[论文解读] Water Care: Water Surface Cleaning Bot and Water Body Surveillance System

Harsh Sankar Naicker, Yash Srivastava+5 more|arXiv (Cornell University)|Nov 24, 2021

Water Quality Monitoring Technologies被引用 4

一句话总结

本文提出了一种太阳能供电的机器人水面清洁与监控系统，利用计算机视觉技术检测并收集水面漂浮的塑料垃圾，同时通过虚拟围栏技术在污染行为发生时向相关部门发出警报。该系统集成了移动应用程序和网络控制面板，实现对水面状况的实时监控，为水体提供集预防与治理于一体的双重解决方案，以应对塑料污染问题。

ABSTRACT

Whenever a person hears about pollution, more often than not, the first thought that comes to their mind is air pollution. One of the most under-mentioned and under-discussed pollution globally is that caused by the non-biodegradable waste in our water bodies. In the case of India, there is a lot of plastic waste on the surface of rivers and lakes. The Ganga river is one of the 10 rivers which account for 90 percent of the plastic that ends up in the sea and there are major cases of local nalaas and lakes being contaminated due to this waste. This limits the source of clean water which leads to major depletion in water sources. From 2001 to 2012, in the city of Hyderabad, 3245 hectares of lakes dissipated. The water recedes by nine feet a year on average in southern New Delhi. Thus, cleaning of these local water bodies and rivers is of utmost importance. Our aim is to develop a water surface cleaning bot that is deployed across the shore. The bot will detect garbage patches on its way and collect the garbage thus making the water bodies clean. This solution employs a surveillance mechanism in order to alert the authorities in case anyone is found polluting the water bodies. A more sustainable system by using solar energy to power the system has been developed. Computer vision algorithms are used for detecting trash on the surface of the water. This trash is collected by the bot and is disposed of at a designated location. In addition to cleaning the water bodies, preventive measures have been also implemented with the help of a virtual fencing algorithm that alerts the authorities if anyone tries to pollute the water premises. A web application and a mobile app is deployed to keep a check on the movement of the bot and shore surveillance respectively. This complete solution involves both preventive and curative measures that are required for water care.

研究动机与目标

• 解决水体中塑料污染这一关键但未被充分重视的问题，特别是在印度的河流与湖泊中。
• 开发一种自主运行、太阳能供电的机器人，能够有效检测并收集水面漂浮的垃圾。
• 实施一种监控机制，实时检测并通知相关部门非法排污行为。
• 集成网络端与移动端界面，实现对机器人及水体状况的远程监控。
• 构建一种可持续的双重解决方案，兼顾垃圾清除（治疗性）与污染预防（预防性）

提出的方法

• 利用计算机视觉算法，通过机器人搭载的摄像头实时检测水面上的垃圾聚集区域。
• 在机器人上配备物理垃圾收集装置，将漂浮垃圾收集并储存在指定舱室内。
• 部署虚拟围栏算法，监测机器人接近受限区域的情况，若检测到未经授权的进入或排污行为则触发警报。
• 依靠太阳能供电，确保长期运行的可持续性并降低环境影响。
• 连接至中央网络应用与移动应用程序，实现实时追踪机器人的位置、运行状态及监控数据。
• 采用混合系统架构，结合边缘计算用于垃圾识别，以及云端数据记录与警报功能。

实验结果

研究问题

• RQ1 自主机器人如何在自然水体中有效检测并收集漂浮塑料垃圾？
• RQ2 计算机视觉算法在动态、反光的水面上对垃圾的识别准确度如何？
• RQ3 虚拟围栏系统在阻止和检测水体中非法排污行为方面的有效性如何？
• RQ4 太阳能供电的机器人系统在真实环境条件下能否保持长期运行的可持续性？
• RQ5 通过移动端与网络平台实现实时监控，如何提升水体清理作业的可扩展性与可管理性？

主要发现

• 系统通过实时计算机视觉技术成功检测并收集水面漂浮塑料垃圾，实现水面的持续清洁。
• 虚拟围栏算法能有效识别潜在污染事件并及时向相关部门发出警报，显著提升预防性监控能力。
• 太阳能供电设计确保了能源可持续性，降低了对外部电源的依赖。
• 移动应用程序与网络控制面板的集成，实现了对机器人及水体状况的实时追踪与运行监管。
• 该系统展示了可扩展的双重功能解决方案，兼顾垃圾清除与污染预防，适用于水体保护。
• 该方案在 RIACT 2021 上展示，并被选为 Springer 特刊论文发表，验证了其技术与实际应用价值。