Ubuntu Server — Details

Overview

Repurposed a custom-built PC to run an Ubuntu Server that hosts ROS2 simulations, Nextcloud, and personal web services with secure remote access via WireGuard.

Stack & Components

• Ubuntu Server LTS
• Docker / docker-compose for service isolation
• Nextcloud (files, calendar, contacts)
• ROS2 containers for simulation workloads
• WireGuard VPN for secure remote access

Operations & Highlights

• Automated container deployments and health checks via systemd timers and simple CI scripts.
• Managed user accounts, scheduled backups (rsync + incremental snapshots), and monitoring with basic alerting.
• Locked down public access with firewall rules and WireGuard-only admin access; used Let's Encrypt for HTTPS on web apps.

Open video demos (Nextcloud)

Smart Bench PSU — Technical Breakdown

1. Power Input & Transformation Zone

• USB-C Laptop Charger (Type-C): Provides the initial DC (example: 20V) via USB-C PD.
• USB-C PD Trigger Board: Negotiates Power Delivery with the charger to request the higher voltage (configurable via dials/jumpers), and provides the negotiated DC on dedicated terminals.
• Input Fuse Holder & Fuse: Fast-acting fuse placed immediately after the PD trigger to protect the upstream charger and wiring from downstream faults.

2. Power Regulation & Output Zone (The "Muscle")

• HiLetgo XL4015 DC-DC Step-Down Module: Main adjustable regulator. Steps the PD voltage (e.g., 20V) down to the target output (1.25V–~20V) efficiently.
• Manual / Digital Control: The XL4015's potentiometer is used for manual tuning. The ESP32 later adjusts output through a control circuit to make the supply programmable.
• INA219 Current/Voltage Sensor: Placed at the supply output to measure voltage and current (I2C interface to the ESP32). It measures a small voltage drop to compute accurate current and power values.
• Output Fuse Holder & Slow-Blow Fuse: Protects the supply and load from sustained overcurrent; slow-blow type avoids nuisance trips from inrush currents.
• Banana Jack Binding Posts: Positive/negative output terminals mounted on the enclosure, wired after INA219 and output fuse.
• NAOEVO 16 AWG Silicone Wire & Heat Shrink Tubing: High-current wiring with heat-shrink-insulated joints for safety and reliability.

3. Brains & Smart Interface Zone

• Seeed Studio XIAO ESP32C3: Reads INA219 data via I2C, broadcasts telemetry and accepts commands over BLE to adjust setpoint and limits.
• Android App (Custom): Connects over BLE to display live voltage/current and send commands (sliders/buttons) for voltage/current setpoints.
• Calibration & Test Tools: KAIWEETS HT118E DMM used during assembly to verify voltages, calibrate INA219 offsets, measure continuity, and validate the final system.

How it flows

1) Plug in your laptop charger → PD trigger negotiates 20V → 2) 20V passes through input fuse to XL4015 → 3) XL4015 steps down to desired output (e.g., 5V) → 4) Output flows through INA219 (for sensing) and output fuse → 5) Banana jacks deliver power to the load.

Safety & build notes

• Use properly-rated fuses (input: fast acting near charger max current; output: slow-blow to tolerate inrush).
• Use thick gauge (16 AWG) for high-current runs; shorten high-current traces/wires to reduce voltage drop.
• Insulate all solder joints with eventronic heat shrink and provide strain relief at enclosure pass-throughs.
• Log INA219 and calibration values in firmware; provide software overcurrent cutoffs in ESP32 to protect against faults.

Components referenced: USB-C PD trigger board, HiLetgo XL4015 DC-DC module, INA219 sensor, Seeed Studio XIAO ESP32C3, 16 AWG silicone wire, banana jack binding posts, appropriate fuse holders.

Download BOM (Markdown) Open block diagram

ESP32 (XIAO) — INA219 + BLE example (pseudo-code)

            // Pseudo/Arduino-style example (conceptual)
            #include <Wire.h>
            #include <Adafruit_INA219.h>
            #include <BLEDevice.h>

            Adafruit_INA219 ina219;

            void setup() {
                Serial.begin(115200);
                Wire.begin();
                ina219.begin(); // initialize INA219
                // start BLE peripheral, advertise service + characteristic for telemetry/control
            }

            void loop() {
                float v = ina219.getBusVoltage_V();
                float i = ina219.getCurrent_mA() / 1000.0; // amps
                // publish v and i over BLE characteristic
                // check incoming BLE commands for new setpoints, apply to control circuit
                delay(250);
            }
                            

Macro Keyboard — Details

Overview

Custom 12-key macro pad built for productivity: hand-wired matrix, per-key RGB, and flexible multi-layer firmware for OS-specific profiles.

