Asil Andrei Acasio

About

From machine learning to IoT to niche little web apps, I build systems that solve real-world problems (or just for fun). My background in Electronics Engineering from UP Diliman keeps me grounded in the technical details.

I run Linux, partly for practicality, mostly for the bragging rights.

I’m currently working toward my official engineer title through the October 2025 boards.

Experience

May 2024 — October 2024

Web and Mobile App Developer Intern

Symph

Contributed to two projects involving frontend development using NextJs, backend API development with NestJS, and cloud configuration on Google Cloud Platform. This experience enhanced my technical skills and understanding of the web development lifecycle.

June 2019 — July 2019

Digital Signal Processing Lab Intern

UP EEEI

Assisted in collecting data from various signal sources such as audio from Philippine native instruments and human vital signs sensor data for research by using Python and MATLAB.

Projects

Traffic-Based Air Pollution Monitoring System for Urban Intersections

Capstone project for my undergraduate Electronics Engineering degree at UPD. Built a responsive NextJS web app to visualize real-time air pollution and traffic data with a 3D digital twin for pollutant dispersion. Developed a CoAP server in NodeJS for IoT data ingestion and storage, and implemented a Python-based vehicle tracking system using YOLO and BoT-SORT.
Python
YOLOv5
OpenCV
Raspberry Pi
NodeJs
NextJs

Automatic Smoke Observer

A remote monitoring and alerting system for forest fires mitigation, which was built with a Raspberry Pi equipped with smoke sensors and a camera. Trained and integrated a YOLOv5 model for fire and smoke detection through images. Gold awardee at the Malaysia Technology Expo 2021.
Python
Raspberry Pi
Arduino
YOLOv5
OpenCV

Personal Portfolio

My personal portfolio website built with Next.js, Tailwind CSS, and animated with Framer Motion.
ReactJs
NextJs
Tailwind

Hayahay

An IoT-based home automation system for controlling lights, fans, and other appliances. Interfaced sensor components with ESP32 microcontrollers and controlled them through a Flutter app. Built backend services with Firebase and Python.
Flutter
Python
Firebase
IoT

Buoywatch

A buoy-based system that detects and reports illegal fishing. Trained and integrated a YOLOv5 model for fishing vessel image detection. Built as an entry for the 2021 Karagatan Hackathon.
Python
OpenCV
Tensorflow
YOLOv5

© 2025 Asil Andrei Acasio. Built with Next.js and Tailwind CSS. Layout inspired from Brittany Chiang.