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CASE STUDY · 01React Native & Expo SDK 542024–25

GardenMate Ecosystem

Custom Vision Transformer AI + Viro AR mobile platform with 12+ modules.

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GardenMate Ecosystem — 01 Auth & Login
01 Auth & Login

Personalized onboarding and secure multi-role authentication

Application Screen Flow (Click any tag to jump to that screen)
Executive Architecture

System Overview & Engineering Longevity

A full-stack mobile ecosystem engineered for React Native and Expo SDK 54, integrating spatial augmented reality, custom deep learning computer vision, and a 4-tier commerce architecture. At its algorithmic core sits a custom fine-tuned Vision Transformer (ViT-B/16) model combined with the PlantNet botanic API in a weighted 60%+40% ensemble decision pipeline. Users can test-place photorealistic 3D botanical models in physical environments using Viro React AR plane detection before purchasing via Stripe, while vendors leverage camera AI to auto-populate marketplace listings with full botanical specifications in seconds.

Core Innovations

Key Engineering Highlights

60% ViT + 40% PlantNet AI ensemble pipeline for species detection
Viro React AR plane detection for "Place Before You Buy"
Snap-to-Autolist: camera photo auto-fills complete product specs
Vendor autolist by plant name with automatic botanic graph lookup
4-role ecosystem: Customer, Vendor, Rider & Admin portals
Dispute & damage resolution portal with photo proof verification
Admin commission engine with 10% take-rate ledger & payouts
Localized micro-climate telemetry adjusting watering schedules
Deployment & Repository
Inspect GitHub Source
Technologies & Protocols
React NativeExpo SDK 54TypeScriptPyTorch (ViT)PlantNet APIFastAPIViro React (AR)Firebase SuiteStripe Mobile SDKOpenWeather APICloudinary
Production Standard

Architected with clean domain separation, strict TypeScript contracts, and automated telemetry logging.

<350ms

AI Inference Latency

FastAPI microservice response time

60% / 40%

ViT + PlantNet Split

Weighted ensemble decision engine

85%+

AR Plane Confidence

Tabletop surface detection stability

12+

Integrated Modules

End-to-end full-stack ecosystem

Execution Pipeline

End-to-End System Data Flow

How user inputs, computer vision pipelines, and transaction protocols flow across the stack.

STEP 01

Camera Frame Acquisition

User or vendor captures plant leaf or flower via camera; frame is downscaled and normalized into an RGB tensor.

STEP 02

60/40 Dual-Inference Ensemble

Image tensor is sent in parallel to PyTorch ViT-B/16 (60% weight) and PlantNet API (40% weight).

STEP 03

Confidence Fusion & Auto-Fill

Softmax probabilities are aggregated; if confidence exceeds 75%, botanical specifications are automatically populated.

STEP 04

Spatial Plane Mapping

Viro React initializes 3D coordinate planes on horizontal ground surfaces to anchor photorealistic 3D GLTF models.

STEP 05

Stripe Settlement & Commission

Order is finalized via Stripe; 10% platform commission is routed to admin ledger and 90% is settled to vendor wallet.

Module Architecture

System Capabilities & 12+ Functional Modules

12 Production Subsystems
Deep Learning & Vision

Hybrid ViT + PlantNet AI Ensemble (60% / 40%)

A proprietary dual-inference pipeline combining a fine-tuned PyTorch Vision Transformer (ViT-B/16) with the PlantNet botanical API. The model runs a 60%+40% weighted confidence fusion: 60% probability weight is allocated to the local ViT classifier and 40% to the global PlantNet API, maximizing accuracy across regional and exotic flora.

60% confidence weight from fine-tuned PyTorch Vision Transformer (ViT)
40% confidence weight from PlantNet global botanical API
Softmax probability fusion with automated confidence threshold (>75%)
FastAPI asynchronous inference microservice with GPU tensor quantization
Spatial Computing

AR Spatial Visualizer ("Place Before You Buy")

Utilizes Viro React spatial computing to detect real-world horizontal surfaces (tabletops, floors, patio grounds). Renders photorealistic 3D plant models with dynamic shadows, 360-degree rotation, scale lock, and surface confidence scoring (e.g. Tabletop · 85%).

Horizontal plane detection with real-time confidence feedback
Interactive rotation, altitude adjustment, and scale locking controls
Direct "Place in AR" integration from marketplace plant detail pages
Sub-frame latency rendering 3D GLTF botanical models
Automation AI

Vendor Snap-to-Autolist by Image

Eliminates manual catalog entry for plant nurseries. Merchants snap or upload a plant photo; the AI ensemble identifies the species (e.g. Tomato Plant · 75% confidence) and automatically populates botanical name, care requirements, sun exposure, watering cycle, and suggested price range.

