FLOWER IDENTIFIER — PLANT CARE
Computer vision mobile application combining live camera capture, real-time botanical classification, and comprehensive plant-care guidance.
EVIDENCE BRIEF
PROBLEM
Plant enthusiasts and gardeners frequently struggle to identify unfamiliar botanical species and diagnose plant health needs from static manual field guides.
SOLUTION
Developed a mobile application utilizing device camera feeds, image preprocessing pipelines, and cloud Vision APIs to deliver immediate species classification, botanical taxonomy, and customized care instructions.
OUTCOMES
Designed, built, and launched an AI computer vision application on the App Store featuring live camera recognition, plant taxonomy databases, and structured care guides.
- PLATFORM
- iOS
- INFERENCE
- VISION API
CLIENT REMARK
The app makes plant identification very convenient. Being able to take a photo, identify the plant, and then immediately see useful care information makes it practical for everyday use. I especially liked that it combines identification and care guidance in one place.
Nayab Fatima
Product Owner
descriptionCASE STUDY
CURATED BRIEFFlower Identifier — Plant Care
Project Context
Flower Identifier — Plant Care is a production iOS application designed to assist gardeners, plant hobbyists, and nature enthusiasts in identifying plant species and accessing actionable care information in real time.
The Challenge
Real-world botanical identification requires processing varied lighting conditions, camera angles, and partial occlusions. The mobile experience must efficiently capture high-resolution photos, preprocess images locally for bandwidth efficiency, communicate with computer vision models, and present concise care steps without latency.
Architecture & Implementation
Shahmeer Samdani engineered the client from camera integration through vision inference and App Store release:
- Camera Pipeline: Built dynamic camera controls with live autofocus, gallery selection, and local image compression for rapid upload.
- Computer Vision Pipeline: Asynchronous integration with AI Vision APIs to extract feature embeddings and match species with high confidence scores.
- Plant Care Knowledge Hub: Structured botanical data presentation covering watering schedules, sunlight requirements, soil preferences, and disease diagnostics.
- Firebase Infrastructure: Cloud backend for analytics, crash logging, and remote asset delivery.
- App Store Delivery: Handled complete Apple developer provisioning, privacy manifests, and App Store review compliance.
Key Highlights
- Live on Apple App Store with native camera workflow.
- High-accuracy computer vision classification and instant plant-care insights.
- Clean mobile architecture in Flutter with offline-resilient state handling.