Minzhou Wang ¹, Taoran Jiang ¹ and Jingyi Ma ², ¹ Independent Researcher, USA ² Georgia Institute of Technology, Georgia, USA

Lawn maintenance remains a challenge for many homeowners, particularly those lacking professional horticultural knowledge, often resulting in inconsistent care quality and increased cognitive load. Traditional approaches rely heavily on manual inspection, fragmented tools, and multiple service platforms, making the process time-consuming and inefficient. Greenhub, an AI and IoT integrated lawn care platform, addresses these limitations by unifying diagnosis, task scheduling, and equipment management into a single streamlined system. Combining AI-powered image analysis with connected lawn care devices, Greenhub automatically detects lawn health issues such as diseases, weeds, and localized damage while providing actionable, context-aware solutions. Its core features, including an onboarding questionnaire, AI lawn analysis, AI assistant chat with photo upload, and AI-driven task scheduling, deliver personalized care plans and reduce user decision-making effort. Greenhub integrates AI analysis, visualization, and IoT into an all-in-one horticultural platform, reducing misinformation, clarifying source reliability, and lowering dependence on costly professionals.

Smart Lawn care, AI-driven diagnosis, Predictive maintenance, IoT, Lawn health monitoring, Robotics