Jobs & Experience

Data Analyst Intern, HOYA, World 2rd lens manufacturer

(May 2024 – Jul 2024)

During my internship at HOYA, I worked with operational data to better understand how everyday processes run in a real manufacturing environment. I spent most of my time exploring production data, looking for patterns, inefficiencies, and small issues that could affect overall workflow. Through this experience, I learned how data can support practical decision-making rather than just analysis for its own sake. The internship also helped me appreciate the value of clear communication and simple, reliable systems in complex operations.

Tech Team Member, Organization of Hua Classmates (OHCM)

(Sep 2025 – Present)

As part of Hua Classmates, I’ve been helping maintain our course review website, making sure the backend data stays updated and the site runs smoothly. I regularly work with databases to add new records, fix errors, and improve how information is organized. Over time, I’ve learned how small updates can make a big difference for users, and I enjoy finding ways to make the site more reliable and user-friendly. Being part of this ongoing effort has also taught me patience, attention to detail, and how to balance technical work with practical impact.

Elderly IoT Home System Design

Link here: https://wepub.org/index.php/TCSISR/article/view/115

I designed and implemented an IoT‑driven smart home system aimed at improving safety, comfort, and independence for elderly users. The project focuses on real‑time monitoring, automated reminders, and intelligent device control, enabling family members or caregivers to remotely track the living environment and receive alerts during emergencies.

Project Overview

The system integrates multiple sensors, smart devices, and automation rules to support daily routines and safety needs of elderly individuals. It continuously collects environmental and behavioral data—such as temperature, smoke concentration, and door‑lock status—and triggers appropriate actions or alerts based on predefined conditions.

Core Features

• Automated Daily Reminders Scheduled voice prompts for medication, bathing, and sleep routines, helping elderly users maintain healthy habits.
• Smart Device Automation Automatic activation of appliances such as water heaters, lights, and air conditioners based on time or environmental conditions.
• Environmental & Safety Monitoring Real‑time detection of temperature, smoke, and door‑lock status. The system sends alerts and triggers alarms when abnormal conditions occur.
• Emergency Notification System When dangerous situations arise (e.g., smoke detected), the system immediately notifies family members or community service personnel.

Technical Architecture

The system follows a three‑layer IoT architecture:

• Perception Layer: Sensors for temperature, humidity, smoke detection, infrared control, and door‑lock status.
• Network Layer: Wi‑Fi, Bluetooth, Zigbee, and MQTT for device communication.
• Application Layer: A centralized platform for automation, monitoring, and user interaction.

Hardware & Software Stack

• Raspberry Pi 4B as the core server, running a lightweight and stable environment for continuous operation.
• Xiaomi Mijia sensors for temperature, humidity, and smoke detection.
• Xiaomi Gateway for Bluetooth/Zigbee device integration.
• BroadLink infrared controller for controlling traditional appliances like air conditioners.
• Home Assistant as the main automation platform, enabling:
  • Device discovery and integration
  • Automation rule configuration
  • HomeKit compatibility for Siri voice control
  • Local, vendor‑independent operation

Implementation Highlights

• Integrated multi‑brand smart devices into a unified Home Assistant environment.
• Configured automation rules for scheduled tasks, environmental responses, and emergency alerts.
• Implemented infrared command learning for controlling non‑smart appliances.
• Built a real‑time monitoring dashboard for caregivers and family members.
• Ensured full local control without reliance on vendor cloud services, improving privacy and reliability.

Outcome

The final system provides a comprehensive smart‑home solution tailored for elderly care. It enhances daily convenience, improves safety, and enables remote supervision. The project demonstrates practical IoT integration, cross‑platform device management, and real‑world automation design.

Awards

➡️ Mathematical Contest In Modeling Paper here (click to download): https://github.com/Carolzhxxx/Carolzhxxx.github.io/blob/main/Dandelion%20diffusion%20distribution%20model.pdf

➡️ Introduction to AMC/AIME here: https://maa.org/student-programs/amc/