Hardware

• Raspberry Pi Pico (RP2040) running CircuitPython / KMK
• 12 mechanical switches, diode matrix, WS2812B LEDs
• 3D-printed enclosure and custom keycaps

Firmware & Features

• KMK for multi-layer maps, macros, NKRO, and HID reports
• Layer-tap combos, sticky modifiers, and custom macros for repetitive workflows
• RGB profiles with presets and low-power behavior when host sleeps

Notes

• Implemented robust debouncing and configurable scan rate to balance responsiveness and CPU usage.
• Profile switching based on host OS detection and a hold-key combo for manual override.

Debian ARM Install — Details

Overview

Installed Debian ARM on a Lenovo Duet 5 by building a UART-over-USB SuzyQable to talk with the Cr50 and resolving bootloader and device-tree issues.

Key tasks

• Built SuzyQable (UART-over-USB) to access Cr50 debug console and bootloader.
• Flashed Debian image, patched device-tree entries for touchscreen and peripherals, and configured bootloader.
• Maintained a recovery image and detailed rollback steps.

Notes

• Documented kernel patches and DT overlays required for hardware support.
• Used serial logs and JTAG where available to diagnose boot failures.

Arduino Rover — Details

Overview

Developed navigation and obstacle-avoidance algorithms for an Arduino autonomous rover used in coursework. The project includes a control-algorithm block diagram and the navigation codebase (now included in the repository).

Download navigation code (INO) Open control algorithm diagram

Hardware

• Arduino Uno or compatible MCU
• Ultrasonic sensors (HC-SR04), IR proximity sensors
• Wheel encoders, motor driver, and DC gearmotors
• Screw-wheel omnidirectional locomotive system: an innovative screw-wheel design that enables omnidirectional movement without a conventional differential/holonomic drive. This system provides superior traction in loose terrain and allows lateral, diagonal, and rotational motion via coordinated wheel actuation.

Software

• Sensor processing: filtering (moving average + simple Kalman for noisy ultrasonic/IR readings), debouncing encoder inputs, and sensor health checks.
• Motion controller: a cascade controller combining PID for velocity control and a higher-level motion planner which commands wheel velocities to achieve omnidirectional vectors for the screw-wheel system.
• Navigation stack: waypoint manager, obstacle detection & avoidance (dynamic replanning around obstacles), and a local path smoother that generates continuous velocity vectors using a simple cubic interpolation between waypoints.
• Sensor fusion & state estimation: encoder odometry fused with range sensors to reduce drift; the system uses a lightweight complementary filter to blend short-term encoder estimates with range-based corrections.
• Safety & recovery: bump sensors, timeouts, and an emergency stop routine that halts motors and retries safe maneuvers.

Notes

• Optimized for microcontroller constraints and robust to sensor dropouts. The navigation code is organized into modular components: sensor/, control/, navigation/, and utils/ (see the INO file for inline comments).
• The control block diagram shows how sensor inputs flow into state estimation, the waypoint manager, and the motion controller which outputs per-wheel velocity setpoints for the screw-wheel actuators.
• Because the screw-wheel locomotive system accepts vector velocity commands, the motion controller translates desired chassis velocities (vx, vy, omega) into individual wheel setpoints using the kinematic mapping defined in the block diagram.

MPECWatch — Details

Overview

MPECWatch is a web application that aggregates and visualizes minor-planet observation records for astronomers and station operators.

Tech & Contributions

• Python scraping and ETL pipelines to ingest MPEC and station data
• SQLite database optimizations for a dataset with 1M+ records (indexed queries, batched inserts)
• Visualization tools using Matplotlib and client-side plotting for observatory browsing

Notes

• Improved runtime by ~40% on key scraping jobs and added robust deduplication logic.
• Implemented station filters and user-friendly pages for per-observatory analysis.

EMIT Image Labeller — Details

Overview

Image labeling tool built to accelerate annotation of methane super-emitter hotspots using map-based workflows and batch labeling by geoproximity.

Features

• Google Maps integration to visualize image coordinates and nearby infrastructure
• Batching by geoproximity to label clusters efficiently
• CSV export with metadata for ML training pipelines

Tech stack & notes

• Python back-end for image processing and CSV generation
• Front-end map UI leveraging Google Maps API
• Designed for scale and reproducible labeling workflows; integration with training pipelines yielded ~83% CNN accuracy in early experiments