+IT & Digital Systems

JerichoOng.

From physical infrastructure to digital systems.

13 years in construction project management. Now developing software, data and simulation skills to investigate how digital systems can support physical operations.

Explore my work GitHub

Tokyo, Japan

01 / 03Field to systems

A different foundation

CONSTRUCTION × TECHNOLOGY × HUMAN POTENTIAL

PORTFOLIO / 2026

01The perspective

From site constraints
to system requirements.

My starting point is construction project management: coordinating materials, crews, equipment and site information.

A late delivery can disrupt a work package. An unavailable machine can change the sequence. In practice, reliable coordination depends on knowing which conditions are confirmed and which still need review.

I’m developing my software and data skills through IT studies, a construction supply capstone and independent research. I focus on requirements, data quality and workflows that support decisions under real operational constraints.

Jericho OngConstruction experience, applied to systems requirements.

Field experience

Understand the operation

Systems thinking

Identify dependencies

Software & data

Develop and validate

02Construction & logistics systems

From material flow
to coordinated work.

Construction and logistics share the same constraints. I study how information can connect procurement, delivery and workfront readiness.

CONNECTED OPERATIONS / 01Conceptual systems blueprint

OPERATIONS / SYSTEM STUDY

Physical material flowProposed information linkHuman decision

OPERATIONAL DEPENDENCY01 / 03

Start with the material, not just the order.

A purchase order does not establish that material is ready for use. Stock records, reservations and receiving checks need to describe the same physical supply.

Shared information: Stock on hand · allocations · open orders
Constraint: Availability and receiving status
Decision point: Verify the quantity before releasing an order.

Independent research into requirements, dependencies and information handoffs.

Select a point to inspect

Construction DX

I draw on construction project management to frame requirements for inventory, procurement and site reporting. The focus is practical: reliable records, visible dependencies and accountable decisions.

Requirements analysis / operational workflows

Logistics DX

My independent research considers delivery scheduling, material flow and information exchange between suppliers and sites. API integration and event-driven coordination are research directions within that work.

Material flow / inter-system coordination

Read the research framework

03Selected work & research

Applied work.
Independent research.

A closer look at the problems I’m working on, the systems I’m studying and the evidence behind them.

FIELDOPS AI · PLANNED WORKFLOWCONCEPT

Field requirements
Software & data
Secure tools
Agentic workflow
Human approval
Auditable action

Construction and logistics experience informs the proposed workflow. Architecture and workflow design in active development · Private source.

ACTIVE DEVELOPMENT/01

Architecture & Workflow Design

Applied AI / Technical Delivery / FDE-Style Project

FieldOps AI

Bilingual Agentic Workflow for Construction & Logistics

Turning construction and logistics experience into operational requirements, then software and data workflows. FieldOps AI explores secure tool integration, agentic planning, human approval and auditable operational action.

Operational requirementsSecure toolsHuman approvalAudit trail

PRIVATE SOURCE

CASE STUDY IN DEVELOPMENT

Behind the project+

The problem

Field decisions depend on scattered operational context. A useful AI workflow needs clear requirements, controlled access to tools and a record of who approved each action.

The approach

Design a bilingual path from operational requirements through software and data, secure tool integration and agentic workflow to human approval and auditable action. The architecture illustration is a concept; provider adapters and autonomous agents are not presented as working integrations.

Evidence & status

Active development at the architecture and workflow design stage. Source remains private; the public case study is in development. FDE-style describes the project approach, not professional FDE employment. No production deployment or completed system is claimed.

SENTRIVELA · SECURITY ARCHITECTURECONCEPT

System context
Security boundary
Human review

A conceptual cybersecurity architecture illustration for Sentrivela: systems, security boundaries and human review.

PROTOTYPE/02

Early security-monitoring prototype

Cybersecurity / Security architecture

Sentrivela

A personal cybersecurity architecture project exploring security protocols and their practical application. Its early prototype explores mobile-friendly security monitoring, alerts and incident management.

PHPJavaScriptHTML / CSSSecurity architecture

PRIVATE SOURCE

Public demo not yet available

Behind the project+

The problem

Explore how security information and alerts can be made accessible for review from a mobile-friendly interface.

