Chapter 13: Presentation

Team 03 – Mapúa TechNest: "FerroScan"

The next name called was unexpected—not a team, but an individual. A tall, wiry student with sharp features, dressed in a worn gray engineering jacket with Mapúa's crest stitched over the heart, made his way alone to the center of the stage.

He wasn't flashy. No polished presentation deck. No color-coordinated entourage.

In his hands, he carried a peculiar object—something between a short staff and a handheld scanner, lined with copper coils and sleek carbon casing. Curious murmurs rippled through the audience.

The lights dimmed slightly, and he adjusted the microphone.

"My name is Carlo Javier," he began, voice calm but steady. "Fourth-year civil engineering, and this is FerroScan."

He lifted the device slightly for the audience to see.

"Infrastructure in our country is aging fast—especially in remote provinces. Yet most rebar testing equipment is either too expensive or too large to deploy on the field. We lose time, money, and sometimes, lives."

A video began to play behind him—muted tones of dusty provincial roads and half-finished bridges. Workers in helmets stood beside slabs of concrete while the device Carlo held now was gently swept over beams.

"FerroScan is a portable ground-penetrating radar scanner. It identifies microfractures in reinforced concrete, analyzes the internal rebar structure, and pushes real-time diagnostic data to a dashboard app."

A new visual emerged: a sleek tablet UI displaying red heat zones, vibrational graphs, and fracture probability indicators over structural blueprints.

"But here's what sets it apart," Carlo continued, taking a single step forward. "The scanner is embedded with a lightweight AI model—custom-trained to detect stress anomalies even before they're visible to the naked eye. No Wi-Fi needed on site. It stores and syncs once connected."

On screen, the scanner passed over a bridge piling. The interface lit up—a blinking arc in red, timestamped and GPS-tagged.

"And yes, we've field-tested it with a provincial construction crew. Accuracy rate? 93%. Cost savings? 70% cheaper than traditional GPR units. And I'm already working with the DOST for the safety certifications."

A judge from the Department of Public Works leaned forward. "What about EMI interference in dense urban zones?"

Carlo didn't blink. "The device's internal shielding is lined with a mu-metal blend. I calibrated it to isolate and filter out false positives based on the regional magnetic baseline. There's a fallback mode for manual override."

Another judge, a private sector innovation consultant, asked, "What's your production scalability plan?"

Carlo smiled faintly. "I've been prototyping with my uncle's fabrication shop in Cavite. It's modular. Assembly time: under two hours. I designed it for rural deployment—no clean rooms needed."

There was silence. Then quiet nods. A low wave of impressed murmurs followed.

But for Elias—sitting near the middle row, back straight and journal in his lap—it was something deeper.

This guy… built hardware that companies would pay for. Not just demo tech. Real tools for real-world problems.

Elias watched as Carlo stood firm, not once showing off, yet commanding the room with confidence grounded in function. His invention wasn't flashy—it was necessary.

More than inspiration, Elias felt a flicker of fire in his chest. Not envy. Not intimidation. Something more focused.

Resolve.

He scribbled furiously in his notebook:

Edge-AI on embedded device…Redundancy systems for offline sync...Application: structural safety in remote schools?

His mind was already spinning, connecting what he'd seen to his own project—ways to apply similar logic to optimize AccessEd's AI. Maybe real-time scan reports for school accessibility? Early alert triggers for dropout zones?

As Carlo gave his closing bow, the room gave him a longer, more sustained round of applause. He hadn't dazzled with design. He had shown utility.

Elias exhaled quietly.

That's the level. That's the bar. And I will meet it.

The emcee took the mic again. "Thank you, Mr. Javier. A powerful demonstration of what individual innovation can look like."

And with that, the spotlight dimmed.

But the impact remained.

Team 04 – UST Sparkline: "EduNudge"

The next team approached the stage with polished poise—three women, all wearing matching UST engineering blazers and confident smiles. Their synergy was palpable, like a trio that had rehearsed every line, every transition, down to the second.

As they stood center stage beneath the soft white lights, their lead presenter—tall, articulate, with a clear and resonant voice—stepped forward.

"We're Sparkline, from the University of Santo Tomas," she began. "And today, we want to talk about a problem that doesn't make headlines—but changes lives."

She paused, and the room quieted, intrigued.

"Dropout rates in public senior high schools."

Murmurs stirred. This wasn't a technical pitch yet—it was a social challenge. The kind of problem most platforms glossed over.

The lead speaker continued. "Every student who disappears from the system is a story interrupted. We asked: how can we use AI—not just for automation, but for compassion?"

Behind them, the screen lit up, revealing an interface unlike the usual dashboards. It wasn't all graphs and metrics—it was soft, inviting. Rounded edges. Pastel tones. A system that felt more like a digital friend than a surveillance tool.

They called it EduNudge.

"Our platform layers on top of existing LMS tools," the second member explained. "It doesn't replace your portal—it watches with empathy. It tracks engagement patterns: late logins, skipped modules, assignment hesitation, even prolonged idle time."

Then the third member added, "But we don't just track—we respond."

A simulated student login played on the big screen.