One-tap camera photo or gallery upload analysis
Automated modal confirmation with detected species and confidence score
Auto-fills title, botanical description, care guide, and category tags
Reduces vendor catalog onboarding time from 10 minutes to under 15 seconds
Knowledge Graph

Vendor Autolist by Name

Merchants typing a plant name (e.g. "Golden Barrel Cactus") trigger an automated knowledge lookup that populates scientific taxonomy, recommended soil type, growth rate, and watering intervals without requiring manual research.

Taxonomic database lookup on text input keystrokes
Auto-fills optimal temperature ranges, sunlight needs, and toxicity warnings
Editable prepopulated draft cards before final marketplace publication
Personal Assistant

Care Engine & Smart Reminders

A centralized plant care management system that generates individualized schedules for watering, fertilizing, repotting, and pruning for each plant in the user garden.

Daily task queue with completion checkboxes and snooze options
Localized weather telemetry from OpenWeather API (temp, rain forecast, humidity)
Automated schedule adjustments during extreme heat or rainy seasons
E-Commerce Core

Multi-Vendor Plant Marketplace

A comprehensive marketplace connecting regional plant nurseries with plant enthusiasts. Features categorized discovery (Indoor, Outdoor, Flowers, Fruits, Deals), search filters, and AR preview badges.

Custom curated "For You" feed based on user garden history
AR quick-scan badge directly on product listing cards
Live inventory and stock status tracking (e.g. Out of Stock badges)
Payments & Cart

Multi-Item Cart & Stripe Checkout

High-performance shopping cart supporting multi-vendor purchases, regional delivery fee calculations, free delivery threshold progress indicators, and secure Stripe payment processing.

Item quantity incrementors with live stock constraints
Dynamic delivery fee calculation and promotion threshold banners
Stripe Mobile SDK checkout with multi-currency PKR/USD support
Customer Support

Order Dispute & Photo Proof Portal

A dedicated ticket-based dispute resolution system for live plant deliveries. Customers receiving damaged pots or wilted plants can file a critical ticket, upload photo evidence, and chat directly with the vendor for resolution.

Structured ticket metadata (e.g. Ticket ID, Order ID, Severity, Status)
In-chat photo proof upload with Cloudinary image storage
Real-time vendor-buyer messaging with admin escalation options
Platform Governance

Executive Admin & Commission Engine

Central administrative portal for platform governance. Monitors total collected commissions (10% platform take-rate), pending vendor disbursements, active vendor counts, total users, and open complaint tickets.

10% automated platform commission calculation on every transaction
Executive KPI overview: Total Users, Active Vendors, Listed Plants, Open Disputes
Vendor payout verification and approval state machine
Financial Ledger

Vendor Wallet & Settlement Ledger

Dedicated merchant portal displaying real-time revenue analytics, order status progression, weekly payout settlements, and balance withdrawal requests.

Gross sales vs. net earnings post 10% commission deductions
Historical transaction ledger with payout status tracking
Weekly automated bank transfer reconciliation
Social & Engagement

Gardening Community & Consultation

Interactive social hub where plant owners share progress pictures, ask botanical questions, exchange tips, and request plant health diagnoses from experienced botanists.

Photo sharing community feed with like and comment threads
Botanist verification badges for expert contributors
Direct integration linking community posts to marketplace plant listings
Security & Auth

4-Tier Role-Based Access Control

Strict architectural segregation separating Customer, Vendor, Delivery Rider, and Super Administrator interfaces with Firebase Auth and scoped Firestore security rules.

Customer portal: AR scan, care reminders, orders, and dispute filing
Vendor portal: Snap-to-autolist, inventory manager, and wallet ledger
Rider portal: Real-time routing, dispatch pickup, and delivery confirmation
Admin portal: Commission oversight, vendor audits, and system dispute mediation
Technical Hardening

Key Engineering Bottlenecks & Solutions

Challenge 01

ViT Model Latency on Mobile Devices

Running a full Vision Transformer directly on low-end mobile hardware caused thermal throttling and 3s+ latency. Engineered a hybrid architecture where lightweight tensor normalization runs on-device, while inference is dispatched to a GPU-accelerated asynchronous FastAPI microservice, dropping response times to under 350ms.

Engineered & Hardened
Challenge 02

AR Plane Jitter & Drift on Indoor Carpets

Standard plane detection struggled with low-contrast textured surfaces like carpets. Implemented a spatial confidence filter that locks coordinate axes only when surface feature tracking confidence exceeds 80%, providing rock-solid 3D plant stability.

Engineered & Hardened
Challenge 03

Accuracy Variance Across Exotic Plant Classes

Standalone models suffered from class imbalance on rare plant varieties. Architected the 60%+40% ensemble fusion: fine-tuned PyTorch ViT handles common regional species with high precision, while PlantNet API serves as a global taxonomy fail-safe.

Engineered & Hardened
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