RRepoGEO

REPOGEO REPORT · LITE

GitHpriyanshu23/Smart-Plant-Doctor

Default branch main · commit 19098e88 · scanned 6/28/2026, 5:18:19 PM

GitHub: 706 stars · 1 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface GitHpriyanshu23/Smart-Plant-Doctor, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README H1 and opening paragraph to clarify project type

    Why:

    CURRENT
    # Smart Plant Doctor
    
    **Smart Plant Doctor** is an AI + IoT plant health platform that combines real-time environmental sensing from ESP32 devices with image-based disease detection and an AI plant care assistant.
    COPY-PASTE FIX
    # Smart Plant Doctor: Full-Stack AI + IoT Plant Health Platform Template
    
    **Smart Plant Doctor** is a production-ready, full-stack **React + FastAPI** application template for building AI + IoT plant health platforms. It combines real-time environmental sensing from ESP32 devices with image-based disease detection (MobileNetV2) and an AI plant care assistant (Gemma 4), featuring Supabase authentication, live WebSocket dashboards, and a robust API.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai, iot, plant-health, disease-detection, full-stack, react, fastapi, esp32, streamlit, supabase, machine-learning, computer-vision, real-time, websocket, pwa, gemma
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root of the repository. A common choice for open-source projects is the MIT License, which allows broad reuse.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface GitHpriyanshu23/Smart-Plant-Doctor
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AWS IoT Core
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. AWS IoT Core · recommended 2×
  2. AWS Amplify · recommended 2×
  3. Google Cloud IoT Core · recommended 2×
  4. Firebase · recommended 2×
  5. Azure Machine Learning · recommended 2×
  • CATEGORY QUERY
    How to build an AI and IoT platform for smart plant health monitoring and disease detection?
    you: not recommended
    AI recommended (in order):
    1. AWS IoT Core
    2. AWS SageMaker
    3. AWS Amplify
    4. React
    5. Google Cloud IoT Core
    6. Google Cloud AI Platform (Vertex AI)
    7. Firebase
    8. Angular
    9. Microsoft Azure IoT Hub
    10. Azure Machine Learning
    11. Azure App Service
    12. Power Apps
    13. TensorFlow Lite
    14. Raspberry Pi
    15. NVIDIA Jetson
    16. OpenVINO
    17. Intel Movidius Myriad X
    18. Grafana
    19. InfluxDB
    20. Power BI
    21. Tableau

    AI recommended 21 alternatives but never named GitHpriyanshu23/Smart-Plant-Doctor. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a full-stack template to combine real-time IoT sensor data with AI recommendations.
    you: not recommended
    AI recommended (in order):
    1. AWS IoT Core
    2. AWS Amplify
    3. SageMaker
    4. AWS IoT Rules Engine
    5. AWS Lambda
    6. AWS Kinesis Data Streams
    7. Firehose
    8. Amazon DynamoDB
    9. Amazon Timestream
    10. Amazon Personalize
    11. Google Cloud IoT Core
    12. Firebase
    13. Google Cloud AI Platform
    14. Vertex AI
    15. Google Cloud Functions
    16. Google Cloud Dataflow
    17. Google Cloud Firestore
    18. Google Cloud Bigtable
    19. Recommendation AI
    20. Azure IoT Hub
    21. Azure App Service
    22. Azure Functions
    23. Azure Machine Learning
    24. Azure Stream Analytics
    25. Azure Cosmos DB
    26. Azure SQL Database
    27. Azure Static Web Apps
    28. Node.js
    29. Python
    30. MQTT
    31. WebSockets
    32. TensorFlow.js (tensorflow/tfjs)
    33. PyTorch (pytorch/pytorch)
    34. Mosquitto (eclipse/mosquitto)
    35. EMQX (emqx/emqx)
    36. Express.js (expressjs/express)
    37. NestJS (nestjs/nest)
    38. Flask (pallets/flask)
    39. Django (django/django)
    40. socket.io (socketio/socket.io)
    41. websockets (python-websockets/websockets)
    42. PostgreSQL
    43. MongoDB
    44. InfluxDB (influxdata/influxdb)
    45. TensorFlow (tensorflow/tensorflow)
    46. React (facebook/react)
    47. Vue.js (vuejs/core)
    48. Angular (angular/angular)
    49. Home Assistant (home-assistant/core)
    50. Node-RED (node-red/node-red)
    51. SQLite
    52. MariaDB
    53. Lovelace UI
    54. scikit-learn (scikit-learn/scikit-learn)

    AI recommended 54 alternatives but never named GitHpriyanshu23/Smart-Plant-Doctor. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of GitHpriyanshu23/Smart-Plant-Doctor?
    pass
    AI did not name GitHpriyanshu23/Smart-Plant-Doctor — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts GitHpriyanshu23/Smart-Plant-Doctor in production, what risks or prerequisites should they evaluate first?
    pass
    AI named GitHpriyanshu23/Smart-Plant-Doctor explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo GitHpriyanshu23/Smart-Plant-Doctor solve, and who is the primary audience?
    pass
    AI named GitHpriyanshu23/Smart-Plant-Doctor explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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