A girl named Anna logs in at 11:43 p.m. Her quiz score history shows a decline. The system detects a gap between Math module openings and video completions. Moments later, a soft notification appears on her dashboard:

Hey, Anna. We noticed you've been pushing through a lot lately. Math seems tough this week. Want to try a short confidence-boosting quiz with instant feedback?

The audience stilled.

It was… gentle.

No judgment. No red flags. Just presence.

"This is what we call behavioral AI," the lead presenter explained. "But the real innovation is the framework behind it."

They clicked to the next slide. A matrix appeared—color-coded rows indicating emotional states, paired with appropriate digital nudges. The header read:

Co-Developed with Licensed Guidance Counselors

"In partnership with public school mental health professionals," she continued, "we mapped engagement behavior to emotional triggers. Things like academic fatigue, burnout, anxiety patterns."

One of the judges—a clinical psychologist from the Department of Education—leaned forward. "So it's not just algorithmically generated responses?"

The UST presenter smiled. "Correct. Every nudge is rooted in cognitive behavioral intervention models, pre-approved by real counselors. And students can opt-in to real-time support referrals if they need more help."

The psychologist nodded, visibly impressed. "That's ethically sound. And scalable."

They showed another demo: A student named Jomar repeatedly opened and closed his quiz interface without answering. After the fourth time, EduNudge offered him a prompt:

Hi Jomar. Struggling to begin? It's okay. Let's start with just the first question. We'll guide you from there.

And on the lower corner of the screen, a link appeared:

Need someone to talk to? Click here to message a counselor.

The applause began before the video even ended.

Elias sat upright, heart steady but alert. He was watching not just a pitch—but a product of thoughtfulness. Of intention. These women had taken AI—a buzzword so often thrown around carelessly—and shaped it into something warm.

He opened his notebook.

Emotional response mapping...Attendance + emotional AI triggers = early alerts?AccessEd + mental health layer?Could school dashboards detect disengagement before dropouts happen?

His mind spun with possibilities. His system had been built for accessibility—language support, voice control, AI recommendations. But what about emotional inclusivity?

EduNudge didn't just track students—it saw them.

Back on stage, the UST team gave their closing statement.

"We believe AI doesn't have to be cold or clinical. In fact, we believe the most powerful systems are the ones that listen—without saying a word."

Thunderous applause broke out, echoing across the auditorium. Even the technical panel, often reserved in their reactions, exchanged quiet nods.

As the team bowed, Elias caught the faintest tremble in his fingertips. Not from nerves.

From recognition.

This wasn't just innovation. It was heart. And I need to meet that energy. Or surpass it.

The emcee returned to the mic. "Thank you, Sparkline. An inspiring look at how human-centered design can shape technology for good."

As they left the stage, Elias couldn't help but write one final note at the bottom of his page:

Compassion is a feature. Build it in.

Team 05 – UP Diliman Apex: "AgriSynth"

They didn't need to announce themselves—fourth-year engineering majors from a state university known for applied sciences. Their matching green collared shirts bore the name AgriSynth, embroidered near the heart.

They began without flair.

"Philippine agriculture suffers from two things," the lead presenter said evenly, "limited access to technology, and a lack of predictive data."

On the screen behind them, a drone's aerial feed played—lush farmlands, color-coded overlays shifting in real time.

"Our system combines drone vision, IoT soil sensors, and a machine learning model to forecast yield. We track irrigation efficiency, detect microclimate risk, and analyze soil health trends."

Their slide transitioned to a chart that adjusted dynamically, projecting harvest yields based on moisture levels and temperature deltas.

"What sets us apart," another member added, "is our offline-capable community dashboard. Farmers in remote barangays don't need smartphones to benefit."

That made the panel shift. One judge narrowed his eyes. "Offline? How?"

"GSM module integration. We compress sensor logs into text-packet summaries. Farmers receive yield forecasts via regular SMS. Simple, accessible."

The room leaned in. This wasn't just theory—it was implementation designed for limitations.

A pause. Then one of the industry judges, arms crossed all morning, finally nodded. "Now that's grounded innovation."

The team didn't smile or cheer. They simply stood still, professional, letting the work speak.

Elias scribbled quickly: Offline data transmission. Smart compression. Could be useful for regions with unstable net access—apply to AccessEd remote syncing?

The emcee stepped up again.

"Thank you, Team AgriSynth. With that, we conclude the morning session. Lunch will be served in the main hall—presenters for the afternoon, please prepare."

Elias closed his notebook slowly.

His time was coming.

Each of those projects had something impressive. Hardware integration. Community impact. Behavioral analysis. System design built to scale.

And he wasn't afraid. Because his system—the one he'd been refining for days in silence—was designed to intersect all of them.

AccessEd wasn't a tool. It was a platform.

It could analyze attendance patterns like EduNudge, optimize learning journeys like MediNav+, and layer on accessibility and NLP in underserved schools. It wasn't limited to students—it was structured for entire organizations, licensing, onboarding, and analytics.

"You're Elias Angeles, right?"

He stood up quickly. "Yes, ma'am."

She glanced at his ID badge and smiled faintly. "You're the first-year wildcard, aren't you?"