The approach

An early web prototype using PHP, JavaScript, HTML and CSS, with simulated alert handling. AI-assisted monitoring and incident management remain intended capabilities, not verified working features.

Evidence & status

The source README identifies work in progress. Read-only source review confirms an early prototype, and repository visibility is verified private. No public demo, production monitoring or completed system is claimed.

FROM THE FIELD TO A DECISIONILLUSTRATIVE

Site study / delivery · materials · work areas

Delivery
Site readiness
Human decision

One delayed delivery. A site full of connected decisions.

Independent research/03

Domain research / Systems architecture

Construction & Logistics DX Japan

Connecting the construction site to the supply chain. A bilingual framework for material flow, site operations and digital coordination.

Construction DXLogisticsDigital twins

Behind the project+

The problem

Materials, people and equipment are often planned in separate systems. The handoffs between them create operational friction.

The approach

Document construction sites as logistics nodes; explore JIT delivery, API coordination, IoT and digital-twin concepts.

Evidence & status

Public bilingual documentation. Conceptual architecture, not a deployed commercial system.

Explore the site decision exercise Explore the research

CONTEXT → SUGGESTION → REVIEWILLUSTRATIVE

Observed context
Proposed action
Human review

A workspace cue becomes a suggestion. A person decides.

Research framework/04

Physical AI / Human–system interaction

Embodied Anticipatory Personal Assistant

What if an assistant could understand the next useful action? A research architecture for perception, prediction and human-guided action.

Embodied AIWorld modelsHuman oversight

Behind the project+

The problem

Reactive assistants wait for a command. Real physical assistance also needs context, anticipation and safe interaction.

The approach

A perception–prediction–action loop with multimodal context, a predictive world model and explicit human oversight.

Evidence & status

Public architecture and implementation guidelines. No claim of a working robot or production deployment.

Read the architecture

MATERIAL → RECORD → REQUESTILLUSTRATIVE

Physical materials
Stock record
Order request

Connect what is on the shelf with what is needed next.

Academic project/05

Academic project / Web systems

Construction Supply Inventory & Ordering

A capstone connecting construction experience with IT: a web-based inventory and ordering system for construction supply businesses.

InventoryOrderingWeb systems

Behind the project+

The problem

Construction supply operations need a clearer connection between stock availability and customer orders.

The approach

The documented capstone focuses on a web-based inventory and ordering workflow for construction supply businesses.

Evidence & status

Listed in the public profile. A public repository, demo and completion status are not yet verified.

View project context

Currently building

Developing software and systems capability.

FieldOps AI connects my construction and logistics experience to applied AI architecture and workflow design. Sentrivela continues my cybersecurity work alongside IT studies, the construction supply capstone and independent DX documentation. SITEARM and the Omniverse learning pathway define the next research direction.

04The journey

~13 yearsConstruction project managementPhilippines · site operations

Field → ITA connected perspectiveCareer transition

BS ITETEEAP studiesUndergraduate studies in progress

IndependentConstruction & Logistics DXTechnical research & documentation

Field experience.
Technical development.

My transition into IT builds on construction project management. Formal study, practical development and continuing education are ongoing parts of that work.

Tokyo, Japan

02 / 03An evolving perspective

THE FOUNDATIONExperience

Construction project management.

13 years in construction project management in the Philippines — coordinating materials, people, equipment and the realities of site operations.

Construction operations · Project coordination

THE TRANSITIONIn progress

From site operations to information systems.

A civil-engineering academic foundation now meets ongoing BS Information Technology studies through the University of the East’s ETEEAP program.

IT studies · Construction supply capstone

THE PRESENTIndependent research

Construction & Logistics DX research.

Based in Japan, documenting Construction & Logistics DX concepts and exploring how data, automation and intelligent systems can support physical operations.

Bilingual documentation · Systems thinking

CONTINUING DEVELOPMENTOngoing learning

Management, IT & professional Japanese.

Continuing PMI learning in project management and generative AI, preparing for IPA examinations, and developing business Japanese toward BJT goals.

