检测湖泊污染和生物保护的实时监测

Dr. Shalini S, K Mounika Sree, Prajwal M H, Nitin Reddy N V, P Govardhan Reddy
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摘要

这项研究揭示了一种旨在自主解决湖泊塑料污染问题的综合系统,无需人工干预。该系统利用通过 YOLO 算法处理的传感器数据和相机图像,识别塑料碎片。然后计算碎片密度,并与预设阈值进行比较。一旦超过阈值,系统就会自动向相关部门发送包含密度数据的电子邮件警报。此外,还集成了水质传感器,以持续监测环境状况。通过定期更新,可采取积极措施预防污染。这项工作展示了利用先进技术应对环境挑战和保护水生生态系统健康的成果。通过采用自动检测和监测机制,该系统提供了一种可持续的方法来消除湖泊中的塑料污染,促进环境保护工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
REAL-TIME MONITORING FOR DETECTING LAKE POLLUTION AND BIOTIC CONSERVATION
This research unveils a comprehensive system designed to tackle plastic pollution in lakes autonomously, eliminating the necessity for human intervention. By harnessing sensor data and camera imagery processed through the YOLO algorithm, the system identifies plastic debris. It then calculates the debris density and compares it against a preset threshold. Once the threshold is exceeded, an automated email alert containing the density data is sent to relevant authorities. Additionally, water quality sensors are integrated to continuously monitor environmental conditions. Regular updates are provided to enable proactive measures in pollution prevention. This endeavor showcases the utilization of advanced technology to address environmental challenges and safeguard aquatic ecosystems' health. By employing automated detection and monitoring mechanisms, the system offers a sustainable  approach to combat plastic pollution in lakes, fostering environmental conservation endeavors.
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