoT edge module — Raspberry Pi edge node for local data acquisition and pre-processing
• LTE / 4G uplink — cellular telemetry, no wired network required
• Cloud backend — AWS-hosted ingestion, storage, and analytics
• Web interface — dashboards for live and historical readings