PMI learning · IPA preparation · BJT study

THE DIRECTIONLong-term goal

Toward systems architecture.

Build software, data and security foundations, then extend the research toward OpenUSD scene composition, NVIDIA Omniverse workflows and simulation for construction robotics.

Systems architecture · Omniverse / OpenUSD · SITEARM

05Technology & practice

Tools for
the work.

PHP and MySQL anchor my systems work. My wider toolkit covers frontend development, data analysis, technical documentation and AI-assisted development, with further study in cloud and simulation.

Core systems stack

Core PHP systems

PHP application logic, MySQL data storage and SQL queries form the core of my systems toolkit.

PHP
MySQL
SQL

Portfolio stack · installed versions

Frontend & interaction

Semantic HTML follows the HTML Living Standard. Modern CSS uses Grid, Flexbox and custom properties for responsive layouts; JavaScript uses ES modules.

Semantic HTML
Modern CSS
JavaScript (ES modules)
Next.js 16
React 19
TypeScript 6
Tailwind CSS 4
Motion 13
Lenis 1.3

Practice & continued study

Programming & development environment

Scripting, command-line work and software fundamentals.

Python
Node.js
Linux
Bash
PowerShell
Visual Studio Code

Local development & administration

Local PHP development

XAMPP for a local PHP development environment and phpMyAdmin for database administration.

XAMPP
phpMyAdmin

Data tools & continuing study

Data, interchange & business intelligence

JSON for data interchange and Power BI for reporting and visualization, alongside continued study of PostgreSQL and AWS foundations.

JSON
Microsoft Power BI
PostgreSQL
AWS foundations

Documentation workflow

Version control & technical documentation

Requirements, research notes and a traceable history of changes.

Git
GitHub
Markdown
Notion

AI in my workflow

These tools support research, coding and technical writing across overlapping workflows. Google AI Studio also supports application prototyping. I review outputs against requirements, source material and tests.

Research & technical writing

ChatGPT
Claude
Gemini
Google AI Studio

Coding & prototyping

Codex
Claude Code
Cursor
Replit
Google Antigravity
Google AI Studio

Notion supports research notes and planning; Markdown and GitHub keep technical documentation alongside the work.

Define requirements
Draft & implement
Review assumptions
Test & document

Research & learning

Event, spatial & integration systems

Technologies I am studying for construction and logistics architectures: event streams, spatial queries, shared state and service interfaces.

Apache Kafka
PostGIS
Redis
REST APIs

Learning pathway

NVIDIA Omniverse / OpenUSD

My planned progression from scene description to simulation, with construction and logistics as the application domain.

01Learning direction
OpenUSD foundations
Scene structure, coordinate systems, transforms and reusable assets.
02Planned study
Scene composition
Combine construction and logistics assets with consistent scale and documented assumptions.
03Research direction
Robotics simulation
Evaluate simulation workflows for SITEARM, including reach, collisions and the gap between models and field conditions.

PMI learning, IPA preparation & business Japanese Icon credits

06Decision Systems Lab

Operational constraints.
A decision to review.

Explore three construction coordination cases: a delivery delay, an inventory discrepancy and unavailable equipment. Review the dependencies and compare the consequences of each response.

SITE STUDY / 01Illustrative decision exercise

FIELD VIEW2.5D / CONCEPT MODEL

Site study / delivery · materials · work areas

InformationNeeds confirmationIllustrated response

CASE REVIEW01 / 04

Observe

A critical material delivery has no confirmed arrival time.

A crew and lifting equipment are booked for the dependent task.

Start with what is known.

DECISION REVIEW

Select an operational response.

Choose a response, consider its conditions, then confirm. The scene will show the possible consequence.

Your choice stays in this exercise.

BEFORE CONFIRMING

The site lead checks prerequisites, safety and crew availability before approving a change.

A proposal becomes an illustrated response only after you confirm.

Inspect the systemSource · review · data contract

BEHIND THE SCENE

A decision needs context.

This local, rule-based example connects a signal, its uncertainty, a proposed response and a human review state. It uses illustrative scenarios without sensors, personal data or a live AI connection.

Confirming a choice illustrates an outcome. It does not verify operational prerequisites or authorize work on a real site.

