Leaf Aging Fall Prediction | 植物叶片老化/脱落预测

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@user_bb47e3e3/leaf-aging-fall-prediction-analysis

Using a fixed indoor camera to continuously capture leaf images of houseplants from the same angle every day, AI vision techniques detect leaf color changes (green → yellow → brown), loss of glossiness (reduced surface reflectance), and formation of the abscission zone at the petiole base (angle change). Based on a time-series model over historical images, the skill predicts the risk window for leaf fall within the next 3-7 days. It helps users distinguish natural turnover from stress-induced leaf drop and adjust care in advance (raise humidity, fertilize, prune, etc.). Application scenarios: indoor potted plant care, plant rental companies, botanical garden greenhouses. The system generates a daily aging report and pushes alerts when leaf fall is imminent (e.g., 'lower leaves of lucky bamboo expected to fall in 3 days, prune in advance to keep it tidy'). Skill features: leaf aging and shedding are normal life-cycle events, but early shedding often signals environmental issues. AI fall-time prediction lets users clean up dead leaves proactively, keep plants tidy, and tune care based on predicted speed (e.g., higher humidity slows senescence). Can be integrated into smart planters or gardening apps for refined care recommendations. | 通过室内绿植固定摄像头连续采集叶片图像（每天同一角度），利用AI视觉分析技术检测叶片颜色变化（从绿到黄再到褐）、光泽度下降（叶面反光减弱）、叶柄基部离层形成（角度变化）等老化进程，并基于历史图像序列的时间序列模型预测未来3-7天内叶片脱落的风险时段。该技能帮助用户提前了解植物自然更新或胁迫落叶，及时调整养护（如增加湿度、施肥、修剪等）。应用场景：室内盆栽养护、绿植租赁公司、植物园温室。系统每日生成老化报告，当预测即将落叶时推送提醒（如'富贵竹下位叶预计3天后脱落，可提前剪除以保持美观'）。技能特点：叶片老化脱落是植物正常生命周期的一部分，但过早脱落可能提示环境问题。通过AI预测脱落时间，用户可提前清理枯叶，保持美观，并根据预测速度调整养护（如增加湿度可延缓衰老）。该技能可集成到智能花盆、园艺APP中，为用户提供精细化养护建议。