21/08/2026
๐๐๐ ๐๐๐๐๐ณ๐๐ง๐ฌ ๐๐ซ๐ข๐ง๐ ๐๐-๐๐จ๐ฐ๐๐ซ๐๐ ๐๐๐ฌ๐๐๐ซ๐๐ก ๐ญ๐จ ๐๐ฅ๐จ๐๐๐ฅ ๐๐ญ๐๐ ๐, ๐๐๐ซ๐ง ๐๐๐ฌ๐ญ ๐๐๐ฉ๐๐ซ ๐๐ฐ๐๐ซ๐
Four Master of Information Technology (MIT) students from West Visayas State UniversityโCollege of Information and Communications Technology (WVSU-CICT) brought their research on Wireless Sensor Networks (WSN) to the international stage through ๐ญ๐ผ๐ผ๐บ on ๐๐๐ด๐๐๐ 11 at the 15๐๐ต ๐๐ป๐๐ฒ๐ฟ๐ป๐ฎ๐๐ถ๐ผ๐ป๐ฎ๐น ๐๐ผ๐ป๐ณ๐ฒ๐ฟ๐ฒ๐ป๐ฐ๐ฒ ๐ผ๐ป ๐ฆ๐บ๐ฎ๐ฟ๐ ๐ ๐ฒ๐ฑ๐ถ๐ฎ ๐ฎ๐ป๐ฑ ๐๐ฝ๐ฝ๐น๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป๐ (๐ฆ๐ ๐ 2026), held from August 10 to 12, 2026, in Ulaanbaatar, Mongolia, with one of their studies earning the conferenceโs ๐๐ฒ๐๐ ๐ฃ๐ฎ๐ฝ๐ฒ๐ฟ ๐๐๐ฎ๐ฟ๐ฑ.
Among the presented studies, the research of ๐๐ฒ๐ฟ๐ฒ๐บ ๐ฉ. ๐๐ฒ ๐๐๐๐บ๐ฎ๐ป received the ๐ฆ๐ ๐ ๐๐ฒ๐๐ ๐ฃ๐ฎ๐ฝ๐ฒ๐ฟ ๐๐๐ฎ๐ฟ๐ฑ for its AI-driven WSN architecture designed to enhance flood early warning capabilities in coastal environments. The study highlights the potential of spatially aware and intelligent sensor networks in supporting more resilient and responsive disaster preparedness systems.
Representing WVSU-CICT alongside Mr. De Guzman were ๐๐ถ๐น๐บ๐ผ๐๐ฟ ๐. ๐๐น๐บ๐ฎ๐น๐ฏ๐ถ๐, ๐ฉ๐ถ๐๐ถ๐ฒ๐ป ๐ก๐ถ๐บ๐๐ฒ ๐ข. ๐ค๐๐ถ๐บ๐ฝ๐ผ-๐๐น๐บ๐ฎ๐น๐ฏ๐ถ๐, ๐๐ฎ๐ฟ๐ฒ๐ป ๐ ๐ฎ๐ฑ๐ผ๐น๐ถ๐ป๐ฒ ๐. ๐๐ฎ๐ฏ๐ฟ๐ถ๐น๐น๐ผ๐, whose studies explored how artificial intelligence and intelligent systems can strengthen wireless sensor networks for applications in agriculture, infrastructure management, and disaster resilience.
Their respective studies focused on addressing specific challenges through AI-enabled and data-driven WSN solutions:
โข ๐๐ฒ๐ฟ๐ฒ๐บ ๐ฉ. ๐๐ฒ ๐๐๐๐บ๐ฎ๐ป โ AI-Driven Spatially Correlated WSN Architecture for Resilient Flood Early Warning in Coastal Environments
โข ๐๐ถ๐น๐บ๐ผ๐๐ฟ ๐. ๐๐น๐บ๐ฎ๐น๐ฏ๐ถ๐ โ An Edge-Computed, Cross-Layer SVM Filter for Sybil Detection in Agricultural Wireless Sensor Networks
โข ๐ฉ๐ถ๐๐ถ๐ฒ๐ป ๐ก๐ถ๐บ๐๐ฒ ๐ข. ๐ค๐๐ถ๐บ๐ฝ๐ผ-๐๐น๐บ๐ฎ๐น๐ฏ๐ถ๐ โ A Hybrid TEEN Architecture for Energy-Efficient, High-Fidelity Wireless Sensor Networks in Dense Canopy Mango Orchards
โข ๐๐ฎ๐ฟ๐ฒ๐ป ๐ ๐ฎ๐ฑ๐ผ๐น๐ถ๐ป๐ฒ ๐. ๐๐ฎ๐ฏ๐ฟ๐ถ๐น๐น๐ผ๐ โ Hybrid XAI-Driven Anomaly Management for WSN Infrastructures Using Telemetry Analytics and Predictive Behavioral Modeling
The four studies were co-authored by ๐๐ฟ. ๐ฅ๐ฒ๐ด๐ถ๐ป ๐. ๐๐ฎ๐ฏ๐ฎ๐ฐ๐ฎ๐ of WVSU-CICT, together with ๐ฃ๐ฟ๐ผ๐ณ. ๐๐ป-๐๐ผ ๐ฅ๐ฎ of ๐๐๐ป๐๐ฎ๐ป ๐ก๐ฎ๐๐ถ๐ผ๐ป๐ฎ๐น ๐จ๐ป๐ถ๐๐ฒ๐ฟ๐๐ถ๐๐. Their collaboration reflects the continuing academic and research partnership between WVSU-CICT and Kunsan National University in advancing research on intelligent and connected technologies.
Organized by the ๐๐ผ๐ฟ๐ฒ๐ฎ๐ป ๐๐ป๐๐๐ถ๐๐๐๐ฒ ๐ผ๐ณ ๐ฆ๐บ๐ฎ๐ฟ๐ ๐ ๐ฒ๐ฑ๐ถ๐ฎ (๐๐๐ฆ๐ ) under the ๐๐ผ๐ฟ๐ฒ๐ฎ ๐ฆ๐บ๐ฎ๐ฟ๐ ๐ ๐ฒ๐ฑ๐ถ๐ฎ ๐ฆ๐ผ๐ฐ๐ถ๐ฒ๐๐, SMA 2026 brought together participants from seven countries, including the Philippines, while the WVSU-CICT researchers joined the international conference remotely through Zoom.
For WVSU-CICT, the international presentation and Best Paper recognition underscore the collegeโs growing contribution to technology research that moves beyond the laboratory and addresses practical concerns in agriculture, infrastructure, and disaster resilience. Through its MIT researchers and continuing international collaborations, CICT continues to contribute to the broader digital transformation toward smarter, more connected, and resilient communities.