EXAMPLE DATA CONTRACT / NO LIVE DATA

{
  "scenario": "delivery",
  "stage": "observe",
  "source": "illustrative_no_live_data",
  "proposed_response": null,
  "human_review": "pending",
  "illustrated_response": null,
  "operational_prerequisites": "not_verified_by_this_exercise",
  "privacy_boundary": "no_personal_or_sensor_data"
}

Independent research / wearable roboticsConcept stage · simulation-first research

SITEARM

Human-centered wearable robotic assistance research for construction and logistics

Let the task define the assistance.

SITEARM explores how wearable robotic assistance could support lifting, positioning and material handling. The research begins with the worker, task, load, movement and operating environment, then investigates a body-worn upper-limb mechanism around those requirements.

Explore the concepts Research stack

Simulation-first research plan

Clarified SITEARM visual-intent illustration: a human mannequin wearing an upper-limb mechanism, with padded cuffs and a proposed torso connection. Not a CAD export. — AI-assisted illustration · not a CAD export. Inspect the separate geometry studies below.

THE RESEARCH BOUNDARY

A wearable upper-limb robotic system. Human control is a design requirement. These are design investigations—not manufactured products or validated assistance systems.

01 / The working context

Physical work is a human-system problem.

Repetitive lifting, elevated arms and constrained working positions shape construction and logistics tasks. These environments also demand perception, dexterity and judgment. SITEARM asks where wearable support could fit within that work.

The human–device system

The person is part of the mechanism.

The proposed system couples a wearable linkage to the upper body. Human motion, joint alignment, attachment interfaces and load interaction must be considered together. Kinematics, biomechanics, ergonomics and human–robot interaction frame the investigation.

02 / Design investigations

Three ways to study assistance.

Distinct task requirements. Different mechanical questions. Each concept is a proposed direction for study.

M1 / Three-quarterUNITLESS CONCEPT GEOMETRY

SITEARM M1 / Three-quarter / shared concept geometry, not a validated device

One authored assembly per concept. View controls change the camera, not the mechanism.

Inspect the proposed interfaces

Visible attachment interfaces express modularity. Each configuration would need separate alignment and load evaluation.

DESIGN STATUS

Geometry: Proposed / unitless
Actuation & materials: Not selected
Joint alignment & fit: Not evaluated
Assistance & safety: Not validated

Authored concept geometry · not to scale · no performance data

The four views and optional 3D inspection share one model per concept. Camera motion is not a kinematic simulation. Geometry, body fit and structural connections are proposed; materials, actuation and performance are not specified or validated.

SA-03 / DESIGN INVESTIGATION

SITEARM M1

Modular Task-Assist Arm

A proposed modular wearable architecture for changing between lifting, holding and guiding tasks.

Task context: Mixed construction and logistics workflows with different assistance needs.
Proposed architecture: A common body interface would accept task-specific support modules. Module geometry, attachment constraints and assistance behavior would be evaluated as a coupled configuration.
Potential benefit to investigate: Potential to adapt the assistance to the work without redesigning every body interface. Useful task coverage remains a research hypothesis.
Design limitations: Modularity adds mass, interface complexity and configuration-dependent behavior. Each combination would need its own evaluation.

THE MECHANICAL QUESTION

Can a common body interface support different task modules without compromising alignment, movement or structural load transfer?

Planned evaluation priorities

Module-interface constraints
Configuration-dependent behavior
Comparative task coverage

Modular Task-Assist Arm

03 / Research method

Begin with the person and the task.

A proposed sequence for making the design assumptions explicit before evaluating an assistance concept.

01
Task
Describe motion, object or tool, external load, duration, repetition, access and operating conditions.
02
Human model
Represent arm geometry, joint motion and the assumed range of body dimensions.
03
Wearable model
Define candidate links, human-device interfaces, joint locations, structural connections and alignment requirements.
04
Kinematics
Examine relative motion, joint limits and compatibility with human movement.
05
Workspace
Compare reachable poses with task access and clearance constraints.
06
Simulation
Evaluate selected scenarios using explicit models, assumptions, boundary conditions and evaluation criteria.
07
Results
Record supported findings, uncertainty, untested conditions and the need for physical validation.

Explore the technical scope

Kinematics

Human and wearable joint motion, relative transforms, alignment and reachable configurations.

Biomechanics

Proposed load paths, body–device interaction and the assumptions needed to interpret mechanical support.

Ergonomics

Fit, posture, contact interfaces, donning and freedom of movement as design considerations.

Human–robot interaction

User control, intention, predictable assistance and the ability to adjust or disengage support.

Task-driven design

Compare configurations against a defined task and assess suitability for each intended activity.

Simulation-first evaluation

Use models to test selected design questions before deciding whether a physical study is justified.

Reality Gap Ledger

Track assumptions about friction, compliance, fit, sensing and site conditions that may alter real behavior.

Concept validation

State the evidence needed for each design claim and distinguish a feasible model from a validated device.

04 / Research toolchain

Numerical foundations. A staged simulation path.

A selected research toolchain—not a claim of completed implementation. The first scope is numerical modeling and reproducible experiments, independent of the portfolio's browser viewer.

01Python
02Kinematics
03Blender
04Isaac Sim / Omniverse
05Future Physical AI

01 / Initial scopeSelected · implementation planned

Python + numerical foundations

Python 3.12+ for custom forward and inverse kinematics, explicit joint limits, workspace sampling and coupled human-arm / wearable-link geometry. Begin with defined test cases, not a robotics middleware stack.

Math & visualization: NumPySciPySymPyMatplotlib
Inputs → outputs: YAMLJSONCSV
Tests & quality: pytestRuff
Documentation & history: MarkdownMermaidGitGitHub

02 / NextPlanned

Geometry with traceable assumptions

Use Blender for detailed concept assemblies and consistent camera views. Add PyVista when numerical 3D inspection is useful, and mypy as the Python interfaces stabilize. Blender geometry alone does not establish physical validity.

Modeling & inspection: BlenderPyVistamypy

03 / Advanced simulationLong-term · not a dependency

NVIDIA Isaac Sim / Omniverse

Evaluate Isaac Sim, built on NVIDIA Omniverse libraries, for articulated-body physics, contact and sensor scenarios. Progress depends on model quality, explicit boundary conditions and reproducible baseline tests—not visual fidelity alone.

Planned platform: NVIDIA Isaac SimNVIDIA OmniverseOpenUSD

04 / Optional researchExploratory · outside initial scope

Physical AI, only with a research case

Isaac Lab would be considered only for a later question involving robot learning, reinforcement learning or learned control. No AI/ML model or controller is part of the initial SITEARM scope.

Conditional future direction: NVIDIA Isaac LabPhysical AI

SCOPE CONTROL

Outside the initial research scope: ROS 2, Gazebo, AI/ML, databases, Arduino and hardware control. No physical device is connected to this website.

Presentation is separate from research. This portfolio uses Next.js, React, TypeScript and an optional Three.js concept viewer. A future research-results interface may use the same web stack; React Three Fiber is an option, not a current dependency.

Platform referencesNVIDIA Isaac Sim ↗NVIDIA Isaac Lab ↗

05 / Evidence & design philosophy

A concept should carry its assumptions.

The hero illustration expresses visual intent. The separate 3D studies use consistent, authored concept geometry—not calibrated anatomy, verified CAD or solver results. No physical prototype, measured assistance or ergonomic outcome is presented. The Reality Gap Ledger and Design Passport are SITEARM documentation concepts, not external standards.

Reality Gap Ledger

A planned record of assumptions, uncertainties and validation needs. Every finding should retain the conditions under which it was obtained.

Design Passport

A planned summary of the wearable configuration, intended task, evaluation scope and limitations, linked to selected supporting evidence when available.

Public research & development boundaries

Selected public documentation

The public portfolio is intended to present selected concept studies, research questions, evaluation summaries and limitations. The level of detail would be chosen for each release.

Future development material

Detailed models, implementation methods and experimental material may remain private during future development. This publication policy applies to work as it develops; no completed internal system is implied.

06 / Future research

A planned path to evaluation.

All phases planned

01
Foundation
- Research questions and task definitions
- Human assumptions and concept architecture
02
Geometry
- Human upper-limb and wearable links
- Interfaces and candidate configurations
03
Kinematics
- Forward kinematics and joint constraints
- Reach, workspace and alignment
04
Task evaluation
- Task scenarios, clearance and loads
- Configuration comparison
05
Assistance modeling
- Proposed load paths and actuation
- Force / torque models where justified
06
Simulation
- Scenario and sensitivity analysis
- Uncertainty and failure cases
07
Evidence
- Reality Gap Ledgers and Design Passports
- Reproducible experiments and documented results
08
Physical validation
- Future / optional — not started
- Benchtop and human-device interface studies

An independent research initiative exploring how wearable robotic assistance can be shaped by real-world work.

For employers, researchers and potential collaborators interested in the research direction.

Discuss the research

07Professional development

Current studies.
Next milestones.

Current coursework, examination preparation and proposed research. Each has a different stage of progress.

Now

LEARNING & BUILDING

IT studies & construction supply capstone
Python, data & cybersecurity foundations
Construction & Logistics DX research
PMI learning: project management & generative AI

PLANNED / PREPARING

IPA FE: Fundamental Information Technology Engineer Examination preparation
IPA SG: Information Security Management Examination preparation
IPA AP: Applied Information Technology Engineer Examination, a longer-term goal
BJT Business Japanese Proficiency Test: working toward J2 / J1 target levels

Exploring

RESEARCH INTERESTS

NVIDIA Omniverse / OpenUSD: scene composition and simulation workflows
SITEARM: planned research into task-driven wearable robotic assistance
Physical AI and cyber-physical systems with human oversight

Examinations and language goals shown here are plans, not earned qualifications.

Technical documentation & independent research.

Research & documentation on GitHub

08Start a conversation

Better systems.
Built together.

I welcome conversations about construction technology, software and data systems, and simulation research. I’m continuing to develop my technical skills and looking for opportunities to contribute.

Connect on LinkedIn GitHub

Based in Japan. An international perspective.

Tokyo, Japan

03 / 03Open to collaboration

JerichoOng.

From site constraintsto system requirements.

Field experience

Systems thinking

Software & data

From material flowto coordinated work.

Start with the material, not just the order.

Construction DX

Logistics DX

Applied work.Independent research.

FieldOps AI

The problem

The approach

Evidence & status

Sentrivela

The problem

The approach

Evidence & status

Construction & Logistics DX Japan

The problem

The approach

Evidence & status

Embodied Anticipatory Personal Assistant

The problem

The approach

Evidence & status

Construction Supply Inventory & Ordering

The problem

The approach

Evidence & status

Developing software and systems capability.

Field experience.Technical development.

Construction project management.

From site operations to information systems.

Construction & Logistics DX research.

Management, IT & professional Japanese.

Toward systems architecture.

Tools forthe work.

Core PHP systems

Frontend & interaction

Programming & development environment

Local PHP development

Data, interchange & business intelligence

Version control & technical documentation

AI in my workflow

Research & technical writing

Coding & prototyping

Event, spatial & integration systems

NVIDIA Omniverse / OpenUSD

OpenUSD foundations

Scene composition

Robotics simulation

Operational constraints.A decision to review.

A critical material delivery has no confirmed arrival time.

Select an operational response.

A decision needs context.

Let the task define the assistance.

Physical work is a human-system problem.

The person is part of the mechanism.

Three ways to study assistance.

Modular Task-Assist Arm

Begin with the person and the task.

Task

Human model

Wearable model

Kinematics

Workspace

Simulation

Results

Kinematics

Biomechanics

Ergonomics

Human–robot interaction

Task-driven design

Simulation-first evaluation

Reality Gap Ledger

Concept validation

Numerical foundations. A staged simulation path.

Python + numerical foundations

Geometry with traceable assumptions

From site constraints
to system requirements.

From material flow
to coordinated work.

Applied work.
Independent research.

Field experience.
Technical development.

Tools for
the work.

Operational constraints.
A decision to review.

Current studies.
Next milestones.

Better systems.
Built together.